scope classification attributes to allowed cameras

Recording fixes (#24072 )
* pin genai review frames to the main stream * retain previews as long as either stream has recordings * watch sub stream recording health separately from main * reject record_sub on the same input as record and document the role * derive recording paths from the cache segment timestamp Recording paths carry one second of resolution, but since sub stream recording start times are resolved to fractional wall clock, anchored to the cache file mtime and chained to the previous segment's end. A stream cutting segments faster than once a second resolves consecutive segments into the same second, so two rows collide on the unique path index and the batch insert fails. The cache segment name is unique per camera stream and second by construction because ffmpeg names segments with strftime, so the recording path is now built from that timestamp while the row keeps the resolved start time. This also restores the path semantics from before sub stream recording, when start times came straight from the cache filename. Nothing derives times from recording paths: playback offsets, stream switching, and export all use the row's start time, which is unchanged, and the recordings sync matches files by exact path string. * keep the rest of a recording batch when one row conflicts * only publish record_sub status when a sub stream is configured * don't shadow camera_cfg when publishing empty cache streams * back off restarts when a recording stream goes stale * give the shared sub stream grace on any capture thread reset * include segment details in recording discard warnings
2026-09-09 04:01:42 -04:00 · 2026-08-25 14:40:13 -05:00 · 2026-08-25 11:51:58 -06:00 · 2026-08-23 14:40:32 -06:00 · 2026-08-23 10:50:03 -06:00 · 2026-08-23 10:31:31 -06:00
952 changed files with 59854 additions and 12177 deletions
@@ -8,6 +8,7 @@ amdgpu
 analyzeduration
 Annke
 apexcharts
+Aqara
 arange
 argmax
 argmin
@@ -64,6 +65,7 @@ dsize
 dtype
 ECONNRESET
 edgetpu
+Eufy
 facenet
 fastapi
 faststart
@@ -82,6 +84,7 @@ frontdoor
 fstype
 fullchain
 fullscreen
+gatekeep
 genai
 generativeai
 genpts
@@ -10,7 +10,11 @@ body:

        Before submitting, read the [beta documentation][docs].

-        [docs]: https://deploy-preview-19787--frigate-docs.netlify.app/
+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
+        [docs]: https://docs-dev.frigate.video/
+        [discussions]: https://github.com/blakeblackshear/frigate/discussions
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -22,8 +26,8 @@ body:
    id: version
    attributes:
      label: Beta Version
-      description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.17.0-beta1)
-      placeholder: "0.17.0-beta1"
+      description: Visible on the System Metrics page in the Web UI. Please include the full version including the build identifier (eg. 0.18.0-beta1, 0.18.0-8b72c7a, etc.)
+      placeholder: "0.18.0-beta1"
    validations:
      required: true
  - type: dropdown
@@ -71,11 +75,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxomox via VM
        - Windows WSL2
    validations:
      required: true
@@ -8,9 +8,12 @@ body:

        Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -87,11 +90,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxomox via VM
        - Windows WSL2
    validations:
      required: true
@@ -8,9 +8,12 @@ body:

        Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -73,11 +76,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxomox via VM
        - Windows WSL2
    validations:
      required: true
@@ -8,9 +8,12 @@ body:

        Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -53,11 +56,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxomox via VM
        - Windows WSL2
    validations:
      required: true
@@ -8,9 +8,12 @@ body:

        Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -73,11 +76,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxmox via VM
        - Windows WSL2
    validations:
      required: true
@@ -8,9 +8,12 @@ body:

        Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -69,11 +72,12 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
        - Proxmox via Docker
-        - Proxmox via TTeck Script
+        - Proxmox via installation script
+        - Proxomox via VM
        - Windows WSL2
    validations:
      required: true
@@ -10,9 +10,12 @@ body:

        **If you are looking for support, start a new discussion and use a support category.**

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: textarea
    id: description
    attributes:
@@ -6,17 +6,20 @@ body:
      value: |
        Use this form to submit a reproducible bug in Frigate or Frigate's UI.

-        **⚠️ If you are running a beta version (0.17.0-beta or similar), please use the [Beta Support template](https://github.com/blakeblackshear/frigate/discussions/new?category=beta-support) instead.**
+        **⚠️ If you are running a beta version (0.18.0-beta or similar), please use the [Beta Support template](https://github.com/blakeblackshear/frigate/discussions/new?category=beta-support) instead.**

        Before submitting your bug report, please ask the AI with the "Ask AI" button on the [official documentation site][ai] about your issue, [search the discussions][discussions], look at recent open and closed [pull requests][prs], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your bug has already been fixed by the developers or reported by the community.

        **If you are unsure if your issue is actually a bug or not, please submit a support request first.**

+        By posting here you agree to follow our [AI policy][ai-policy]. Posts that appear to be written by an AI on your behalf may be closed without a response.
+
        [discussions]: https://www.github.com/blakeblackshear/frigate/discussions
        [prs]: https://www.github.com/blakeblackshear/frigate/pulls
        [docs]: https://docs.frigate.video
        [faq]: https://github.com/blakeblackshear/frigate/discussions/12724
        [ai]: https://docs.frigate.video
+        [ai-policy]: https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
  - type: checkboxes
    attributes:
      label: Checklist
@@ -116,9 +119,13 @@ body:
    attributes:
      label: Install method
      options:
-        - Home Assistant Add-on
+        - Home Assistant App
        - Docker Compose
        - Docker CLI
+        - Proxmox via Docker
+        - Proxmox via installation script
+        - Proxomox via VM
+        - Windows WSL2
    validations:
      required: true
  - type: dropdown
@@ -7,6 +7,13 @@ assignees: ''

 ---

+<!--
+  By posting here you agree to follow our AI policy:
+  https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md
+
+  Requests that appear to be written by an AI on your behalf may be closed without a response.
+-->
+
 **Describe what you are trying to accomplish and why in non technical terms**
 I want to be able to ... so that I can ... 

@@ -1,4 +1,4 @@
-_Please read the [contributing guidelines](https://github.com/blakeblackshear/frigate/blob/dev/CONTRIBUTING.md) before submitting a PR._
+_Please read the [contributing guidelines](https://github.com/blakeblackshear/frigate/blob/dev/CONTRIBUTING.md) and the [AI policy](https://github.com/blakeblackshear/frigate/blob/dev/AI_POLICY.md) before submitting a PR. Every PR must be read and submitted by a person, and PRs that appear to be unreviewed AI output will be closed without review._

 ## Proposed change

@@ -42,6 +42,89 @@ jobs:
          tags: ${{ steps.setup.outputs.image-name }}-amd64
          cache-from: type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
          cache-to: type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64,mode=max
+  smoke_test:
+    runs-on: ubuntu-22.04
+    name: AMD64 Smoke Test
+    needs:
+      - amd64_build
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v6
+        with:
+          persist-credentials: false
+      - name: Set up QEMU and Buildx
+        id: setup
+        uses: ./.github/actions/setup
+        with:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+      - name: Start container
+        run: |
+          mkdir -p /tmp/frigate-config
+          printf 'mqtt:\n  enabled: false\ncameras: {}\n' > /tmp/frigate-config/config.yml
+          docker run -d --name frigate --shm-size 256m \
+            -v /tmp/frigate-config:/config \
+            -p 5000:5000 -p 8971:8971 \
+            ${{ steps.setup.outputs.image-name }}-amd64
+      - name: Wait for API
+        run: |
+          for i in $(seq 1 60); do
+            curl -fs http://127.0.0.1:5000/api/version && exit 0
+            sleep 5
+          done
+          echo "API never came up"; docker logs frigate; exit 1
+      - name: Assert security headers and permissions
+        run: |
+          headers=$(curl -ksI https://127.0.0.1:8971/)
+          echo "$headers"
+          echo "$headers" | grep -qi "x-content-type-options: nosniff"
+          echo "$headers" | grep -qi "referrer-policy: strict-origin-when-cross-origin"
+          # server_tokens off: Server header must not include a version.
+          # written as an if rather than "! grep", because bash exempts a
+          # negated command from set -e and the assertion would never fail
+          if echo "$headers" | grep -qiE "^server: nginx/[0-9]"; then
+            echo "Server header leaks the nginx version; server_tokens is not off"
+            exit 1
+          fi
+          # Frigate never ships frame-ancestors: HA's Webpage card and iframe
+          # panels frame it cross-origin and it would break them silently
+          if echo "$headers" | grep -qi "frame-ancestors"; then
+            echo "response carries frame-ancestors, which breaks cross-origin iframe embedding"
+            exit 1
+          fi
+          docker exec frigate /usr/local/nginx/sbin/nginx -t
+          docker exec frigate stat -c %a /etc/letsencrypt/live/frigate/privkey.pem | grep -qx 600
+          docker exec frigate stat -c %a /dev/shm/go2rtc.yaml | grep -qx 640
+      - name: Assert PUID/PGID remapping
+        run: |
+          mkdir -p /tmp/frigate-config-puid
+          printf 'mqtt:\n  enabled: false\ncameras: {}\n' > /tmp/frigate-config-puid/config.yml
+          docker run -d --name frigate-puid --shm-size 256m \
+            -e PUID=1500 -e PGID=1500 \
+            -v /tmp/frigate-config-puid:/config \
+            ${{ steps.setup.outputs.image-name }}-amd64
+          up=0
+          for i in $(seq 1 60); do
+            docker exec frigate-puid curl -fs http://127.0.0.1:5000/api/version && up=1 && break
+            sleep 5
+          done
+          if [ "$up" -ne 1 ]; then echo "PUID container never became healthy"; docker logs frigate-puid; exit 1; fi
+          docker exec frigate-puid id -u frigate | grep -qx 1500
+          docker exec frigate-puid id -g frigate | grep -qx 1500
+          docker exec frigate-puid cat /config/.permissions_version | grep -qx "1:1500:1500"
+          # second boot must skip the sweep (sentinel hit). Poll rather than
+          # sleep: the string can only come from the second boot (the first
+          # had no sentinel), so grepping the full log is unambiguous.
+          docker restart frigate-puid
+          ok=0
+          for i in $(seq 1 30); do
+            docker logs frigate-puid 2>&1 | grep -q "already applied" && ok=1 && break
+            sleep 2
+          done
+          if [ "$ok" -ne 1 ]; then echo "sentinel skip never logged"; docker logs frigate-puid; exit 1; fi
+          docker rm -f frigate-puid
+      - name: Teardown
+        if: always()
+        run: docker rm -f frigate || true
  arm64_build:
    runs-on: ubuntu-22.04-arm
    name: ARM Build
@@ -12,6 +12,7 @@ config/*
 models
 *.mp4
 *.db
+*.db-*
 *.csv
 frigate/version.py
 web/build
@@ -38,6 +38,7 @@ When reviewing code, do NOT comment on:
 - **Type Checking**: Use type hints consistently
 - **Testing**: unittest framework - use `python3 -u -m unittest` to run tests
 - **Language**: American English for all code, comments, and documentation
+- **Punctuation**: Do not use em dashes in documentation, comments, or strings; reword with standard punctuation (commas, colons, parentheses, or separate sentences)

 ### Logging Standards

@@ -0,0 +1,126 @@
+# Frigate AI Policy
+
+## TL;DR
+
+- **Use AI tools if they help you.** We do too. This is about what you post, not which tools you use to write it.
+- **A person has to read it and send it.** Don't wire a bot or an agent up to post on your behalf.
+- **Write your posts yourself.** Your own words, the template filled in, and you answering maintainers rather than your assistant.
+- **Don't paste an AI's guess at the cause as though it were a diagnosis.** Tell us what you actually observed.
+- **Read your code before you submit it.** Disclose that AI was used, and be ready to explain every line.
+- **If we misjudge something you wrote, just say so.** We'll take you at your word.
+
+The rest of this document explains each of these, and why.
+
+## Scope
+
+AI tools are a reality of modern development and we're not opposed to their use. You are responsible for anything you submit, however it was produced, and we are responsible for anything we merge and release. We hold a high bar for both.
+
+This policy applies everywhere this project is discussed: issues, discussions, pull requests, code reviews, and commit comments.
+
+## Why this exists
+
+Frigate is built and supported by a small group of maintainers and a community of volunteers who read every post and review every pull request. Nobody here is paid to do it, and time spent reading a post is time not spent fixing bugs or building features.
+
+We're not opposed to AI tools. We use them too. But content generated by an AI and submitted without review costs a real person real time, and usually gives them less to work with than a few honest sentences would have. That is the problem this policy addresses.
+
+## A person has to be in the loop
+
+Every issue, discussion, comment, and pull request here must be read and submitted by a person. Using an AI tool to help you write is fine. Wiring one up to post on your behalf is not.
+
+Specifically, do not:
+
+- Connect a bot or agent to GitHub that opens issues, discussions, or pull requests without you reading them first
+- Post output from a tool you have not read
+- Use tooling to file bulk or drive-by contributions across the repository
+
+We will close anything we believe was posted without a person reading it, and we may mark it as spam. Posts that skip the templates are the most common sign of this.
+
+## Issues, discussions, and comments
+
+We do not mind if you use AI tools to help you write. Do not have tools post unreviewed content on your behalf. We may hide any comment we believe to be unreviewed AI output.
+
+Keep posts to what is needed to communicate your point. A long, confidently written, AI-padded post is harder to help with than a short direct one, not easier, and it is usually obvious.
+
+**Describe your actual problem in your own words.** Tell us what you did, what you expected, and what actually happened. That is the information we need, and only you have it.
+
+**Do not paste an AI's guess at the cause as though it were a diagnosis.** It is frequently wrong in ways that send everyone down the wrong path, and it buries the details that would have led to the real answer. We would rather see what you observed than what a model inferred.
+
+**Fill in the template completely.** The templates ask for logs, config, version, and hardware because those are the things needed to help you. An AI cannot supply them for you, and a post missing them cannot be acted on.
+
+**Answer maintainers yourself.** If we ask you a question, we are asking _you_, not your AI assistant. These are the spaces where we build trust and understanding with the community, and that only works if we're talking to each other. Using AI to fix your grammar or clarity is fine, but the substance has to be yours.
+
+This applies to pull request descriptions and review replies as much as it does to bug reports and discussions.
+
+### Quoting AI output
+
+If you want to include something an AI told you, it must be:
+
+- In a quote block, using `>`
+- Disclosed as AI output, saying which tool it came from
+- Accompanied by your own comment explaining why you think it is relevant
+
+Keep the excerpt short. Do not paste long transcripts.
+
+### Non-native English speakers
+
+AI is genuinely useful for participating in a project that operates in English, and we would rather hear from you through a translation tool than not hear from you at all. Using AI to improve the grammar or clarity of something you wrote yourself is fine.
+
+If you are translating your posts, make sure the translation says what you meant. Including your original text in a `<details>` block helps us verify the translation if something reads oddly, and keeps the thread readable.
+
+## Code contributions
+
+We need to understand your relationship with the code you're submitting. The more AI was involved, the more important it is that you've genuinely reviewed, tested, and understood what it produced.
+
+Because of the long-term maintenance burden every merged change creates, we require a human in the loop who understands the work the AI produced. Pull requests that appear to be unreviewed AI output will be closed without review.
+
+### Requirements when AI is used
+
+If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
+
+1. **Explicitly disclose the manner in which AI was employed.** The PR template asks for this. Be honest, this won't automatically disqualify your PR. We'd rather have an honest disclosure than find out later. Trust matters more than method.
+2. **Perform a comprehensive manual review prior to submitting the pull request.** Don't submit code you haven't read carefully and tested locally.
+3. **Be prepared to explain every line of code you submitted when asked about it by a maintainer.** If you can't explain why something works the way it does, you're not ready to submit it.
+4. **Check for an existing pull request addressing the same change.** If one exists, comment there and work with its author instead of opening a duplicate.
+5. **It is strictly prohibited to use AI to write your posts for you** (bug reports, feature requests, pull request descriptions, GitHub discussions, responding to humans, etc.). We need to hear from _you_, not your AI assistant. These are the spaces where we build trust and understanding with contributors, and that only works if we're talking to each other.
+
+### Established contributors
+
+Contributors with a long history of thoughtful, quality contributions to Frigate have earned trust through that track record. The level of scrutiny we apply to AI usage naturally reflects that trust. This isn't a formal exemption, it's just how trust works. If you've been around, we know how you think and how you work. If you're new, we're still getting to know you, and clear disclosure helps build that relationship.
+
+### What this means in practice
+
+We're not trying to gatekeep how you write code. Use whatever tools make you productive. But there's a difference between using AI as a tool to implement something you understand and handing a feature request to an AI and submitting whatever comes back. The former is fine. The latter creates maintenance risk for the project.
+
+Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term, often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.
+
+One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated, where the author can't explain the design, debug issues independently, or engage substantively in design discussions, doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
+
+## Our use of AI
+
+The Frigate documentation site has an "Ask AI" search that answers questions from the docs, and we may use AI tooling to help with triage and project management. Like any automated tooling, it is not always right.
+
+If an AI tool leaves a comment on your contribution, treat it the way you would any other comment. If you think it is wrong, say so, and a brief explanation is enough. Maintainers always have the final say.
+
+## Enforcement
+
+Contributions and posts that do not follow this policy will be closed. Depending on the situation, maintainers may also:
+
+- Hide or delete comments that appear to be unreviewed AI output
+- Mark automated content as spam
+- Close an issue, discussion, or pull request without further review
+- Lock a conversation
+- Temporarily or permanently block an account from participating in the project
+
+Repeated violations may result in being blocked from contributing to Frigate.
+
+### When we get it wrong
+
+There is no reliable way to detect this, and we're not going to pretend otherwise. Whether something reads as unreviewed AI output is a judgment call, usually made quickly, by a volunteer with limited time and no way to know for certain. These calls are subjective and we won't always get them right.
+
+If it happens to you, just say so. A short reply telling us you wrote it yourself is enough, and we'll take you at your word and pick the conversation back up. We would much rather occasionally reopen something we misjudged than treat everyone who posts here as a suspect.
+
+We'd ask for some understanding in return. These calls get made quickly because the volume is real, and time spent second-guessing them is time not spent helping the person in the next thread.
+
+## Attribution
+
+Portions of this policy are adapted from the [Open Home Foundation AI Policy](https://developers.home-assistant.io/docs/ai_policy/).
@@ -2,6 +2,8 @@

 Thank you for your interest in contributing to Frigate. This document covers the expectations and guidelines for contributions. Please read it before submitting a pull request.

+All participation in this project, including pull requests, issues, and discussions, is covered by our [AI policy](AI_POLICY.md).
+
 ## Before you start

 ### Bugfixes
@@ -21,28 +23,16 @@ Before writing code for a new feature:

 ## AI usage policy

-AI tools are a reality of modern development and we're not opposed to their use. But we need to understand your relationship with the code you're submitting. The more AI was involved, the more important it is that you've genuinely reviewed, tested, and understood what it produced.
+AI tools are a reality of modern development and we're not opposed to their use. But we need to understand your relationship with the code you're submitting, and we need to hear from you rather than from your AI assistant.

-### Requirements when AI is used
+**Read the [AI policy](AI_POLICY.md) before you open a pull request.** It is short, and it applies to everything you post here. The parts that most often catch people out:

-If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
+- A person has to be in the loop. Don't wire a bot or agent up to open pull requests, issues, or discussions on your behalf.
+- Disclose how AI was used. The PR template asks for this. Be honest, it won't automatically disqualify your PR.
+- Review and test everything you submit, and be prepared to explain every line when asked.
+- Don't use AI to write your PR description or your replies to maintainers.

-1. **Explicitly disclose the manner in which AI was employed.** The PR template asks for this. Be honest — this won't automatically disqualify your PR. We'd rather have an honest disclosure than find out later. Trust matters more than method.
-2. **Perform a comprehensive manual review prior to submitting the pull request.** Don't submit code you haven't read carefully and tested locally.
-3. **Be prepared to explain every line of code they submitted when asked about it by a maintainer.** If you can't explain why something works the way it does, you're not ready to submit it.
-4. **It is strictly prohibited to use AI to write your posts for you** (bug reports, feature requests, pull request descriptions, GitHub discussions, responding to humans, etc.). We need to hear from _you_, not your AI assistant. These are the spaces where we build trust and understanding with contributors, and that only works if we're talking to each other.
-
-### Established contributors
-
-Contributors with a long history of thoughtful, quality contributions to Frigate have earned trust through that track record. The level of scrutiny we apply to AI usage naturally reflects that trust. This isn't a formal exemption — it's just how trust works. If you've been around, we know how you think and how you work. If you're new, we're still getting to know you, and clear disclosure helps build that relationship.
-
-### What this means in practice
-
-We're not trying to gatekeep how you write code. Use whatever tools make you productive. But there's a difference between using AI as a tool to implement something you understand and handing a feature request to an AI and submitting whatever comes back. The former is fine. The latter creates maintenance risk for the project.
-
-Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term — often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.
-
-One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated — where the author can't explain the design, debug issues independently, or engage substantively in design discussions — doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
+Pull requests that appear to be unreviewed AI output will be closed without review.

 ## Pull request guidelines

@@ -1,7 +1,7 @@
 default_target: local

 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
-VERSION = 0.18.0
+VERSION = 0.19.0
 IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
 GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD)
 BOARDS= #Initialized empty
@@ -24,7 +24,7 @@ yell
 sigh
 singing
 choir
-sodeling
+yodeling
 chant
 mantra
 child_singing
@@ -60,10 +60,10 @@ ARG DEBIAN_FRONTEND
 RUN --mount=type=bind,source=docker/main/build_intel_media_driver.sh,target=/deps/build_intel_media_driver.sh \
    /deps/build_intel_media_driver.sh

-FROM scratch AS go2rtc
+FROM wget AS go2rtc
 ARG TARGETARCH
-WORKDIR /rootfs/usr/local/go2rtc/bin
-ADD --link --chmod=755 "https://github.com/AlexxIT/go2rtc/releases/download/v1.9.13/go2rtc_linux_${TARGETARCH}" go2rtc
+RUN --mount=type=bind,source=docker/main/install_go2rtc.sh,target=/deps/install_go2rtc.sh \
+    /deps/install_go2rtc.sh

 FROM wget AS tempio
 ARG TARGETARCH
@@ -81,10 +81,10 @@ RUN --mount=type=bind,source=docker/main/install_tempio.sh,target=/deps/install_
 FROM base_host AS ov-converter
 ARG DEBIAN_FRONTEND

-# Install OpenVino Runtime and Dev library
+# Install OpenVINO for model conversion
 COPY docker/main/requirements-ov.txt /requirements-ov.txt
 RUN apt-get -qq update \
-    && apt-get -qq install -y wget python3 python3-dev python3-distutils gcc pkg-config libhdf5-dev \
+    && apt-get -qq install -y wget python3 python3-distutils \
    && wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
    && sed -i 's/args.append("setuptools")/args.append("setuptools==77.0.3")/' get-pip.py \
    && python3 get-pip.py "pip" \
@@ -265,6 +265,23 @@ ENV PATH="/usr/local/go2rtc/bin:/usr/local/tempio/bin:/usr/local/nginx/sbin:${PA
 RUN --mount=type=bind,source=docker/main/install_deps.sh,target=/deps/install_deps.sh \
    /deps/install_deps.sh

+# Runtime users. frigate may be remapped at start via PUID/PGID (init-usermod)
+# or replaced entirely with docker's --user. go2rtc is intentionally separate
+# and more restricted. frigate-data is the shared group for /config access.
+# -o tolerates variant base images that already contain uid/gid 1000.
+RUN groupadd -o --gid 1000 frigate \
+    && useradd -o --uid 1000 --gid frigate --no-create-home --shell /usr/sbin/nologin frigate \
+    && groupadd --system go2rtc \
+    && useradd --system --gid go2rtc --no-create-home --shell /usr/sbin/nologin go2rtc \
+    && groupadd --system frigate-data \
+    && usermod -aG frigate-data frigate \
+    && usermod -aG frigate-data go2rtc \
+    && for grp in video render plugdev audio; do \
+         if getent group "$grp" >/dev/null; then \
+           usermod -aG "$grp" frigate && usermod -aG "$grp" go2rtc; \
+         fi; \
+       done
+
 ENV DEFAULT_FFMPEG_VERSION="8.0"
 ENV INCLUDED_FFMPEG_VERSIONS="${DEFAULT_FFMPEG_VERSION}:7.0:5.0"

@@ -307,6 +324,11 @@ HEALTHCHECK --start-period=300s --start-interval=5s --interval=15s --timeout=5s
 # Frigate deps with Node.js and NPM for devcontainer
 FROM deps AS devcontainer

+# /config here is the developer's bind-mounted checkout, not a data volume, so
+# the prepare ownership sweep must not run: it would chown the source tree to
+# the runtime uid and lock out any container user that isn't 1000.
+ENV FRIGATE_RUN_AS_ROOT=true
+
 # Do not start the actual Frigate service on devcontainer as it will be started by VS Code
 # But start a fake service for simulating the logs
 COPY docker/main/fake_frigate_run /etc/s6-overlay/s6-rc.d/frigate/run
@@ -1,11 +1,106 @@
-import openvino as ov
-from openvino.tools import mo
+"""Convert the default SSDLite MobileNet v2 model to OpenVINO IR.

-ov_model = mo.convert_model(
-    "/models/ssdlite_mobilenet_v2_coco_2018_05_09/frozen_inference_graph.pb",
-    compress_to_fp16=True,
-    transformations_config="/usr/local/lib/python3.11/dist-packages/openvino/tools/mo/front/tf/ssd_v2_support.json",
-    tensorflow_object_detection_api_pipeline_config="/models/ssdlite_mobilenet_v2_coco_2018_05_09/pipeline.config",
-    reverse_input_channels=True,
+Replaces the legacy openvino-dev Model Optimizer conversion. The TensorFlow
+frontend translates the Object Detection API pre and post processors literally,
+producing per-class NonMaxSuppression, NonZero ops and map loops with data
+dependent shapes that the GPU plugin handles very badly. Both are cut out the
+way ssd_v2_support.json used to do it: the preprocessor is an identity at the
+native 300x300 input, and the postprocessor becomes a single fused
+DetectionOutput. The result is the [1, 1, 100, 7] tensor that Frigate's
+OpenVINO detector expects, with the input flipped to BGR to match the legacy
+reverse_input_channels behavior.
+"""
+
+import numpy as np
+import openvino as ov
+from openvino import opset8 as ops
+from openvino.preprocess import PrePostProcessor
+
+MODEL_DIR = "/models/ssdlite_mobilenet_v2_coco_2018_05_09"
+OUTPUT_PATH = "/models/ssdlite_mobilenet_v2.xml"
+INPUT_SHAPE = [1, 300, 300, 3]
+
+# faster_rcnn_box_coder divides the deltas by pipeline.config's y/x/height/width
+# scales of 10/10/5/5, which DetectionOutput expresses as per-prior variances.
+BOX_VARIANCES = np.float32([0.1, 0.1, 0.2, 0.2])
+
+model = ov.convert_model(
+    f"{MODEL_DIR}/frozen_inference_graph.pb",
+    input=[("image_tensor:0", INPUT_SHAPE)],
 )
-ov.save_model(ov_model, "/models/ssdlite_mobilenet_v2.xml")
+
+nodes = {op.get_friendly_name(): op for op in model.get_ordered_ops()}
+parameter = model.get_parameters()[0]
+
+preprocessor = nodes["Preprocessor/map/TensorArrayStack/TensorArrayGatherV3"]
+box_deltas = nodes["Postprocessor/Reshape_1"].output(0)
+class_scores = nodes["Postprocessor/convert_scores"].output(0)
+anchors_output = nodes["Postprocessor/Reshape"].output(0)
+
+# The anchors only depend on the static input shape, so fold them into a
+# constant and drop the generator subgraph with the rest of the postprocessor.
+probe = ov.Core().compile_model(
+    ov.Model([anchors_output, preprocessor.output(0)], [parameter], "probe"), "CPU"
+)
+probe_input = np.random.default_rng(0).integers(0, 255, INPUT_SHAPE, dtype=np.uint8)
+anchors, resized = (out.copy() for out in probe([probe_input]).values())
+
+assert np.allclose(resized, probe_input, atol=1e-3), (
+    "preprocessor is not an identity at 300x300, it cannot be bypassed"
+)
+
+image = ops.convert(parameter, "f32")
+
+for consumer in list(preprocessor.output(0).get_target_inputs()):
+    consumer.replace_source_output(image.output(0))
+
+# (ymin, xmin, ymax, xmax) -> (xmin, ymin, xmax, ymax)
+priors = anchors[:, [1, 0, 3, 2]].astype(np.float32).reshape(-1)
+variances = np.tile(BOX_VARIANCES, len(anchors))
+proposals = ops.constant(np.stack([priors, variances])[np.newaxis])
+
+# (ty, tx, th, tw) -> (dx, dy, dw, dh) for the CENTER_SIZE decode
+box_logits = ops.reshape(ops.gather(box_deltas, [1, 0, 3, 2], 1), [1, -1], False)
+class_preds = ops.reshape(class_scores, [1, -1], False)
+
+detections = ops.detection_output(
+    box_logits,
+    class_preds,
+    proposals,
+    {
+        "background_label_id": 0,
+        "top_k": 100,
+        "keep_top_k": [100],
+        "nms_threshold": 0.6,
+        "confidence_threshold": 0.3,
+        "code_type": "caffe.PriorBoxParameter.CENTER_SIZE",
+        "share_location": True,
+        "variance_encoded_in_target": False,
+        "normalized": True,
+        "clip_before_nms": False,
+        "clip_after_nms": True,
+        "decrease_label_id": False,
+    },
+)
+detections.output(0).get_tensor().set_names({"detection_out"})
+
+model = ov.Model([detections], [parameter], "ssdlite_mobilenet_v2")
+
+ppp = PrePostProcessor(model)
+ppp.input().tensor().set_layout(ov.Layout("NHWC"))
+ppp.input().preprocess().reverse_channels()
+model = ppp.build()
+
+# Fail the build rather than silently ship the dynamically shaped graph again.
+op_types = [op.get_type_name() for op in model.get_ordered_ops()]
+assert op_types.count("DetectionOutput") == 1, "postprocessor was not fused"
+
+for dynamic_op in ("NonMaxSuppression", "NonZero", "Loop", "TensorIterator"):
+    assert dynamic_op not in op_types, f"{dynamic_op} left in the graph"
+
+output_shape = model.outputs[0].get_partial_shape()
+assert output_shape.is_static and list(output_shape) == [1, 1, 100, 7], (
+    f"unexpected detector output shape {output_shape}"
+)
+
+ov.save_model(model, OUTPUT_PATH, compress_to_fp16=True)
@@ -2,7 +2,7 @@

 set -euxo pipefail

-SQLITE_VEC_VERSION="0.1.3"
+SQLITE_VEC_VERSION="0.1.9"

 source /etc/os-release

@@ -28,7 +28,13 @@ update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1
 mkdir -p -m 600 /root/.gnupg

 # install coral runtime
+# sha256 digests of the release debs; update when bumping the libedgetpu release.
+declare -A edgetpu_checksums=(
+    ["amd64"]="63fd00989d29160fa9894e115156a9abe456e88751fc9be89d26e4696200441b"
+    ["arm64"]="eab8aa4576b4dbf738135d8094f32270b24117f77147d25cbe0f49d0144d85f2"
+)
 wget -q -O /tmp/libedgetpu1-max.deb "https://github.com/feranick/libedgetpu/releases/download/16.0TF2.17.1-1/libedgetpu1-max_16.0tf2.17.1-1.bookworm_${TARGETARCH}.deb"
+echo "${edgetpu_checksums[${TARGETARCH}]}  /tmp/libedgetpu1-max.deb" | sha256sum -c -
 unset DEBIAN_FRONTEND
 yes | dpkg -i /tmp/libedgetpu1-max.deb && export DEBIAN_FRONTEND=noninteractive
 rm /tmp/libedgetpu1-max.deb
@@ -45,36 +51,41 @@ if [[ "${TARGETARCH}" == "arm64" ]]; then
    fi
 fi

+# sha256 digests of the ffmpeg builds, keyed "<install dir>-<arch>".
+# Upstream publishes no checksums; these come from a one-time fetch and guard
+# against later substitution. Update when bumping a build URL.
+declare -A ffmpeg_checksums=(
+    ["5.0-amd64"]="377abec133f9d9e8014dee1b91c9684ac8bb0b5b7d80100a57116ff837c4c0d4"
+    ["7.0-amd64"]="e13860eb90409c8218319c928067834ce450128e86f24cfed5cfe91ce6e31037"
+    ["8.0-amd64"]="9bac85054d351cdc89c0a4f45c8ea5c44df94009aabd964b719bbadd56aedae9"
+    ["5.0-arm64"]="57ee475407bad49910ba9b946428396e30cf075ea28a7912fbe1aa2578085af0"
+    ["7.0-arm64"]="16c8b04e9d0ea9c769ad964c4c453fcf05121a1947237329d2e9d8a5e43e2a3c"
+    ["8.0-arm64"]="cd91948468d0f11ce795a2cdaa0c69911bd1db313b49bb19c22512beb88cde69"
+)
+
+# the tarballs nest their binaries under a directory named for the arch, which
+# matches TARGETARCH for both builds we consume
+install_ffmpeg() {
+    local dir="$1" url="$2"
+    mkdir -p "/usr/lib/ffmpeg/${dir}"
+    wget -qO ffmpeg.tar.xz "${url}"
+    echo "${ffmpeg_checksums[${dir}-${TARGETARCH}]}  ffmpeg.tar.xz" | sha256sum -c -
+    tar -xf ffmpeg.tar.xz -C "/usr/lib/ffmpeg/${dir}" --strip-components 1 "${TARGETARCH}/bin/ffmpeg" "${TARGETARCH}/bin/ffprobe"
+    rm -f ffmpeg.tar.xz
+}
+
 # ffmpeg -> amd64
 if [[ "${TARGETARCH}" == "amd64" ]]; then
-    mkdir -p /usr/lib/ffmpeg/5.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/5.0 --strip-components 1 amd64/bin/ffmpeg amd64/bin/ffprobe
-    rm -rf ffmpeg.tar.xz
-    mkdir -p /usr/lib/ffmpeg/7.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linux64-gpl-7.0.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1 amd64/bin/ffmpeg amd64/bin/ffprobe
-    rm -rf ffmpeg.tar.xz
-    mkdir -p /usr/lib/ffmpeg/8.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2026-06-02-14-20/ffmpeg-n8.1.1-9-g58d4114d36-linux64-gpl-8.1.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/8.0 --strip-components 1 amd64/bin/ffmpeg amd64/bin/ffprobe
-    rm -rf ffmpeg.tar.xz
+    install_ffmpeg 5.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz"
+    install_ffmpeg 7.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linux64-gpl-7.0.tar.xz"
+    install_ffmpeg 8.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2026-06-02-14-20/ffmpeg-n8.1.1-9-g58d4114d36-linux64-gpl-8.1.tar.xz"
 fi

 # ffmpeg -> arm64
 if [[ "${TARGETARCH}" == "arm64" ]]; then
-    mkdir -p /usr/lib/ffmpeg/5.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linuxarm64-gpl-5.1.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/5.0 --strip-components 1 arm64/bin/ffmpeg arm64/bin/ffprobe
-    rm -f ffmpeg.tar.xz
-    mkdir -p /usr/lib/ffmpeg/7.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linuxarm64-gpl-7.0.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1 arm64/bin/ffmpeg arm64/bin/ffprobe
-    rm -f ffmpeg.tar.xz
-    mkdir -p /usr/lib/ffmpeg/8.0
-    wget -qO ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2026-06-02-14-20/ffmpeg-n8.1.1-9-g58d4114d36-linuxarm64-gpl-8.1.tar.xz"
-    tar -xf ffmpeg.tar.xz -C /usr/lib/ffmpeg/8.0 --strip-components 1 arm64/bin/ffmpeg arm64/bin/ffprobe
-    rm -f ffmpeg.tar.xz
+    install_ffmpeg 5.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linuxarm64-gpl-5.1.tar.xz"
+    install_ffmpeg 7.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linuxarm64-gpl-7.0.tar.xz"
+    install_ffmpeg 8.0 "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2026-06-02-14-20/ffmpeg-n8.1.1-9-g58d4114d36-linuxarm64-gpl-8.1.tar.xz"
 fi

 # arch specific packages
@@ -120,27 +131,56 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
    apt-get -qq install -y libtbb12

    # install legacy and standard intel compute packages
+    # sha256 digests of the driver debs, taken from the ww<week>.sum asset
+    # compute-runtime ships per release and the checksum.sha256 on npu-driver
+    # v1.19.0; intel-graphics-compiler and level-zero publish none, so those
+    # five are hash-what-you-get. Refresh after a version bump with
+    # `curl -sL <url> | sha256sum`, cross-checking upstream's sum where the
+    # release still has one. npu-driver stopped publishing them after v1.19.0.
+    declare -A intel_checksums=(
+        ["libigdgmm12_22.9.0_amd64.deb"]="9d712f71c18baee076de9961dda71e8089291e1bd0deb5d649ab5ba5de114f97"
+        ["intel-opencl-icd-legacy1_24.35.30872.36_amd64.deb"]="bbe71e4f414259e06a10cde72c29a2bd78d41b2bb2f6f8463b1806797fe66e85"
+        ["intel-level-zero-gpu-legacy1_1.5.30872.36_amd64.deb"]="40dfbd15ab62de036a00824b304a2aa1fa2d81ad60ef83da09cfe3c5a80c429f"
+        ["intel-igc-opencl_1.0.17537.24_amd64.deb"]="dd016400f87fa2b6a9fa9fbcca7eb4a2629174a29de679709f9bec5cede88b0e"
+        ["intel-igc-core_1.0.17537.24_amd64.deb"]="c1e1ecdfe2064c047c552651cfdcdafc504f2033afafba65654338b880048b67"
+        ["intel-opencl-icd_26.14.37833.4-0_amd64.deb"]="2e15eeb4fe9c1bba467a655967373eec6a20dd04cc7159de53c359f17ab53e41"
+        ["libze-intel-gpu1_26.14.37833.4-0_amd64.deb"]="34ce5791160d87ce6d54edb558a4030858ee1dad2afb067b9c5c58d4cde774c6"
+        ["intel-igc-opencl-2_2.32.7+21184_amd64.deb"]="3c9bddbfe558279402bbeaabcf9c63b8de46b956b0ad9625415fd35dda53ad52"
+        ["intel-igc-core-2_2.32.7+21184_amd64.deb"]="64e5230788e3a31e611e8d815a141b1facb91e5f0ef239233ef3f0614bfe3fd6"
+        ["level-zero_1.28.2+u22.04_amd64.deb"]="9015a579abef960166f8e943858d5c81fd4199a960f07260c1da66038257effb"
+        ["intel-driver-compiler-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb"]="8087bfcc0872d7976d0163203c7c783a4176f813c473766587e86c7b34135dff"
+        ["intel-fw-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb"]="740219c03495f8812c03ab74baf8199acf17d13929001105418d4ba226ba2290"
+        ["intel-level-zero-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb"]="f4f5eb97aa7da52c7fec97e4ddfb43aae01703bbadc767bae1f2d4faf342ba42"
+    )
+
+    fetch_intel_deb() {
+        local url="$1" name
+        name=$(basename "$url")
+        wget -q "$url"
+        echo "${intel_checksums[${name}]}  ${name}" | sha256sum -c -
+    }
+
    # see https://github.com/intel/compute-runtime/blob/master/LEGACY_PLATFORMS.md for more info
    # needed core package
-    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libigdgmm12_22.9.0_amd64.deb
+    fetch_intel_deb https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libigdgmm12_22.9.0_amd64.deb
    dpkg -i libigdgmm12_22.9.0_amd64.deb
    rm libigdgmm12_22.9.0_amd64.deb

    # legacy compute-runtime packages
-    wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-opencl-icd-legacy1_24.35.30872.36_amd64.deb
-    wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-level-zero-gpu-legacy1_1.5.30872.36_amd64.deb
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-opencl_1.0.17537.24_amd64.deb
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-core_1.0.17537.24_amd64.deb
+    fetch_intel_deb https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-opencl-icd-legacy1_24.35.30872.36_amd64.deb
+    fetch_intel_deb https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-level-zero-gpu-legacy1_1.5.30872.36_amd64.deb
+    fetch_intel_deb https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-opencl_1.0.17537.24_amd64.deb
+    fetch_intel_deb https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-core_1.0.17537.24_amd64.deb
    # standard compute-runtime packages
-    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/intel-opencl-icd_26.14.37833.4-0_amd64.deb
-    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libze-intel-gpu1_26.14.37833.4-0_amd64.deb
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-opencl-2_2.32.7+21184_amd64.deb
-    wget https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-core-2_2.32.7+21184_amd64.deb
+    fetch_intel_deb https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/intel-opencl-icd_26.14.37833.4-0_amd64.deb
+    fetch_intel_deb https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libze-intel-gpu1_26.14.37833.4-0_amd64.deb
+    fetch_intel_deb https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-opencl-2_2.32.7+21184_amd64.deb
+    fetch_intel_deb https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-core-2_2.32.7+21184_amd64.deb
    # npu packages
-    wget https://github.com/oneapi-src/level-zero/releases/download/v1.28.2/level-zero_1.28.2+u22.04_amd64.deb
-    wget https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-driver-compiler-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb
-    wget https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-fw-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb
-    wget https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-level-zero-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb
+    fetch_intel_deb https://github.com/oneapi-src/level-zero/releases/download/v1.28.2/level-zero_1.28.2+u22.04_amd64.deb
+    fetch_intel_deb https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-driver-compiler-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb
+    fetch_intel_deb https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-fw-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb
+    fetch_intel_deb https://github.com/intel/linux-npu-driver/releases/download/v1.19.0/intel-level-zero-npu_1.19.0.20250707-16111289554_ubuntu22.04_amd64.deb

    dpkg -i *.deb
    rm *.deb
@@ -0,0 +1,19 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+go2rtc_version="1.9.14"
+
+# sha256 digests of the release binaries; update when bumping go2rtc_version.
+declare -A go2rtc_checksums=(
+    ["amd64"]="32d616af226bd731678ffde328b94cfb94e30339bfefc469cfb76323144615a6"
+    ["arm64"]="359fabade8a7a51e81a55fe6df6b0ef81764a5e1d63179577534eaaa71904b50"
+)
+
+dest_dir="/rootfs/usr/local/go2rtc/bin"
+mkdir -p "${dest_dir}"
+
+wget -qO "${dest_dir}/go2rtc" \
+    "https://github.com/AlexxIT/go2rtc/releases/download/v${go2rtc_version}/go2rtc_linux_${TARGETARCH}"
+echo "${go2rtc_checksums[${TARGETARCH}]}  ${dest_dir}/go2rtc" | sha256sum -c -
+chmod 755 "${dest_dir}/go2rtc"
@@ -4,11 +4,29 @@ set -euxo pipefail

 hailo_version="4.21.0"

+# sha256 digests of the release artifacts; update when bumping hailo_version.
+# The runtime tarball is keyed by TARGETARCH, the wheel by the python arch tag.
+declare -A hailort_checksums=(
+    ["amd64"]="0a57ac5f7cc8c2c3668133189d9285b55f498e8cb219797e203f6f5015fec4b3"
+    ["arm64"]="dd840548eb5d0d147c99aee2cb013d39d64be09c5bc63061171fcfacf4547b3f"
+    ["x86_64"]="8112a973ab48095399b29d883f31987828df5861b8553f614c89f098a67b3fb6"
+    ["aarch64"]="658432a43573280d472f6402d7934669effe7f163ba3dffa31c50bbeeaa7c01d"
+)
+
 if [[ "${TARGETARCH}" == "amd64" ]]; then
    arch="x86_64"
 elif [[ "${TARGETARCH}" == "arm64" ]]; then
    arch="aarch64"
 fi

-wget -qO- "https://github.com/frigate-nvr/hailort/releases/download/v${hailo_version}/hailort-debian12-${TARGETARCH}.tar.gz" | tar -C / -xzf -
-wget -P /wheels/ "https://github.com/frigate-nvr/hailort/releases/download/v${hailo_version}/hailort-${hailo_version}-cp311-cp311-linux_${arch}.whl"
+# downloaded rather than streamed into tar because streaming and verifying the
+# digest before extraction are mutually exclusive
+wget -qO /tmp/hailort.tar.gz "https://github.com/frigate-nvr/hailort/releases/download/v${hailo_version}/hailort-debian12-${TARGETARCH}.tar.gz"
+echo "${hailort_checksums[${TARGETARCH}]}  /tmp/hailort.tar.gz" | sha256sum -c -
+tar -C / -xzf /tmp/hailort.tar.gz
+rm -f /tmp/hailort.tar.gz
+
+wheel="/wheels/hailort-${hailo_version}-cp311-cp311-linux_${arch}.whl"
+mkdir -p /wheels
+wget -qO "${wheel}" "https://github.com/frigate-nvr/hailort/releases/download/v${hailo_version}/hailort-${hailo_version}-cp311-cp311-linux_${arch}.whl"
+echo "${hailort_checksums[${arch}]}  ${wheel}" | sha256sum -c -
@@ -4,6 +4,15 @@ set -euxo pipefail

 s6_version="3.2.1.0"

+# sha256 digests of the release artifacts, from the .sha256 files published at
+# https://github.com/just-containers/s6-overlay/releases/tag/v3.2.1.0
+# Update these when bumping s6_version.
+declare -A s6_checksums=(
+    ["noarch"]="42e038a9a00fc0fef70bf0bc42f625a9c14f8ecdfe77d4ad93281edf717e10c5"
+    ["x86_64"]="8bcbc2cada58426f976b159dcc4e06cbb1454d5f39252b3bb0c778ccf71c9435"
+    ["aarch64"]="c8fd6b1f0380d399422fc986a1e6799f6a287e2cfa24813ad0b6a4fb4fa755cc"
+)
+
 if [[ "${TARGETARCH}" == "amd64" ]]; then
    s6_arch="x86_64"
 elif [[ "${TARGETARCH}" == "arm64" ]]; then
@@ -12,8 +21,15 @@ fi

 mkdir -p /rootfs/

-wget -qO- "https://github.com/just-containers/s6-overlay/releases/download/v${s6_version}/s6-overlay-noarch.tar.xz" |
-    tar -C /rootfs/ -Jxpf -
+download_and_extract() {
+    local arch="$1"
+    local tarball="/tmp/s6-overlay-${arch}.tar.xz"
+    wget -qO "${tarball}" \
+        "https://github.com/just-containers/s6-overlay/releases/download/v${s6_version}/s6-overlay-${arch}.tar.xz"
+    echo "${s6_checksums[${arch}]}  ${tarball}" | sha256sum -c -
+    tar -C /rootfs/ -Jxpf "${tarball}"
+    rm -f "${tarball}"
+}

-wget -qO- "https://github.com/just-containers/s6-overlay/releases/download/v${s6_version}/s6-overlay-${s6_arch}.tar.xz" |
-    tar -C /rootfs/ -Jxpf -
+download_and_extract "noarch"
+download_and_extract "${s6_arch}"
@@ -4,6 +4,14 @@ set -euxo pipefail

 tempio_version="2021.09.0"

+# sha256 digests of the release binaries; update when bumping tempio_version.
+# Upstream publishes no checksums, so these come from a one-time fetch and
+# guard against later substitution rather than the original download.
+declare -A tempio_checksums=(
+    ["amd64"]="b7b93ebfd24c1161cec7aecfad62ab51f2241149358cef354b86cdbc6a60546f"
+    ["aarch64"]="3a5c32981ba68b75ed9b28497429e5a5cecbeb74c3b821b035a48b37609bb895"
+)
+
 if [[ "${TARGETARCH}" == "amd64" ]]; then
    arch="amd64"
 elif [[ "${TARGETARCH}" == "arm64" ]]; then
@@ -13,4 +21,5 @@ fi
 mkdir -p /rootfs/usr/local/tempio/bin

 wget -q -O /rootfs/usr/local/tempio/bin/tempio "https://github.com/home-assistant/tempio/releases/download/${tempio_version}/tempio_${arch}"
+echo "${tempio_checksums[${arch}]}  /rootfs/usr/local/tempio/bin/tempio" | sha256sum -c -
 chmod 755 /rootfs/usr/local/tempio/bin/tempio
@@ -1,4 +1,4 @@
-ruff
+ruff == 0.15.20

 # types
 types-peewee == 3.17.*
@@ -1,3 +1,2 @@
 numpy
-tensorflow
-openvino-dev>=2024.0.0
+openvino >= 2026.2.0
@@ -79,7 +79,5 @@ sherpa-onnx==1.12.*
 faster-whisper==1.1.*
 librosa==0.11.*
 soundfile==0.13.*
-# DeGirum detector
-degirum == 0.16.*
 # Memory profiling
 memray == 1.15.*
@@ -1,4 +1,12 @@
 #!/command/with-contenv bash
 # shellcheck shell=bash

-exec logutil-service /dev/shm/logs/certsync
+if [[ "$(id -u)" -eq 0 ]]; then
+    # logutil-service drops to nobody and applies S6_LOGGING_SCRIPT
+    exec logutil-service /dev/shm/logs/certsync
+fi
+
+# Non-root (--user) fallback: logutil-service cannot change UID, so run
+# s6-log directly with the same directives S6_LOGGING_SCRIPT configures.
+# shellcheck disable=SC2086
+exec s6-log ${S6_LOGGING_SCRIPT:-T 1 n0 s10000000 T} /dev/shm/logs/certsync
@@ -1,4 +1,12 @@
 #!/command/with-contenv bash
 # shellcheck shell=bash

-exec logutil-service /dev/shm/logs/frigate
+if [[ "$(id -u)" -eq 0 ]]; then
+    # logutil-service drops to nobody and applies S6_LOGGING_SCRIPT
+    exec logutil-service /dev/shm/logs/frigate
+fi
+
+# Non-root (--user) fallback: logutil-service cannot change UID, so run
+# s6-log directly with the same directives S6_LOGGING_SCRIPT configures.
+# shellcheck disable=SC2086
+exec s6-log ${S6_LOGGING_SCRIPT:-T 1 n0 s10000000 T} /dev/shm/logs/frigate
@@ -1,4 +1,12 @@
 #!/command/with-contenv bash
 # shellcheck shell=bash

-exec logutil-service /dev/shm/logs/go2rtc
+if [[ "$(id -u)" -eq 0 ]]; then
+    # logutil-service drops to nobody and applies S6_LOGGING_SCRIPT
+    exec logutil-service /dev/shm/logs/go2rtc
+fi
+
+# Non-root (--user) fallback: logutil-service cannot change UID, so run
+# s6-log directly with the same directives S6_LOGGING_SCRIPT configures.
+# shellcheck disable=SC2086
+exec s6-log ${S6_LOGGING_SCRIPT:-T 1 n0 s10000000 T} /dev/shm/logs/go2rtc
@@ -0,0 +1,61 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Remap the frigate user to PUID/PGID and register EXTRA_GROUPS.
+# No-op when: started with --user (euid != 0), FRIGATE_RUN_AS_ROOT=true,
+# or PUID/PGID already match.
+
+set -o errexit -o nounset -o pipefail
+
+if [[ "$(id -u)" -ne 0 ]]; then
+    # Started with docker --user; the host owns UID mapping entirely.
+    exit 0
+fi
+
+if [[ "${FRIGATE_RUN_AS_ROOT:-false}" == "true" ]]; then
+    echo "[INFO] FRIGATE_RUN_AS_ROOT=true: skipping user remapping"
+    exit 0
+fi
+
+puid="${PUID:-1000}"
+pgid="${PGID:-1000}"
+
+if ! [[ "$puid" =~ ^[0-9]+$ && "$pgid" =~ ^[0-9]+$ ]]; then
+    echo "[ERROR] PUID and PGID must be numeric, got '${puid}' and '${pgid}'" >&2
+    exit 1
+fi
+
+# Remapping to 0 would make the frigate user root, so every service would keep
+# full privilege while reporting a successful migration.
+if [[ "$puid" -eq 0 || "$pgid" -eq 0 ]]; then
+    echo "[ERROR] PUID/PGID 0 would run the services as root and defeat the privilege separation." >&2
+    echo "[ERROR] Set FRIGATE_RUN_AS_ROOT=true if you want to keep running as root." >&2
+    exit 1
+fi
+
+current_uid="$(id -u frigate)"
+current_gid="$(id -g frigate)"
+
+if [[ "$puid" != "$current_uid" || "$pgid" != "$current_gid" ]]; then
+    if [[ ! -w /etc/passwd ]]; then
+        echo "[ERROR] PUID/PGID remapping needs a writable /etc and is not compatible with read_only: true." >&2
+        echo "[ERROR] Either remove read_only and keep PUID, or drop PUID/PGID and use docker's user: ${puid}:${pgid} instead." >&2
+        echo "[ERROR] See https://docs.frigate.video/configuration/non_root for the compatibility matrix." >&2
+        exit 1
+    fi
+    echo "[INFO] Remapping frigate user to ${puid}:${pgid}"
+    groupmod -o -g "$pgid" frigate
+    usermod -o -u "$puid" frigate
+fi
+
+# EXTRA_GROUPS: numeric host GIDs granting device access (e.g. host render/video)
+if [[ -n "${EXTRA_GROUPS:-}" ]]; then
+    for gid in ${EXTRA_GROUPS//,/ }; do
+        if ! getent group "$gid" >/dev/null; then
+            groupadd -o -g "$gid" "frigate-extra-${gid}"
+        fi
+        group_name="$(getent group "$gid" | cut -d: -f1)"
+        usermod -aG "$group_name" frigate
+        usermod -aG "$group_name" go2rtc
+        echo "[INFO] Added frigate and go2rtc to supplementary group ${group_name} (gid ${gid})"
+    done
+fi
@@ -0,0 +1 @@
+oneshot
@@ -0,0 +1 @@
+/etc/s6-overlay/s6-rc.d/init-usermod/run
@@ -7,5 +7,12 @@ set -o errexit -o nounset -o pipefail
 dirs=(/dev/shm/logs/frigate /dev/shm/logs/go2rtc /dev/shm/logs/nginx /dev/shm/logs/certsync)

 mkdir -p "${dirs[@]}"
-chown nobody:nogroup "${dirs[@]}"
+
+# logutil-service drops s6-log to nobody, so the dirs must stay nobody-owned
+# in root mode. Under docker --user we are already the (only) target user,
+# chown would fail, and the plain s6-log fallback in the *-log services
+# writes as us (the mkdir above is sufficient, /dev/shm is 1777).
+if [[ "$(id -u)" -eq 0 ]]; then
+    chown nobody:nogroup "${dirs[@]}"
+fi
 chmod 02755 "${dirs[@]}"
@@ -1,4 +1,12 @@
 #!/command/with-contenv bash
 # shellcheck shell=bash

-exec logutil-service /dev/shm/logs/nginx
+if [[ "$(id -u)" -eq 0 ]]; then
+    # logutil-service drops to nobody and applies S6_LOGGING_SCRIPT
+    exec logutil-service /dev/shm/logs/nginx
+fi
+
+# Non-root (--user) fallback: logutil-service cannot change UID, so run
+# s6-log directly with the same directives S6_LOGGING_SCRIPT configures.
+# shellcheck disable=SC2086
+exec s6-log ${S6_LOGGING_SCRIPT:-T 1 n0 s10000000 T} /dev/shm/logs/nginx
@@ -77,15 +77,20 @@ if [ ! \( -f "$letsencrypt_path/privkey.pem" -a -f "$letsencrypt_path/fullchain.
    openssl req -new -newkey rsa:4096 -days 365 -nodes -x509 \
        -subj "/O=FRIGATE DEFAULT CERT/CN=*" \
        -keyout "$letsencrypt_path/privkey.pem" -out "$letsencrypt_path/fullchain.pem" 2>/dev/null
+    chmod 600 "$letsencrypt_path/privkey.pem"
+    chmod 644 "$letsencrypt_path/fullchain.pem"
 fi

+# nginx settings are read once; both templates consume them
+nginx_settings=$(python3 /usr/local/nginx/get_nginx_settings.py)
+
 # build templates for optional FRIGATE_BASE_PATH environment variable
-python3 /usr/local/nginx/get_nginx_settings.py | \
+echo "$nginx_settings" | \
    tempio -template /usr/local/nginx/templates/base_path.gotmpl \
           -out /usr/local/nginx/conf/base_path.conf

 # build templates for additional network settings
-python3 /usr/local/nginx/get_nginx_settings.py | \
+echo "$nginx_settings" | \
    tempio -template /usr/local/nginx/templates/listen.gotmpl \
           -out /usr/local/nginx/conf/listen.conf

@@ -144,3 +144,16 @@ rm -f /dev/shm/.frigate-is-stopping

 migrate_addon_config_dir
 migrate_db_from_media_to_config
+
+# Align volume ownership with the runtime user (one sweep per PUID/schema
+# change, guarded by the sentinel; see fix-ownership). The escape hatch
+# deletes the sentinel instead: ownership is never mutated while it is on,
+# so the next non-root boot must re-sweep whatever root created meanwhile.
+if [[ "$(id -u)" -eq 0 ]]; then
+    if [[ "${FRIGATE_RUN_AS_ROOT:-false}" == "true" ]]; then
+        rm -f /config/.permissions_version
+    else
+        /usr/local/bin/fix-ownership --sentinel /config/.permissions_version \
+            "${PUID:-1000}" "${PGID:-1000}" /config /media/frigate
+    fi
+fi
@@ -0,0 +1,129 @@
+#!/bin/bash
+# Single source of truth for aligning volume ownership with the runtime user.
+#
+# Usage: fix-ownership [--dry-run] [--sentinel FILE] UID GID PATH [PATH...]
+#
+#   --dry-run    report what would change, touch nothing
+#   --sentinel   skip entirely when FILE already records "SCHEMA:UID:GID";
+#                write it after a successful run (used by the boot path so
+#                multi-TB volumes are swept once per UID/schema change, not
+#                on every boot)
+#
+# Only files whose uid OR gid differs are touched, so re-runs are cheap.
+# Top-level /config additionally grants group frigate-data TRAVERSE ONLY
+# (g+rx) so the separate go2rtc user can reach its pre-created HomeKit file
+# on hosts where /config is mounted 0700. Never g+w: directory write means
+# unlink rights over frigate.db/config.yml, and would let a compromised
+# go2rtc plant /config/go2rtc, which the go2rtc run script executes
+# preferentially, as root under the escape hatch.
+
+set -o errexit -o nounset -o pipefail
+
+# Permissions-layout epoch. Bump to force a one-time re-sweep on upgrade
+# (e.g. when the privilege-drop release must capture files created as root
+# since the previous sweep).
+schema=1
+
+dry_run=0
+sentinel=""
+
+while [[ "${1:-}" == --* ]]; do
+    case "$1" in
+        --dry-run) dry_run=1; shift ;;
+        --sentinel)
+            if [[ -z "${2:-}" ]]; then
+                echo "[ERROR] fix-ownership: --sentinel requires a file argument" >&2
+                exit 2
+            fi
+            sentinel="$2"; shift 2 ;;
+        *) echo "[ERROR] fix-ownership: unknown option $1" >&2; exit 2 ;;
+    esac
+done
+
+if [[ $# -lt 3 ]]; then
+    echo "Usage: fix-ownership [--dry-run] [--sentinel FILE] UID GID PATH..." >&2
+    exit 2
+fi
+
+target_uid="$1"
+target_gid="$2"
+shift 2
+
+if [[ "$(id -u)" -ne 0 ]]; then
+    echo "[INFO] fix-ownership: not running as root, skipping (ownership is managed by the host in --user mode)"
+    exit 0
+fi
+
+# A dry run always inspects: the sentinel records what a past sweep did, not
+# what the volume looks like now, and reporting from it would hide later drift.
+if [[ "$dry_run" -eq 0 && -n "$sentinel" && -f "$sentinel" && "$(cat "$sentinel")" == "${schema}:${target_uid}:${target_gid}" ]]; then
+    echo "[INFO] fix-ownership: ${target_uid}:${target_gid} (schema ${schema}) already applied, skipping"
+    exit 0
+fi
+
+# A sweep that could not chown everything must not be recorded as complete:
+# the sentinel would make every later boot skip it and the entries would stay
+# unreachable once services run unprivileged.
+swept_clean=1
+
+for path in "$@"; do
+    # An absent root is an incomplete sweep, not a finished one: /media/frigate
+    # is not in the image, so a boot before the volume is mounted would
+    # otherwise record success and the volume would never be swept once added.
+    if [[ ! -d "$path" ]]; then
+        swept_clean=0
+        echo "[WARN] fix-ownership: $path does not exist, skipping; will retry on next boot"
+        continue
+    fi
+
+    # find may fail mid-walk on a live volume (file deleted under it) or on a
+    # stale mount. Tolerate it rather than aborting under errexit, but never
+    # read a failed scan as "nothing to do": that would record the sweep as
+    # complete without having looked.
+    if ! count=$(find "$path" \( -not -uid "$target_uid" -o -not -gid "$target_gid" \) -printf '.' 2>/dev/null | wc -c); then
+        swept_clean=0
+        echo "[WARN] fix-ownership: could not scan ${path}; will retry on next boot"
+        continue
+    fi
+
+    if [[ "$count" -eq 0 ]]; then
+        echo "[INFO] fix-ownership: $path already owned by ${target_uid}:${target_gid}, nothing to do"
+        continue
+    fi
+
+    # find does not descend symlinks and chown -h retargets the link itself, so
+    # anything behind a symlinked directory is outside this sweep. Following
+    # them is not an option: a link could walk the chown out of the volume.
+    if [[ -n "$(find "$path" -type l -xtype d -print -quit 2>/dev/null)" ]]; then
+        echo "[WARN] fix-ownership: ${path} contains symlinked directories; ownership behind them is not managed and must be aligned by hand"
+    fi
+
+    echo "[WARN] fix-ownership: adjusting ownership of ${count} entries under ${path}; on large recordings volumes this can take a long time"
+    if [[ "$dry_run" -eq 1 ]]; then
+        echo "[INFO] fix-ownership: dry run, not changing ${path}"
+        continue
+    fi
+
+    find "$path" \( -not -uid "$target_uid" -o -not -gid "$target_gid" \) \
+        -exec chown -h "${target_uid}:${target_gid}" {} + || {
+        swept_clean=0
+        echo "[WARN] fix-ownership: some entries under ${path} could not be updated (deleted mid-sweep or chown denied); will retry on next mismatch"
+    }
+done
+
+# go2rtc (separate user) must be able to REACH its HomeKit state in /config.
+# Write access is per-file, not per-directory: go2rtc's PatchConfig rewrites
+# the first -config file via os.WriteFile (in-place truncate, no rename,
+# verified against go2rtc v1.9.14 internal/app/config.go), and the file is
+# always pre-created by setup_homekit_config before go2rtc starts, so
+# O_CREATE never needs directory write. See header comment for why g+w is
+# forbidden here.
+if [[ "$dry_run" -eq 0 && -d /config ]]; then
+    chgrp frigate-data /config 2>/dev/null || true
+    chmod g+rx /config 2>/dev/null || true
+fi
+
+if [[ "$dry_run" -eq 0 && -n "$sentinel" && "$swept_clean" -eq 1 ]]; then
+    echo "${schema}:${target_uid}:${target_gid}" > "$sentinel" || \
+        echo "[WARN] fix-ownership: could not write ${sentinel}; the sweep will run again on next boot"
+fi
@@ -8,14 +8,17 @@ from typing import Any
 from ruamel.yaml import YAML

 sys.path.insert(0, "/opt/frigate")
-from frigate.config.env import substitute_frigate_vars
+from frigate.config.env import apply_config_env_vars, substitute_frigate_vars
 from frigate.const import (
    BIRDSEYE_PIPE,
    LIBAVFORMAT_VERSION_MAJOR,
 )
 from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_encode
 from frigate.util.config import find_config_file, resolve_ffmpeg_path
-from frigate.util.services import is_restricted_go2rtc_source
+from frigate.util.services import (
+    is_go2rtc_arbitrary_exec_allowed,
+    is_restricted_go2rtc_source,
+)

 sys.path.remove("/opt/frigate")

@@ -34,6 +37,20 @@ try:
 except FileNotFoundError:
    config: dict[str, Any] = {}

+# No validator runs here, so install environment_vars ourselves. FRIGATE_
+# names only: anything else lands in os.environ, where the exec gate reads
+# GO2RTC_ALLOW_ARBITRARY_EXEC.
+config_env_vars = config.get("environment_vars")
+apply_config_env_vars(
+    {
+        key: value
+        for key, value in config_env_vars.items()
+        if str(key).startswith("FRIGATE_")
+    }
+    if isinstance(config_env_vars, dict)
+    else {}
+)
+
 go2rtc_config: dict[str, Any] = config.get("go2rtc", {})

 # Need to enable CORS for go2rtc so the frigate integration / card work automatically
@@ -109,7 +126,7 @@ for name in list(go2rtc_config.get("streams", {})):
                del go2rtc_config["streams"][name]
                continue
            go2rtc_config["streams"][name] = formatted_stream
-        except KeyError as e:
+        except ValueError as e:
            print(
                "[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
            )
@@ -128,7 +145,7 @@ for name in list(go2rtc_config.get("streams", {})):
                    continue

                filtered_streams.append(formatted_stream)
-            except KeyError as e:
+            except ValueError as e:
                print(
                    "[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
                )
@@ -143,6 +160,20 @@ for name in list(go2rtc_config.get("streams", {})):
            )
            del go2rtc_config["streams"][name]

+    elif isinstance(stream, dict):
+        # The map form ({"url": ...}) lets go2rtc resolve the source
+        # recursively, so it is effectively a dynamic way to generate the URL
+        # for a stream. That can only be backed by an exec source, so it cannot
+        # be allowed unless arbitrary exec is explicitly enabled. When it is
+        # enabled, leave the map untouched for go2rtc to resolve.
+        if not is_go2rtc_arbitrary_exec_allowed():
+            print(
+                f"[ERROR] Stream '{name}' uses a dynamic source format which is disabled by default for security. "
+                f"Set GO2RTC_ALLOW_ARBITRARY_EXEC=true to enable arbitrary exec sources."
+            )
+            del go2rtc_config["streams"][name]
+            continue
+
 # add birdseye restream stream if enabled
 if config.get("birdseye", {}).get("restream", False):
    birdseye: dict[str, Any] = config.get("birdseye")
@@ -158,3 +189,6 @@ if config.get("birdseye", {}).get("restream", False):
 # Write go2rtc_config to /dev/shm/go2rtc.yaml
 with open("/dev/shm/go2rtc.yaml", "w") as f:
    yaml.dump(go2rtc_config, f)
+
+# config contains camera credentials; do not leave it world-readable
+os.chmod("/dev/shm/go2rtc.yaml", 0o640)
@@ -11,6 +11,7 @@ events {

 http {
    map_hash_bucket_size 256;
+    server_tokens off;

    include mime.types;
    default_type application/octet-stream;
@@ -62,6 +63,7 @@ http {

    server {
        include listen.conf;
+        include security_headers.conf;

        # enable HTTP/2 for TLS connections to eliminate browser 6-connection limit
        http2 on;
@@ -75,6 +77,12 @@ http {
        vod_align_segments_to_key_frames on;
        vod_manifest_segment_durations_mode accurate;
        vod_ignore_edit_list on;
+        # short leading segments at each playlist start; sources start at
+        # the seek target, so the ladder applies to every seek. Only
+        # effective when clips declare real keyFrameDurations
+        vod_bootstrap_segment_durations 1000;
+        vod_bootstrap_segment_durations 2000;
+        vod_bootstrap_segment_durations 4000;
        vod_segment_duration 10000;

        # MPEG-TS settings (not used when fMP4 is enabled, kept for reference)
@@ -117,6 +125,7 @@ http {
            secure_token $args;
            secure_token_types application/vnd.apple.mpegurl;

+            include security_headers.conf;
            add_header Cache-Control "no-store";
            expires off;

@@ -133,6 +142,7 @@ http {

        location /stream/ {
            include auth_request.conf;
+            include security_headers.conf;
            add_header Cache-Control "no-store";
            expires off;

@@ -154,6 +164,7 @@ http {
            }

            expires 7d;
+            include security_headers.conf;
            add_header Cache-Control "public";
            autoindex on;
            root /media/frigate;
@@ -246,6 +257,7 @@ http {

        location /api/ {
            include auth_request.conf;
+            include security_headers.conf;
            add_header Cache-Control "no-store";
            expires off;
            proxy_pass http://frigate_api/;
@@ -274,6 +286,13 @@ http {
                include proxy.conf;
            }

+            location /api/logout {
+                auth_request off;
+                rewrite ^/api(/.*)$ $1 break;
+                proxy_pass http://frigate_api;
+                include proxy.conf;
+            }
+
            # Allow unauthenticated access to the first_time_login endpoint
            # so the login page can load help text before authentication.
            location /api/auth/first_time_login {
@@ -305,29 +324,34 @@ http {

        location / {
            # do not require auth for static assets
+            include security_headers.conf;
            add_header Cache-Control "no-store";
            expires off;

            location /assets/ {
                access_log off;
                expires 1y;
+                include security_headers.conf;
                add_header Cache-Control "public";
            }

            location /fonts/ {
                access_log off;
                expires 1y;
+                include security_headers.conf;
                add_header Cache-Control "public";
            }

            location /locales/ {
                access_log off;
+                include security_headers.conf;
                add_header Cache-Control "public";
            }

            location ~ ^/.*-([A-Za-z0-9]+)\.webmanifest$ {
                access_log off;
                expires 1y;
+                include security_headers.conf;
                add_header Cache-Control "public";
                default_type application/json;
                proxy_set_header Accept-Encoding "";
@@ -0,0 +1,5 @@
+# Deliberately no X-Frame-Options or CSP frame-ancestors: HA's Webpage card and
+# iframe panels frame Frigate cross-origin, and either would break them
+# silently. Bind-mount this file to add your own.
+add_header X-Content-Type-Options "nosniff" always;
+add_header Referrer-Policy "strict-origin-when-cross-origin" always;
@@ -0,0 +1,45 @@
+#!/bin/bash
+# Ahead-of-time volume ownership migration for switching Frigate to non-root.
+# Run from the host BEFORE enabling PUID/PGID or --user:
+#
+#   ./fix-permissions.sh [--dry-run] <config_dir> <media_dir> [PUID] [PGID]
+#
+# Wraps the image's fix-ownership helper so there is exactly one
+# implementation of the chown logic. Requires an image that contains the
+# helper (any release that includes non-root support).
+
+set -o errexit -o nounset -o pipefail
+
+IMAGE="${FRIGATE_IMAGE:-ghcr.io/blakeblackshear/frigate:stable}"
+
+dry_run_flag=""
+if [[ "${1:-}" == "--dry-run" ]]; then
+    dry_run_flag="--dry-run"
+    shift
+fi
+
+if [[ $# -lt 2 ]]; then
+    echo "Usage: $0 [--dry-run] <config_dir> <media_dir> [PUID] [PGID]" >&2
+    exit 2
+fi
+
+config_dir="$1"
+media_dir="$2"
+puid="${3:-1000}"
+pgid="${4:-1000}"
+
+# The ids are interpolated into the container's bash -c source below, so
+# anything but digits would be reparsed as shell rather than passed through
+if ! [[ "$puid" =~ ^[0-9]+$ && "$pgid" =~ ^[0-9]+$ ]]; then
+    echo "[ERROR] PUID and PGID must be numeric, got '${puid}' and '${pgid}'" >&2
+    exit 2
+fi
+
+echo "[INFO] Using image ${IMAGE} (override with FRIGATE_IMAGE=...)"
+# shellcheck disable=SC2086
+docker run --rm \
+    -v "${config_dir}:/config" \
+    -v "${media_dir}:/media/frigate" \
+    --entrypoint bash \
+    "${IMAGE}" \
+    -c "command -v fix-ownership >/dev/null || { echo '[ERROR] this Frigate image predates non-root support; set FRIGATE_IMAGE to a release that includes it' >&2; exit 1; }; exec fix-ownership ${dry_run_flag} ${puid} ${pgid} /config /media/frigate"
@@ -11,10 +11,10 @@ except FileNotFoundError:
    pass

 try:
-    with open("/config/conv2rknn.yaml", "r") as config_file:
+    with open("/config/conv2rknn.yaml") as config_file:
        configuration = yaml.safe_load(config_file)
 except FileNotFoundError:
-    raise Exception("Please place a config file at /config/conv2rknn.yaml")
+    raise Exception("Please place a config file at /config/conv2rknn.yaml") from None

 if configuration["config"] != None:
    rknn_config = configuration["config"]
@@ -31,7 +31,7 @@ if "soc" not in configuration:
        with open("/proc/device-tree/compatible") as file:
            soc = file.read().split(",")[-1].strip("\x00")
    except FileNotFoundError:
-        raise Exception("Make sure to run docker in privileged mode.")
+        raise Exception("Make sure to run docker in privileged mode.") from None

    configuration["soc"] = [
        soc,
@@ -11,6 +11,8 @@ It is not recommended to copy this full configuration file. Only specify values

 :::

+Sections marked `# NOTE: Can be overridden at the camera level` can be set globally and then adjusted per camera. See [Global and Camera-Level Configuration](../config_overrides.md) for how that works.
+
 ```yaml
 mqtt:
  # Optional: Enable mqtt server (default: shown below)
@@ -54,17 +56,6 @@ mqtt:
  # 2 = exactly once
  qos: 0

-# Optional: Detectors configuration. Defaults to a single CPU detector
-detectors:
-  # Required: name of the detector
-  detector_name:
-    # Required: type of the detector
-    # Frigate provides many types, see https://docs.frigate.video/configuration/object_detectors for more details (default: shown below)
-    # Additional detector types can also be plugged in.
-    # Detectors may require additional configuration.
-    # Refer to the Detectors configuration page for more information.
-    type: cpu
-
 # Optional: Database configuration
 database:
  # The path to store the SQLite DB (default: shown below)
@@ -155,43 +146,56 @@ auth:
      - front_door
      - back_yard

-# Optional: model modifications
+# Optional: object detection models. Defaults to a single model on a CPU detector.
 # NOTE: The default values are for the EdgeTPU detector.
 # Other detectors will require the model config to be set.
-model:
-  # Required: path to the model. Frigate+ models use plus://<model_id> (default: automatic based on detector)
-  path: /edgetpu_model.tflite
-  # Required: path to the labelmap (default: shown below)
-  labelmap_path: /labelmap.txt
-  # Required: Object detection model input width (default: shown below)
-  width: 320
-  # Required: Object detection model input height (default: shown below)
-  height: 320
-  # Required: Object detection model input colorspace
-  # Valid values are rgb, bgr, or yuv. (default: shown below)
-  input_pixel_format: rgb
-  # Required: Object detection model input tensor format
-  # Valid values are nhwc or nchw (default: shown below)
-  input_tensor: nhwc
-  # Optional: Data type of the model input tensor
-  # Valid values are float, float_denorm, or int (default: shown below)
-  input_dtype: int
-  # Required: Object detection model type, currently only used with the OpenVINO detector
-  # Valid values are ssd, yolox, yolonas (default: shown below)
-  model_type: ssd
-  # Required: Label name modifications. These are merged into the standard labelmap.
-  labelmap:
-    2: vehicle
-  # Optional: Map of object labels to their attribute labels (default: depends on model)
-  attributes_map:
-    person:
-      - amazon
-      - face
-    car:
-      - amazon
-      - fedex
-      - license_plate
-      - ups
+models:
+    # Optional: the camera environment this model is for (default: shown below)
+    # Cameras select a model by setting detect -> scene to a matching value, and
+    # a model with a scene of all is used by any camera that does not set one.
+    # Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
+  - scene: all
+    # Required: hardware this model runs on, as <detector> or <detector>:<device>
+    # See https://docs.frigate.video/configuration/object_detectors for the
+    # detectors available and the devices each one accepts. All of a model's
+    # devices must use the same detector. Listing the same device more than once
+    # runs additional inference processes on it.
+    devices:
+      - edgetpu:pci:0
+    # Required: path to the model. Frigate+ models use plus://<model_id> (default: automatic based on detector)
+    path: /edgetpu_model.tflite
+    # Required: path to the labelmap (default: shown below)
+    labelmap_path: /labelmap.txt
+    # Required: Object detection model input width (default: shown below)
+    width: 320
+    # Required: Object detection model input height (default: shown below)
+    height: 320
+    # Required: Object detection model input colorspace
+    # Valid values are rgb, bgr, or yuv. (default: shown below)
+    input_pixel_format: rgb
+    # Required: Object detection model input tensor format
+    # Valid values are nhwc, nchw, hwnc, or hwcn (default: shown below)
+    input_tensor: nhwc
+    # Optional: Data type of the model input tensor
+    # Valid values are float, float_denorm, or int (default: shown below)
+    input_dtype: int
+    # Required: Object detection model architecture, used by detectors that support more
+    # than one model type (openvino, onnx, rknn, memryx, axengine, synaptics, and others)
+    # Valid values are ssd, yolox, yolonas, yolo-generic, rfdetr, dfine (default: shown below)
+    model_type: ssd
+    # Required: Label name modifications. These are merged into the standard labelmap.
+    labelmap:
+      2: vehicle
+    # Optional: Map of object labels to their attribute labels (default: depends on model)
+    attributes_map:
+      person:
+        - amazon
+        - face
+      car:
+        - amazon
+        - fedex
+        - license_plate
+        - ups

 # Optional: Audio Events Configuration
 # NOTE: Can be overridden at the camera level
@@ -214,6 +218,8 @@ audio:
    - fire_alarm
    - speech
    - yell
+  # Optional: Audio label name modifications. These are merged into the standard audio labelmap.
+  labelmap: {}
  # Optional: Filters to configure detection.
  filters:
    # Label that matches label in listen config.
@@ -248,11 +254,15 @@ birdseye:
  # Optional: Encoding quality of the mpeg1 feed (default: shown below)
  # 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
  quality: 8
-  # Optional: Mode of the view. Available options are: objects, motion, and continuous
-  #   objects - cameras are included if they have had a tracked object within the last 30 seconds
-  #   motion - cameras are included if motion was detected in the last 30 seconds
-  #   continuous - all cameras are included always
-  mode: objects
+  # Optional: Activity types that include cameras in Birdseye (default: shown below)
+  # Multiple activity types can be listed at the same time.
+  #   continuous:  all cameras are included always
+  #   motion:      included if motion was detected within the inactivity threshold
+  #   all_objects: included if a tracked object was present within the inactivity threshold
+  #   alerts:      included while an alert review item is in progress
+  #   detections:  included while a detection review item is in progress
+  modes:
+    - all_objects
  # Optional: Threshold for camera activity to stop showing camera (default: shown below)
  inactivity_threshold: 30
  # Optional: Configure the birdseye layout
@@ -284,6 +294,8 @@ ffmpeg:
    detect: -threads 2 -f rawvideo -pix_fmt yuv420p
    # Optional: output args for record streams (default: shown below)
    record: preset-record-generic
+    # Optional: output args for sub stream record streams (default: the record output args above)
+    # record_sub: preset-record-generic
  # Optional: Time in seconds to wait before ffmpeg retries connecting to the camera. (default: shown below)
  # If set too low, frigate will retry a connection to the camera's stream too frequently, using up the limited streams some cameras can allow at once
  # If set too high, then if a ffmpeg crash or camera stream timeout occurs, you could potentially lose up to a maximum of retry_interval second(s) of footage
@@ -303,6 +315,10 @@ detect:
  width: 1280
  # Optional: height of the frame for the input with the detect role (default: use native stream resolution)
  height: 720
+  # Optional: the environment this camera looks at, which picks the model it runs on
+  # (default: the model with a scene of all)
+  # Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
+  scene: outdoor
  # Optional: desired fps for your camera for the input with the detect role (default: shown below)
  # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
  fps: 5
@@ -339,7 +355,7 @@ detect:
  # especially when using separate streams for detect and record.
  # Use this setting to make the timeline bounding boxes more closely align
  # with the recording. The value can be positive or negative.
-  # TIP: Imagine there is an tracked object clip with a person walking from left to right.
+  # TIP: Imagine there is a tracked object clip with a person walking from left to right.
  #      If the tracked object lifecycle bounding box is consistently to the left of the person
  #      then the value should be decreased. Similarly, if a person is walking from
  #      left to right and the bounding box is consistently ahead of the person
@@ -468,8 +484,8 @@ review:
    detections: False
    # Optional: Activity Context Prompt to give context to the GenAI what activity is and is not suspicious.
    # It is important to be direct and detailed. See documentation for the default prompt structure.
-    activity_context_prompt: """Define what is and is not suspicious
-"""
+    activity_context_prompt: |
+      Define what is and is not suspicious
    # Optional: Image source for GenAI (default: preview)
    # Options: "preview" (uses cached preview frames at ~180p) or "recordings" (extracts frames from recordings at 480p)
    # Using "recordings" provides better image quality but uses more tokens per image.
@@ -634,6 +650,42 @@ record:
      #       For example, if the camera retain mode is "motion", the segments without motion are
      #       never stored, so setting the mode to "all" here won't bring them back.
      mode: motion
+  # Optional: Sub stream recording settings
+  # Records a second, lower quality stream for quality selection during playback
+  # and extended low quality retention. Requires the record_sub role to be assigned
+  # to one of the camera's inputs.
+  sub:
+    # Optional: Enable sub stream recording (default: shown below)
+    # NOTE: Recording must also be enabled for sub stream recording to run.
+    enabled: False
+    # Optional: Continuous retention settings for sub stream recordings
+    continuous:
+      # Optional: Number of days to retain sub stream recordings regardless of tracked objects or motion (default: shown below)
+      days: 0
+    # Optional: Motion retention settings for sub stream recordings
+    motion:
+      # Optional: Number of days to retain sub stream recordings triggered by motion (default: shown below)
+      days: 0
+    # Optional: Retention settings for sub stream recordings of alerts
+    # NOTE: Pre and post capture windows are taken from the main alerts config above.
+    alerts:
+      # Required: Retention days (default: shown below)
+      days: 10
+      # Optional: Mode for retention. (default: shown below)
+      #   all - save all sub stream recording segments for alerts regardless of activity
+      #   motion - save all sub stream recording segments for alerts with any detected motion
+      #   active_objects - save all sub stream recording segments for alerts with active/moving objects
+      mode: motion
+    # Optional: Retention settings for sub stream recordings of detections
+    # NOTE: Pre and post capture windows are taken from the main detections config above.
+    detections:
+      # Required: Retention days (default: shown below)
+      days: 10
+      # Optional: Mode for retention. (default: shown below)
+      #   all - save all sub stream recording segments for detections regardless of activity
+      #   motion - save all sub stream recording segments for detections with any detected motion
+      #   active_objects - save all sub stream recording segments for detections with active/moving objects
+      mode: motion

 # Optional: Configuration for the snapshots written to the clips directory for each tracked object
 # Timestamp, bounding_box, crop and height settings are applied by default to API requests for snapshots.
@@ -813,14 +865,15 @@ classification:
        cameras:
          camera_name:
            # Required: Crop of image frame on this camera to run classification on
-            crop: [0, 180, 220, 400]
+            # [x1, y1, x2, y2] as decimals between 0 and 1, relative to the detect resolution
+            crop: [0.0, 0.25, 0.3, 0.85]
        # Optional: If classification should be run when motion is detected in the crop (default: shown below)
        motion: False
        # Optional: Interval to run classification on in seconds (default: shown below)
        interval: None

 # Optional: Restream configuration
-# Uses https://github.com/AlexxIT/go2rtc (v1.9.13)
+# Uses https://github.com/AlexxIT/go2rtc (v1.9.14)
 # NOTE: The default go2rtc API port (1984) must be used,
 #       changing this port for the integrated go2rtc instance is not supported.
 go2rtc:
@@ -884,7 +937,7 @@ cameras:
        # Required: the path to the stream
        # NOTE: path may include environment variables or docker secrets, which must begin with 'FRIGATE_' and be referenced in {}
        - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
-          # Required: list of roles for this stream. valid values are: audio,detect,record
+          # Required: list of roles for this stream. valid values are: audio,detect,record,record_sub
          # NOTICE: In addition to assigning the audio, detect, and record roles
          # they must also be enabled in the camera config.
          roles:
@@ -977,7 +1030,9 @@ cameras:
      # Optional: Adjust sort order of cameras in the UI. Larger numbers come later (default: shown below)
      # By default the cameras are sorted alphabetically.
      order: 0
-      # Optional: Whether or not to show the camera in the Frigate UI (default: shown below)
+      # Optional: Whether or not to show the camera on the default All Cameras live dashboard.
+      # The camera is still available everywhere else, including camera groups and settings
+      # (default: shown below)
      dashboard: True
      # Optional: Whether this camera is visible in review (the review page and its camera
      # filter, motion review, and the history view) (default: shown below)
@@ -63,34 +63,28 @@ go2rtc:

 ### `environment_vars`

-This section can be used to set environment variables for those unable to modify the environment of the container, like within Home Assistant OS. Docker users should set environment variables in their `docker run` command (`-e FRIGATE_MQTT_PASSWORD=secret`) or `docker-compose.yml` file (`environment:` section) instead. Note that values set here are stored in plain text in your config file, so if the goal is to keep credentials out of your configuration, use Docker environment variables or Docker secrets instead.
+This section sets environment variables in the Frigate process for those unable to modify the environment of the container, like within Home Assistant OS. It's meant for process settings such as `LIBVA_DRIVER_NAME` or the TensorFlow thread counts below. Docker users should set environment variables in their `docker run` command (`-e LIBVA_DRIVER_NAME=i965`) or `docker-compose.yml` file (`environment:` section) instead. Values set here are stored in plain text in your config file, so credentials belong in `secrets.yaml`, Docker environment variables, or Docker secrets instead.

-Variables prefixed with `FRIGATE_` can be referenced in config fields that support environment variable substitution (such as MQTT host and credentials, camera stream URLs, and ONVIF host and credentials) using the `{FRIGATE_VARIABLE_NAME}` syntax.
+Names prefixed with `FRIGATE_` set here also take part in `{FRIGATE_VARIABLE_NAME}` substitution (see [below](#substitution-sources-and-precedence)), but `secrets.yaml` is the better home for them.

 <ConfigTabs>
 <TabItem value="ui">

 Navigate to <NavPath path="Settings > System > Environment variables" /> to add or edit environment variables.

-| Field     | Description                                               |
-| --------- | --------------------------------------------------------- |
-| **Key**   | The environment variable name (e.g., `FRIGATE_MQTT_USER`) |
-| **Value** | The value for the variable                                |
+| Field             | Description                                               |
+| ----------------- | --------------------------------------------------------- |
+| **Variable name** | The environment variable name (e.g., `LIBVA_DRIVER_NAME`) |
+| **Value**         | The value for the variable                                |

-Variables defined here can be referenced elsewhere in your configuration using the `{FRIGATE_VARIABLE_NAME}` syntax.
+Names prefixed with `FRIGATE_` can also be referenced elsewhere in your configuration using the `{FRIGATE_VARIABLE_NAME}` syntax.

 </TabItem>
 <TabItem value="yaml">

 ```yaml
 environment_vars:
-  FRIGATE_MQTT_USER: my_mqtt_user
-  FRIGATE_MQTT_PASSWORD: my_mqtt_password
-
-mqtt:
-  host: "{FRIGATE_MQTT_HOST}"
-  user: "{FRIGATE_MQTT_USER}"
-  password: "{FRIGATE_MQTT_PASSWORD}"
+  LIBVA_DRIVER_NAME: i965
 ```

 </TabItem>
@@ -124,6 +118,51 @@ environment_vars:
 </TabItem>
 </ConfigTabs>

+### `secrets.yaml`
+
+A `secrets.yaml` file next to your `config.yml` is an additional source of `FRIGATE_` variables, for installs that can't set container environment variables or mount Docker secrets. It's a flat map of names to values, and it is never read or written by the Frigate UI:
+
+```yaml
+FRIGATE_CAM_USER: viewer
+FRIGATE_CAM_PASS: "p@ss w0rd"
+FRIGATE_MQTT_HOST: mqtt.internal.example
+```
+
+For Docker this is `/config/secrets.yaml` inside the container, so it lives in whatever host directory you mounted at `/config`. For the Home Assistant App it's `/addon_configs/<addon_directory>/secrets.yaml`, in the same folder as your `config.yml`; see [the App config directory](../config.md#accessing-app-config-dir) for the directory name for your variant.
+
+Names must start with `FRIGATE_`, and nesting is not supported. `secrets.yaml` feeds `{FRIGATE_VARIABLE_NAME}` substitution, so the handful of variables Frigate reads straight from the process environment, such as `FRIGATE_JWT_SECRET`, still need a container environment variable or a Docker secret.
+
+### Substitution sources and precedence
+
+The same `{FRIGATE_VARIABLE_NAME}` placeholder resolves from four sources. When a name is defined in more than one, the higher one wins and a warning at startup names which source was used.
+
+| Priority    | Source                | Where it's set                                                             | Who can use it                 |
+| ----------- | --------------------- | -------------------------------------------------------------------------- | ------------------------------ |
+| 1 (highest) | Docker secrets        | Files in `/run/secrets`, or the directory named by `CREDENTIALS_DIRECTORY` | Docker, systemd                |
+| 2           | Container environment | `docker run -e`, the `environment:` section of `docker-compose.yml`        | Docker                         |
+| 3           | `secrets.yaml`        | Next to `config.yml`, see above                                            | Everyone, including the HA App |
+| 4 (lowest)  | `environment_vars`    | The block in `config.yml` described above                                  | Everyone, including the HA App |
+
+For example, with this `secrets.yaml`:
+
+```yaml
+FRIGATE_MQTT_PASSWORD: from_secrets
+```
+
+and this `config.yml`:
+
+```yaml
+environment_vars:
+  FRIGATE_MQTT_PASSWORD: from_config
+
+mqtt:
+  password: "{FRIGATE_MQTT_PASSWORD}"
+```
+
+the password resolves to `from_secrets`, and the log shows `FRIGATE_MQTT_PASSWORD is defined in more than one place, using the value from secrets.yaml`. Add `-e FRIGATE_MQTT_PASSWORD=from_env` to the container and it resolves to `from_env` instead.
+
+Referencing a name that no source defines is a config validation error naming the field.
+
 ### `database`

 Tracked object and recording information is managed in a sqlite database at `/config/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant.
@@ -171,7 +210,7 @@ Custom models may also require different input tensor formats. The colorspace co
 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > System > Detectors and model" /> and open the **Custom Model** tab to configure the model path, dimensions, and input format.
+Navigate to <NavPath path="Settings > System > Detection models" /> and, on the model you want to change, open the **Custom Model** tab to configure the model path, dimensions, and input format.

 | Field                                         | Description                          |
 | --------------------------------------------- | ------------------------------------ |
@@ -186,12 +225,14 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and open

 ```yaml
 # Optional: model config
-model:
-  path: /path/to/model
-  width: 320
-  height: 320
-  input_tensor: "nhwc"
-  input_pixel_format: "bgr"
+models:
+  - devices:
+      - openvino:GPU
+    path: /path/to/model
+    width: 320
+    height: 320
+    input_tensor: "nhwc"
+    input_pixel_format: "bgr"
 ```

 </TabItem>
@@ -208,15 +249,15 @@ If the labelmap is customized then the labels used for alerts will need to be ad
 The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model.

 ```yaml
-model:
-  labelmap:
-    2: vehicle
-    3: vehicle
-    5: vehicle
-    7: vehicle
-    15: animal
-    16: animal
-    17: animal
+models:
+  - labelmap:
+      2: vehicle
+      3: vehicle
+      5: vehicle
+      7: vehicle
+      15: animal
+      16: animal
+      17: animal
 ```

 Note that if you rename objects in the labelmap, you will also need to update your `objects -> track` list as well.
@@ -237,7 +278,7 @@ Frigate exposes a few networking options. IPv6 and the listen ports are set in t

 ### Enabling IPv6

-By default Frigate listens on IPv4 only. To also listen on IPv6 — on port `5000`, and on `8971` when TLS is configured — enable it in the `networking` configuration.
+By default Frigate listens on IPv4 only. To also listen on IPv6 (on port `5000`, and on `8971` when TLS is configured), enable it in the `networking` configuration.

 <ConfigTabs>
 <TabItem value="ui">
@@ -287,6 +328,10 @@ networking:

 This setting is for advanced users. For the majority of use cases it's recommended to change the `ports` section of your Docker compose file or use the Docker `run` `--publish` option instead, e.g. `-p 443:8971`. Changing Frigate's ports may break some integrations.

+The internal and external ports must be different port numbers, and Frigate will refuse to start otherwise. Requests arriving on the internal port are treated as authenticated admins, so pointing both at the same port would remove authentication from the external one.
+
+Nginx binds these ports when it starts, so port changes only take effect after Frigate restarts.
+
 :::

 ### Customizing the Nginx configuration
@@ -329,7 +374,7 @@ For example:
 ```
 services:
  frigate:
-    image: blakeblackshear/frigate:latest
+    image: ghcr.io/blakeblackshear/frigate:stable
    environment:
      - FRIGATE_BASE_PATH=/frigate
 ```
@@ -354,7 +399,7 @@ To do this:

 ### Custom go2rtc version

-Frigate currently includes go2rtc v1.9.13, there may be certain cases where you want to run a different version of go2rtc.
+Frigate currently includes go2rtc v1.9.14, there may be certain cases where you want to run a different version of go2rtc.

 To do this:

@@ -78,7 +78,7 @@ cameras:

 ### Configuring Minimum Volume

-The audio detector uses volume levels in the same way that motion in a camera feed is used for object detection. This means that Frigate will not run audio detection unless the audio volume is above the configured level in order to reduce resource usage. Audio levels can vary widely between camera models so it is important to run tests to see what volume levels are. The Debug view in the Frigate UI has an Audio tab for cameras that have the `audio` role assigned where a graph and the current levels are is displayed. The `min_volume` parameter should be set to the minimum the `RMS` level required to run audio detection.
+The audio detector uses volume levels in the same way that motion in a camera feed is used for object detection. This means that Frigate will not run audio detection unless the audio volume is above the configured level in order to reduce resource usage. Audio levels can vary widely between camera models so it is important to run tests to see what volume levels are. The [Debug view](/usage/live#the-single-camera-view) in the Frigate UI has an Audio tab for cameras that have the `audio` role assigned where a graph and the current levels are displayed. The `min_volume` parameter should be set to the minimum the `RMS` level required to run audio detection.

 :::tip

@@ -114,6 +114,30 @@ audio:
 </TabItem>
 </ConfigTabs>

+#### Grouping Audio Labels
+
+Related audio classes can be grouped under one label by mapping their numeric
+class IDs to the same name. Add the grouped name to `listen` and use it for any
+corresponding filter:
+
+```yaml
+audio:
+  listen:
+    - dogs
+  labelmap:
+    69: dogs # dog
+    70: dogs # bark
+    75: dogs # whimper_dog
+  filters:
+    dogs:
+      threshold: 0.8
+```
+
+Class IDs are zero-based indices in
+[`audio-labelmap.txt`](https://github.com/blakeblackshear/frigate/blob/dev/audio-labelmap.txt),
+so each ID is one less than the displayed file line number.
+Audio label mappings are separate from the object detector's `model.labelmap`.
+
 ### Common Audio Labels

 The labelmap includes hundreds of sound types. The labels below are the ones most users may find practical, grouped by what they're typically used for. Use the exact label string from the left column in your `listen` config, or search for the label in the Frigate UI directly.
@@ -174,13 +198,13 @@ Some labels cover several related sounds: `yell` is triggered by shouting, yelli

 :::tip

-Frequently-heard labels like `speech` can generate a lot of events, and each event could save a snapshot and recording based on your configuration, so start with a focused set — the defaults (`bark`, `fire_alarm`, `speech`, `yell`) plus a few of the safety labels above cover most needs — and expand from there. See the [full audio labelmap](https://github.com/blakeblackshear/frigate/blob/dev/audio-labelmap.txt) or the Frigate UI for every available type.
+Frequently-heard labels like `speech` can generate a lot of events, and each event could save a snapshot and recording based on your configuration, so start with a focused set and expand from there. The defaults (`bark`, `fire_alarm`, `speech`, `yell`) plus a few of the safety labels above cover most needs. See the [full audio labelmap](https://github.com/blakeblackshear/frigate/blob/dev/audio-labelmap.txt) or the Frigate UI for every available type.

 :::

 ### Audio Transcription

-Frigate supports fully local audio transcription using either `sherpa-onnx` or OpenAI's open-source Whisper models via `faster-whisper`. The goal of this feature is to support Semantic Search for `speech` audio events. Frigate is not intended to act as a continuous, fully-automatic speech transcription service — automatically transcribing all speech (or queuing many audio events for transcription) requires substantial CPU (or GPU) resources and is impractical on most systems. For this reason, transcriptions for events are initiated manually from the UI or the API rather than being run continuously in the background.
+Frigate supports fully local audio transcription using either `sherpa-onnx` or OpenAI's open-source Whisper models via `faster-whisper`. The goal of this feature is to support Semantic Search for `speech` audio events. Frigate is not intended to act as a continuous, fully-automatic speech transcription service. Automatically transcribing all speech (or queuing many audio events for transcription) requires substantial CPU (or GPU) resources and is impractical on most systems. For this reason, transcriptions for events are initiated manually from the UI or the API rather than being run continuously in the background.

 :::info

@@ -256,7 +280,7 @@ The only field that is valid at the camera level is `enabled`.

 #### Live transcription

-The single camera Live view in the Frigate UI supports live transcription of audio for streams defined with the `audio` role. Use the Enable/Disable Live Audio Transcription button/switch to toggle transcription processing. When speech is heard, the UI will display a black box over the top of the camera stream with text. The MQTT topic `frigate/<camera_name>/audio/transcription` will also be updated in real-time with transcribed text.
+The single camera Live view in the Frigate UI supports live transcription of audio for streams defined with the `audio` role. Use the Enable/Disable Live Audio Transcription button/switch to toggle transcription processing, or toggle it outside of the UI with the [`frigate/<camera_name>/audio_transcription/set`](/integrations/mqtt#frigatecamera_nameaudio_transcriptionset) MQTT topic or the HTTP API. When speech is heard, the UI will display a black box over the top of the camera stream with text. The MQTT topic `frigate/<camera_name>/audio/transcription` will also be updated in real-time with transcribed text.

 Results can be error-prone due to a number of factors, including:

@@ -272,7 +296,7 @@ If you have CUDA hardware, you can experiment with the `large` `whisper` model o

 #### Transcription and translation of `speech` audio events

-Any `speech` events in Explore can be transcribed and/or translated through the Transcribe button in the Tracked Object Details pane.
+Any `speech` events in Explore can be transcribed and/or translated through the Transcribe button (the microphone icon) in the Tracked Object Details pane.

 In order to use transcription and translation for past events, you must enable audio detection and define `speech` as an audio type to listen for. To have `speech` events translated into the language of your choice, set the `language` config parameter with the correct [language code](https://github.com/openai/whisper/blob/main/whisper/tokenizer.py#L10).

@@ -294,7 +318,7 @@ Recorded `speech` events will always use a `whisper` model, regardless of the `m

   Because transcription is **serialized (one event at a time)** and speech events can be generated far faster than they can be processed, an auto-transcribe toggle would very quickly create an ever-growing backlog and degrade core functionality. For the amount of engineering and risk involved, it adds **very little practical value** for the majority of deployments, which are often on low-powered, edge hardware.

-   If you hear speech that's actually important and worth saving/indexing for the future, **just press the transcribe button in Explore** on that specific `speech` event - that keeps things explicit, reliable, and under your control.
+   If you hear speech that's actually important and worth saving/indexing for the future, **just press the transcribe button (the microphone icon) in Explore** on that specific `speech` event - that keeps things explicit, reliable, and under your control.

   Other options are being considered for future versions of Frigate to add transcription options that support external `whisper` Docker containers. A single transcription service could then be shared by Frigate and other applications (for example, Home Assistant Voice), and run on more powerful machines when available.

@@ -91,7 +91,7 @@ auth:

 ## Session Length

-The default session length for user authentication in Frigate is 24 hours. This setting determines how long a user's authenticated session remains active before a token refresh is required — otherwise, the user will need to log in again.
+The default session length for user authentication in Frigate is 24 hours. This setting determines how long a user's authenticated session remains active before a token refresh is required. Otherwise, the user will need to log in again.

 While the default provides a balance of security and convenience, you can customize this duration to suit your specific security requirements and user experience preferences. The session length is configured in seconds.

@@ -141,7 +141,7 @@ Changing the secret will invalidate current tokens.

 ## Proxy configuration

-Frigate can be configured to leverage features of common upstream authentication proxies such as Authelia, Authentik, oauth2_proxy, or traefik-forward-auth.
+Frigate can be configured to leverage features of common upstream authentication proxies such as Authelia, Authentik, oauth2_proxy, or traefik-forward-auth. Frigate does not implement OIDC, SAML, or LDAP natively; as an NVR focused on recording and object detection, it relies on robust, battle-tested proxies to handle those protocols and passes the authenticated user and role through via headers (see below).

 If you are leveraging the authentication of an upstream proxy, you likely want to disable Frigate's authentication as there is no correspondence between users in Frigate's database and users authenticated via the proxy. Optionally, if communication between the reverse proxy and Frigate is over an untrusted network, you should set an `auth_secret` in the `proxy` config and configure the proxy to send the secret value as a header named `X-Proxy-Secret`. Assuming this is an untrusted network, you will also want to [configure a real TLS certificate](tls.md) to ensure the traffic can't simply be sniffed to steal the secret.

@@ -262,6 +262,19 @@ In this example:

 - Admin precedence: if the `admin` mapping matches, Frigate resolves the session to `admin` to avoid accidental downgrade when a user belongs to multiple groups (for example both `admin` and `viewer` groups).

+:::note
+
+If a user isn't getting the role you expect, enable debug logging to see exactly what headers Frigate is receiving from your proxy:
+
+```yaml
+logger:
+  default: info
+  logs:
+    frigate.api.auth: debug
+```
+
+:::
+
 #### Port Considerations

 **Authenticated Port (8971)**
@@ -6,6 +6,7 @@ title: Camera Autotracking
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 An ONVIF-capable, PTZ (pan-tilt-zoom) camera that supports relative movement within the field of view (FOV) can be configured to automatically track moving objects and keep them in the center of the frame.

@@ -161,7 +162,7 @@ Every PTZ camera is different, so autotracking may not perform ideally in every

 The object tracker in Frigate estimates the motion of the PTZ so that tracked objects are preserved when the camera moves. In most cases 5 fps is sufficient, but if you plan to track faster moving objects, you may want to increase this slightly. Higher frame rates (> 10fps) will only slow down Frigate and the motion estimator and may lead to dropped frames, especially if you are using experimental zooming.

-A fast [detector](object_detectors.md) is recommended. CPU detectors will not perform well or won't work at all. You can watch Frigate's debug viewer for your camera to see a thicker colored box around the object currently being autotracked.
+A fast [detector](object_detectors.md) is recommended. CPU detectors will not perform well or won't work at all. You can watch Frigate's [debug viewer](/usage/live#the-single-camera-view) for your camera to see a thicker colored box around the object currently being autotracked.

 ![Autotracking Debug View](/img/autotracking-debug.gif)

@@ -187,30 +188,96 @@ In security and surveillance, it's common to use "spotter" cameras in combinatio

 ## Troubleshooting and FAQ

-### The autotracker loses track of my object. Why?
+### Camera Compatibility
+
+<FaqItem id="which-ptz-camera-should-i-use-for-autotracking" question="Which PTZ camera should I use for autotracking?">
+
+See the community-maintained list of [ONVIF PTZ camera recommendations](cameras.md#onvif-ptz-camera-recommendations) for cameras and brands reported to work (and not work) with autotracking. This is not an exhaustive list that is frequently updated, so other cameras not listed may also work well. Frigate's autotracking was developed with a Dahua SD1A404XB-GNR (now sold as the EmpireTech PTZ1A4M-4X-S2), and Dahua / EmpireTech PTZs are the most consistently reported as working well.
+
+When comparing models:
+
+- Verify ONVIF support first. See [Checking ONVIF camera support](#checking-onvif-camera-support) above.
+- Favor a camera with a fast PTZ motor. Cameras with slow motors may fail [calibration](#calibration) and will struggle to keep up with objects that move across the field of view quickly.
+
+</FaqItem>
+
+<FaqItem id="does-autotracking-work-with-reolink-ptz-cameras" question="Does autotracking work with Reolink PTZ cameras?">
+
+No. Reolink cameras (including the TrackMix series) lack the ONVIF FOV RelativeMove firmware support that Frigate's autotracker requires, so autotracking will not work with any current Reolink PTZ. Their video streams and basic PTZ controls still work in Frigate. If you want object tracking on a Reolink PTZ, you will need to use the tracking feature built into the camera's firmware, which is proprietary and operates independently of Frigate.
+
+</FaqItem>
+
+<FaqItem id="im-seeing-an-error-in-the-logs-that-my-camera-is-still-in-onvif-moving-status-what-does-this-mean" question={"I'm seeing an error in the logs that my camera \"is still in ONVIF 'MOVING' status.\" What does this mean?"}>
+
+There are two possible known reasons for this (and perhaps others yet unknown): a slow PTZ motor or buggy camera firmware. Frigate uses an ONVIF parameter provided by the camera, `MoveStatus`, to determine when the PTZ's motor is moving or idle. According to some users, Hikvision PTZs (even with the latest firmware), are not updating this value after PTZ movement. Unfortunately there is no workaround to this bug in Hikvision firmware, so autotracking will not function correctly and should be disabled in your config. This may also be the case with other non-Hikvision cameras utilizing Hikvision firmware, such as some Annke models. In rare cases the vendor may provide fixed firmware on request; for example, Annke has supplied firmware that resolves this for the CZ504 (see the [camera recommendations list](cameras.md#onvif-ptz-camera-recommendations)).
+
+</FaqItem>
+
+<FaqItem id="calibration-seems-to-have-completed-but-the-camera-is-not-actually-moving-to-track-my-object-why" question="Calibration seems to have completed, but the camera is not actually moving to track my object. Why?">
+
+Some cameras have firmware that reports that FOV RelativeMove, the ONVIF command that Frigate uses for autotracking, is supported. However, if the camera does not pan or tilt when an object comes into the required zone, your camera's firmware does not actually support FOV RelativeMove. One such camera is the Uniview IPC672LR-AX4DUPK. It actually moves its zoom motor instead of panning and tilting and does not follow the ONVIF standard whatsoever.
+
+</FaqItem>
+
+### Calibration Issues
+
+<FaqItem id="i-tried-calibrating-my-camera-but-the-logs-show-that-it-is-stuck-at-0-and-frigate-is-not-starting-up" question="I tried calibrating my camera, but the logs show that it is stuck at 0% and Frigate is not starting up.">
+
+This is often caused by the same reason as the "MOVING" status error above - the `MoveStatus` ONVIF parameter is not changing due to a bug in your camera's firmware. Also, see the note above: Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal. But if you don't see log entries every few seconds for calibration progress, your camera is not compatible with autotracking.
+
+</FaqItem>
+
+<FaqItem id="frigate-reports-an-error-saying-that-calibration-has-failed-why" question="Frigate reports an error saying that calibration has failed. Why?">
+
+Calibration measures the amount of time it takes for Frigate to make a series of movements with your PTZ. This error message is recorded in the log if these values are too high for Frigate to support calibrated autotracking. This is often the case when your camera's motor or network connection is too slow or your camera's firmware doesn't report the motor status in a timely manner.
+
+Some things to try:
+
+- If your camera's firmware has a PTZ or motor speed setting, set it to the fastest available speed and calibrate again.
+- Run without calibration: remove the `movement_weights` line from your config, set `calibrate_on_startup` to `False`, and restart.
+
+If calibration consistently fails, this often means your camera's motor is too slow and autotracking will behave unpredictably or won't be able to keep up with moving objects.
+
+</FaqItem>
+
+<FaqItem id="autotracking-is-erratic-or-moves-the-camera-in-the-wrong-direction" question="Autotracking is erratic, moves the camera in the wrong direction, or zooms past my object. Why?">
+
+Frigate uses the `movement_weights` measured during calibration to predict how far the camera needs to move to keep an object centered, so inaccurate values produce movements that don't seem to make sense: overshooting, moving the opposite direction, or zooming in on an object's last known position and losing it entirely. This is almost always a calibration issue.
+
+- Remove the `movement_weights` entry from your config and restart Frigate to run without calibration. If tracking improves, try recalibrating.
+- Recalibrate several times. The `movement_weights` values should be close to each other after each run. If they vary significantly between runs, your camera may not be reporting its motor status reliably, and you may get better results without calibration.
+- If you are using zooming, a high `zoom_factor` can cause the camera to zoom in too far and lose the object. Try a lower value.
+
+Remember to recalibrate whenever you change your `return_preset`, change your camera's detect `fps`, or enable zooming after calibrating with it disabled.
+
+</FaqItem>
+
+### Tracking Behavior
+
+<FaqItem id="the-autotracker-loses-track-of-my-object-why" question="The autotracker loses track of my object. Why?">

 There are many reasons this could be the case. If you are using experimental zooming, your `zoom_factor` value might be too high, the object might be traveling too quickly, the scene might be too dark, there are not enough details in the scene (for example, a PTZ looking down on a driveway or other monotone background without a sufficient number of hard edges or corners), or the scene is otherwise less than optimal for Frigate to maintain tracking.

 Your camera's shutter speed may also be set too low so that blurring occurs with motion. Check your camera's firmware to see if you can increase the shutter speed.

-Watching Frigate's debug view can help to determine a possible cause. The autotracked object will have a thicker colored box around it.
+Watching Frigate's debug view can help to determine a possible cause. The autotracked object will have a thicker colored box around it. If the camera consistently zooms in on the object and then loses it, see [Autotracking is erratic, moves the camera in the wrong direction, or zooms past my object. Why?](#autotracking-is-erratic-or-moves-the-camera-in-the-wrong-direction) above.

-### I'm seeing an error in the logs that my camera "is still in ONVIF 'MOVING' status." What does this mean?
+</FaqItem>

-There are two possible known reasons for this (and perhaps others yet unknown): a slow PTZ motor or buggy camera firmware. Frigate uses an ONVIF parameter provided by the camera, `MoveStatus`, to determine when the PTZ's motor is moving or idle. According to some users, Hikvision PTZs (even with the latest firmware), are not updating this value after PTZ movement. Unfortunately there is no workaround to this bug in Hikvision firmware, so autotracking will not function correctly and should be disabled in your config. This may also be the case with other non-Hikvision cameras utilizing Hikvision firmware.
-
-### I tried calibrating my camera, but the logs show that it is stuck at 0% and Frigate is not starting up.
-
-This is often caused by the same reason as above - the `MoveStatus` ONVIF parameter is not changing due to a bug in your camera's firmware. Also, see the note above: Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal. But if you don't see log entries every few seconds for calibration progress, your camera is not compatible with autotracking.
-
-### I'm seeing this error in the logs: "Autotracker: motion estimator couldn't get transformations". What does this mean?
+<FaqItem id="im-seeing-this-error-in-the-logs-autotracker-motion-estimator-couldnt-get-transformations-what-does-this-mean" question={"I'm seeing this error in the logs: \"Autotracker: motion estimator couldn't get transformations\". What does this mean?"}>

 To maintain object tracking during PTZ moves, Frigate tracks the motion of your camera based on the details of the frame. If you are seeing this message, it could mean that your `zoom_factor` may be set too high, the scene around your detected object does not have enough details (like hard edges or color variations), or your camera's shutter speed is too slow and motion blur is occurring. Try reducing `zoom_factor`, finding a way to alter the scene around your object, or changing your camera's shutter speed.

-### Calibration seems to have completed, but the camera is not actually moving to track my object. Why?
+</FaqItem>

-Some cameras have firmware that reports that FOV RelativeMove, the ONVIF command that Frigate uses for autotracking, is supported. However, if the camera does not pan or tilt when an object comes into the required zone, your camera's firmware does not actually support FOV RelativeMove. One such camera is the Uniview IPC672LR-AX4DUPK. It actually moves its zoom motor instead of panning and tilting and does not follow the ONVIF standard whatsoever.
+<FaqItem id="why-does-object-detection-pause-briefly-when-the-camera-moves" question="Why does object detection pause briefly when the camera moves?">

-### Frigate reports an error saying that calibration has failed. Why?
+When the PTZ moves, the entire frame changes at once. Frigate's motion detection treats sudden scene-wide changes (like a lightning flash, an infrared mode switch, or a camera move) specially and pauses detection momentarily until the scene stabilizes. This is expected and normal, and detection resumes shortly after the camera stops moving. If detection does not resume once the camera is stationary, use the [debug view](/usage/live#the-single-camera-view) to see what is happening.

-Calibration measures the amount of time it takes for Frigate to make a series of movements with your PTZ. This error message is recorded in the log if these values are too high for Frigate to support calibrated autotracking. This is often the case when your camera's motor or network connection is too slow or your camera's firmware doesn't report the motor status in a timely manner. You can try running without calibration (just remove the `movement_weights` line from your config and restart), but if calibration fails, this often means that autotracking will behave unpredictably.
+</FaqItem>
+
+<FaqItem id="can-i-turn-autotracking-on-and-off-automatically" question="Can I turn autotracking on and off automatically?">
+
+Yes. Autotracking can be toggled per camera at runtime over MQTT with the [`frigate/<camera_name>/ptz_autotracker/set`](../integrations/mqtt.md#frigatecamera_nameptz_autotrackerset) topic, and the [Home Assistant integration](../integrations/home-assistant.md) exposes a switch for it. This pairs well with the "spotter" camera automations described in [Usage applications](#usage-applications) above, for example only enabling autotracking at night or when nobody is home.
+
+</FaqItem>
@@ -18,13 +18,17 @@ Each camera tile in Birdseye is composed from the frames of the stream assigned

 ## Birdseye Behavior

-### Birdseye Modes
+### Birdseye Activity Types

-Birdseye offers different modes to customize which cameras show under which circumstances.
+Birdseye offers independent activity types that control when cameras are shown. Multiple activity types can be listed together.

- **continuous:** All cameras are always included
- **motion:** Cameras that have detected motion within the last 30 seconds are included
- **objects:** Cameras that have tracked an active object within the last 30 seconds are included
+- **continuous:** The camera is always included
+- **motion:** The camera is included when motion was detected within the last 30 seconds
+- **all_objects:** The camera is included when a tracked object is present, active or stationary
+- **alerts:** The camera is included while an alert review item is in progress
+- **detections:** The camera is included while a detection review item is in progress
+
+`alerts` and `detections` follow the review item's own lifetime, so the camera is removed as soon as the review item ends. Which objects qualify for each is set in [review configuration](./review.md).

 ### Custom Birdseye Icon

@@ -39,27 +43,29 @@ To include a camera in Birdseye view only for specific circumstances, or exclude

 **Global settings:** Navigate to <NavPath path="Settings > System > Birdseye" /> to configure the default Birdseye behavior for all cameras.

-**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the mode or disable Birdseye for a specific camera.
+**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the activity types or disable Birdseye for a specific camera.

-| Field               | Description                                                   |
-| ------------------- | ------------------------------------------------------------- |
-| **Enable Birdseye** | Whether this camera appears in Birdseye view                  |
-| **Tracking mode**   | When to show the camera: `continuous`, `motion`, or `objects` |
+| Field                  | Description                                                |
+| ---------------------- | ---------------------------------------------------------- |
+| **Enable Birdseye**    | Whether this camera appears in Birdseye view               |
+| **Activity types**     | Conditions that determine when to show the camera          |

 </TabItem>
 <TabItem value="yaml">

-```yaml {8-10,12-14}
+```yaml {10-12,15-16}
 # Include all cameras by default in Birdseye view
 birdseye:
  enabled: True
-  mode: continuous
+  modes:
+    - continuous

 cameras:
  front:
-    # Only include the "front" camera in Birdseye view when objects are detected
+    # Only include the "front" camera in Birdseye view when an alert is in progress
    birdseye:
-      mode: objects
+      modes:
+        - alerts
  back:
    # Exclude the "back" camera from Birdseye view
    birdseye:
@@ -71,7 +77,7 @@ cameras:

 ### Birdseye Inactivity

-By default birdseye shows all cameras that have had the configured activity in the last 30 seconds. This threshold can be configured.
+By default birdseye shows all cameras that have had the configured activity in the last 30 seconds. This threshold can be configured, and applies to the `motion` and `all_objects` activity types only.

 <ConfigTabs>
 <TabItem value="ui">
@@ -126,12 +132,12 @@ birdseye:

 ### Sorting cameras in the Birdseye view

-It is possible to override the order of cameras that are being shown in the Birdseye view. The order is set at the camera level.
+It is possible to override the order of cameras that are being shown in the Birdseye view. The order is set at the camera level (when using YAML).

 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> for each camera and set the **Position** field to control the display order.
+Navigate to <NavPath path="Settings > System > Birdseye" /> and in the **Camera order** field, use the drag handle next to each camera name to control the display order.

 </TabItem>
 <TabItem value="yaml">
@@ -140,7 +146,8 @@ Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> for ea
 # Include all cameras by default in Birdseye view
 birdseye:
  enabled: True
-  mode: continuous
+  modes:
+    - continuous

 cameras:
  front:
@@ -3,6 +3,8 @@ id: camera_specific
 title: Camera Specific Configurations
 ---

+import NavPath from "@site/src/components/NavPath";
+
 :::note

 This page makes use of presets of FFmpeg args. For more information on presets, see the [FFmpeg Presets](/configuration/ffmpeg_presets) page.
@@ -148,19 +150,34 @@ WEB Digest Algorithm  - MD5

 Reolink has many different camera models with inconsistently supported features and behavior. The below table shows a summary of various features and recommendations.

-| Camera Resolution | Camera Generation         | Recommended Stream Type           | Additional Notes                                                        |
-| ----------------- | ------------------------- | --------------------------------- | ----------------------------------------------------------------------- |
-| 5MP or lower      | All                       | http-flv                          | Stream is h264                                                          |
-| 6MP or higher     | Latest (ex: Duo3, CX-8##) | http-flv with ffmpeg 8.0, or rtsp | This uses the new http-flv-enhanced over H265 which requires ffmpeg 8.0 |
-| 6MP or higher     | Older (ex: RLC-8##)       | rtsp                              |                                                                         |
+| Camera Resolution | Camera Generation         | Recommended Stream Type           | Additional Notes                                                                            |
+| ----------------- | ------------------------- | --------------------------------- | ------------------------------------------------------------------------------------------- |
+| 5MP or lower      | All                       | http-flv                          | Stream is h264                                                                              |
+| 6MP or higher     | Latest (ex: Duo3, CX-8##) | http-flv with ffmpeg 8.0, or rtsp | This uses the new http-flv-enhanced over H265 which requires ffmpeg 8.0 (Frigate's default) |
+| 6MP or higher     | Older (ex: RLC-8##)       | rtsp                              |                                                                                             |

-Frigate works much better with newer reolink cameras that are setup with the below options:
+Frigate works much better with newer Reolink cameras that are setup with the below options:

 If available, recommended settings are:

 - `On, fluency first` this sets the camera to CBR (constant bit rate)
 - `Interframe Space 1x` this sets the iframe interval to the same as the frame rate

+#### Setup via the Add Camera Wizard
+
+The [Add Camera Wizard](cameras.md#adding-a-camera-with-the-add-camera-wizard) is the recommended way to add a standard Reolink camera. Before starting, make sure [HTTP is enabled](https://support.reolink.com/articles/360003452893-How-to-Access-Reolink-Cameras-NVRs-Home-Hub-Locally-via-Web-Browsers/) in the camera's advanced network settings. The wizard uses the camera's HTTP API to determine its resolution and choose the recommended stream type from the table above.
+
+1. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />.
+2. Choose **Manual selection** as the stream detection method and select **Reolink** as the camera brand.
+3. The wizard queries the camera and automatically uses an http-flv stream for cameras 5MP and lower, or an RTSP stream for higher resolution cameras.
+4. In the validation step, enable **Use stream compatibility mode** for http-flv streams when the wizard recommends it.
+
+If you use the **Probe camera** method instead, the discovered stream URLs will be RTSP. For Reolink cameras where http-flv is recommended, the wizard will show a warning in the validation step.
+
+The wizard covers standard single-camera setups. For two way talk, cameras connected through a Reolink NVR, or audio transcoding for WebRTC live view, configure the camera manually as shown below.
+
+#### Manual configuration
+
 According to [this discussion](https://github.com/blakeblackshear/frigate/issues/3235#issuecomment-1135876973), the http video streams seem to be the most reliable for Reolink.

 Cameras connected via a Reolink NVR can be connected with the http stream, use `channel[0..15]` in the stream url for the additional channels.
@@ -175,7 +192,7 @@ Reolink's latest cameras support two way audio via go2rtc and other applications

 NOTE: The RTSP stream can not be prefixed with `ffmpeg:`, as go2rtc needs to handle the stream to support two way audio.

-Ensure HTTP is enabled in the camera's advanced network settings. To use two way talk with Frigate, see the [Live view documentation](/configuration/live#two-way-talk).
+Ensure [HTTP is enabled](https://support.reolink.com/articles/360003452893-How-to-Access-Reolink-Cameras-NVRs-Home-Hub-Locally-via-Web-Browsers/) in the camera's advanced network settings. To use two way talk with Frigate, see the [Live view documentation](/configuration/live#two-way-talk).

 :::

@@ -187,7 +204,7 @@ go2rtc:
      - "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password#video=copy#audio=copy#audio=opus"
    your_reolink_camera_sub:
      - "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password"
-    # example for connectin to a Reolink camera that supports two way talk
+    # example for connecting to a Reolink camera that supports two way talk
    your_reolink_camera_twt:
      - "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password#video=copy#audio=copy#audio=opus"
      - "rtsp://username:password@reolink_ip/Preview_01_sub"
@@ -225,13 +242,14 @@ cameras:
          roles:
            - detect
 ```
+
 </details>

 ### Unifi Protect Cameras

-:::note 
+:::note

-Unifi G5s cameras and newer need a Unifi Protect server to enable rtsps stream, it's not posible to enable it in standalone mode.
+Unifi G5s cameras and newer need a Unifi Protect server to enable rtsps stream, it's not possible to enable it in standalone mode.

 :::

@@ -246,7 +264,7 @@ go2rtc:
      - rtspx://192.168.1.1:7441/abcdefghijk
 ```

-[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-rtsp)
+[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#source-rtsp)

 In the Unifi 2.0 update Unifi Protect Cameras had a change in audio sample rate which causes issues for ffmpeg. The input rate needs to be set for record if used directly with unifi protect.

@@ -269,7 +287,6 @@ Some community members have found better performance on Wyze cameras by using an
 To use a USB camera (webcam) with Frigate, the recommendation is to use go2rtc's [FFmpeg Device](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg-device) support:

 - Preparation outside of Frigate:
-
  - Get USB camera path. Run `v4l2-ctl --list-devices` to get a listing of locally-connected cameras available. (You may need to install `v4l-utils` in a way appropriate for your Linux distribution). In the sample configuration below, we use `video=0` to correlate with a detected device path of `/dev/video0`
  - Get USB camera formats & resolutions. Run `ffmpeg -f v4l2 -list_formats all -i /dev/video0` to get an idea of what formats and resolutions the USB Camera supports. In the sample configuration below, we use a width of 1024 and height of 576 in the stream and detection settings based on what was reported back.
  - If using Frigate in a container (e.g. Docker on TrueNAS), ensure you have USB Passthrough support enabled, along with a specific Host Device (`/dev/video0`) + Container Device (`/dev/video0`) listed.
@@ -7,6 +7,74 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

+## Adding a camera with the Add Camera Wizard
+
+The Add Camera Wizard is the recommended way to add a camera. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />. The wizard connects to your camera, tests each stream, and writes the camera's configuration for you, including the [go2rtc](go2rtc.md) restream and the live view stream mapping, so a standard setup needs no hand-written YAML.
+
+### Step 1: Name and connection
+
+Enter a name for the camera along with its host or IP address and credentials, then choose how the wizard should find the camera's streams:
+
+- **Probe camera** queries the camera over ONVIF (the ONVIF port is usually 80 or 8080) and asks it for its stream URLs. Some cameras use a separate ONVIF/service account rather than the device admin user, and some require **Use digest authentication** to be enabled.
+- **Manual selection** builds a stream URL from a template for the camera brand you pick (Dahua/Amcrest/EmpireTech, Hikvision/Uniview/Annke, Ubiquiti, Reolink, Axis, TP-Link, or Foscam). Choose **Other** to enter a custom RTSP URL directly. Non-RTSP stream types must be [configured manually](#setting-up-camera-inputs).
+
+The name you enter is lowercased and spaces become underscores. If the result still isn't a valid config key, the wizard generates a safe name and stores what you typed as `friendly_name`.
+
+### Step 2: Probe or snapshot
+
+In probe mode, the wizard reports what the camera returned (manufacturer, model, firmware, profile count, and whether PTZ, presets, and [autotracking](autotracking.md) are supported) along with the RTSP URLs it discovered. Test each candidate to see its resolution, frame rate, and codecs together with a snapshot, then select the one you want to use.
+
+In manual mode, the wizard tests the templated URL and shows the same metadata and snapshot.
+
+If no RTSP URLs are found, the credentials may be wrong or the camera may not support ONVIF. Go back and use manual selection instead.
+
+### Step 3: Stream configuration
+
+Assign [roles](#setting-up-camera-inputs) to the stream, and use **Add Another Stream** to add the camera's other streams, for example a substream for `detect` alongside the main stream for `record`. At least one stream must have the `detect` role before you can continue.
+
+**Reduce connections to camera** routes that input through the go2rtc restream so Frigate and the live view share a single connection to the camera instead of each opening their own. See [restream](restream.md) for more detail.
+
+### Step 4: Validation and testing
+
+Connect each stream to get a live preview, an estimated bandwidth figure, and a list of validation results. The wizard checks for the most common misconfigurations, including:
+
+- A detect resolution that is too high (increased resource usage) or too low for reliable detection, or one it could not probe at all
+- A stream marked `record` whose audio codec is not AAC, or that has no audio at all
+- A stream marked `audio` that carries no audio stream
+- Using a restreamed input for the `record` role
+- Brand-specific issues, such as an RTSP stream on a Reolink camera that should use http-flv, or a Dahua/Hikvision substream selected for `detect`
+
+**Use stream compatibility mode** passes the stream through go2rtc's ffmpeg module. Enable it if a stream fails to load after several attempts. Note that this also prevents [two way talk](/configuration/live#two-way-talk) from being detected for that stream.
+
+**Save New Camera** writes the configuration and starts the camera right away. No restart is required.
+
+Other features, including [hardware acceleration](hardware_acceleration_video.md), [two way talk](/configuration/live#two-way-talk), and audio transcoding, is configured after the camera has been added. For camera model specific quirks, see the [camera specific](camera_specific.md) docs.
+
+## Deleting a camera
+
+Click **Delete Camera** in <NavPath path="Settings > Global configuration > Camera management" />, choose the camera, and confirm. Deleting a camera requires the `admin` role and cannot be undone.
+
+:::warning
+
+Deleting a camera permanently removes its recordings, tracked objects, and configuration. If you only want to stop processing a camera, set its state to **Off** or **Disabled** in <NavPath path="Settings > Global configuration > Camera management" /> instead. See [camera state](/configuration/live#camera-state).
+
+:::
+
+Deleting a camera removes:
+
+- The camera's section of your config file, along with its entries in any [role](authentication.md#user-roles) camera list. A custom role left with no cameras is removed as well.
+- Every database record for the camera: tracked objects, review items, recordings, previews, timeline entries, the saved region grid, and [triggers](semantic_search.md#triggers).
+- Every media file for the camera: recordings, snapshots, thumbnails, and preview clips.
+
+[Exports](/usage/exports) are kept by default, so saved footage survives the deletion of the camera it came from. Turn on **Also delete exports for this camera** in the confirmation step to remove those too.
+
+The camera's processes are stopped and the change takes effect immediately, so no restart is required. If the resulting config cannot be parsed, Frigate restores the previous config and reports an error instead of leaving Frigate in a broken state.
+
+Two things are not cleaned up for you:
+
+- **go2rtc streams.** Frigate makes a best effort to stop a running [go2rtc](go2rtc.md) stream named after the camera, but stream entries in your config file remain and are recreated on the next restart. Remove them in <NavPath path="Settings > System > go2rtc streams" /> or in your config file.
+- **Camera groups.** A deleted camera stays listed in any [camera group](#setting-up-camera-groups) that referenced it. The group skips the missing camera, so this is harmless, but you can edit the group to drop the stale entry.
+
 ## Setting Up Camera Inputs

 Several inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create recordings from a higher resolution stream, or vice versa.
@@ -15,11 +83,12 @@ A camera is enabled by default but can be disabled by using `enabled: False`. Ca

 Each role can only be assigned to one input per camera. The options for roles are as follows:

-| Role     | Description                                                                         |
-| -------- | ----------------------------------------------------------------------------------- |
-| `detect` | Main feed for object detection. [docs](object_detectors.md)                         |
-| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md) |
-| `audio`  | Feed for audio based detection. [docs](audio_detectors.md)                          |
+| Role         | Description                                                                                                  |
+| ------------ | ------------------------------------------------------------------------------------------------------------ |
+| `detect`     | Main feed for object detection. [docs](object_detectors.md)                                                  |
+| `record`     | Saves segments of the video feed based on configuration settings. [docs](record.md)                          |
+| `record_sub` | Saves segments of a second, lower quality stream with its own retention. [docs](record.md#sub-stream-recording) |
+| `audio`      | Feed for audio based detection. [docs](audio_detectors.md)                                                   |

 <ConfigTabs>
 <TabItem value="ui">
@@ -69,7 +138,7 @@ Additional cameras are simply added under the camera configuration section.
 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and use the add camera button to configure each additional camera.
+Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and use the [Add Camera Wizard](#adding-a-camera-with-the-add-camera-wizard) to configure each additional camera.

 </TabItem>
 <TabItem value="yaml">
@@ -194,7 +263,7 @@ Camera groups let you organize cameras together with a shared name and icon, mak
 <ConfigTabs>
 <TabItem value="ui">

-On the Live dashboard, press the **+** icon in the main navigation to add a new camera group. Configure the group name, select which cameras to include, choose an icon, and set the display order.
+On the Live dashboard, press the **pencil icon** in the main navigation to add a new camera group. Configure the group name, select which cameras to include, choose an icon, and set the display order.

 </TabItem>
 <TabItem value="yaml">
@@ -7,7 +7,7 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

-Frigate can be configured through the **Settings UI** or by editing the YAML configuration file directly. The Settings UI is the recommended approach — it provides validation and a guided experience for all configuration options.
+Frigate can be configured through the **Settings UI** or by editing the YAML configuration file directly. The Settings UI is the recommended approach. It provides validation and a guided experience for all configuration options.

 ## Using the Settings UI

@@ -17,10 +17,10 @@ The Settings UI groups every configuration option into sections that are listed

 Settings are organized into two scopes:

- **Global configuration** — values under <NavPath path="Settings > Global configuration" /> apply to every camera by default. This is where you set the baseline behavior for object detection, recording, snapshots, motion, and so on.
- **Camera configuration** — values under <NavPath path="Settings > Camera configuration" /> apply to a single camera. Use the camera selector button at the top of these pages to choose which camera you are editing.
+- **Global configuration**: values under <NavPath path="Settings > Global configuration" /> apply to every camera by default. This is where you set the baseline behavior for object detection, recording, snapshots, motion, and so on.
+- **Camera configuration**: values under <NavPath path="Settings > Camera configuration" /> apply to a single camera. Use the camera selector button at the top of these pages to choose which camera you are editing.

-When a camera-level section is left untouched, the camera simply inherits the global values. Changing a value on a camera page **overrides** the global value for that camera only — the global setting and every other camera are unaffected. This mirrors how the YAML works, where a value set under `cameras.<name>` takes precedence over the same value set at the top level.
+When a camera-level section is left untouched, the camera simply inherits the global values. Changing a value on a camera page **overrides** the global value for that camera only: the global setting and every other camera are unaffected. This mirrors how the YAML works, where a value set under `cameras.<name>` takes precedence over the same value set at the top level. See [Global and Camera-Level Configuration](./config_overrides.md) for the full details, including how lists and maps are handled and which settings must be enabled globally first.

 To undo an override and go back to inheriting from the parent scope, use the reset button at the bottom of the section:

@@ -36,7 +36,7 @@ Edits are not applied until you save them. As soon as you change a value, the UI
 - The edited section shows a **Modified** badge, and the changed fields are highlighted.
 - A **You have unsaved changes** notice appears above the section's **Save** and **Undo** buttons. **Save** commits just that section; **Undo** discards its pending edits.

-Because pending changes can span multiple sections — and multiple cameras — the header provides a **Save All** button that writes every pending change at once. Next to it, **Review pending changes** opens a summary that lists each pending edit with its scope (Global or a specific camera), the affected field, and the new value, so you can confirm exactly what will be written before committing. **Undo All** discards every pending change across all sections.
+Because pending changes can span multiple sections (and multiple cameras), the header provides a **Save All** button that writes every pending change at once. Next to it, **Review pending changes** opens a summary that lists each pending edit with its scope (Global or a specific camera), the affected field, and the new value, so you can confirm exactly what will be written before committing. **Undo All** discards every pending change across all sections.

 ### Restart-required indicators

@@ -48,17 +48,17 @@ When you save a change that touches one of these fields, Frigate confirms the sa

 When you are working under <NavPath path="Settings > Camera configuration" />, small colored dots can appear next to a section's name in the menu. They give you an at-a-glance summary of that section's state for the selected camera:

- **Blue dot** — this section **overrides the global configuration**. One or more values in the section have been set specifically for this camera and differ from the global defaults.
- **Profile-colored dot** — when you are viewing a [camera profile](./profiles.md), a dot in that profile's assigned color indicates the section is **overridden by that profile**. Each profile is given its own distinct color so you can tell at a glance which sections it changes.
- **Amber dot** — this section has **unsaved changes**. It appears alongside the **Modified** badge whenever you have pending edits in the section that haven't been saved yet.
+- **Blue dot**: this section **overrides the global configuration**. One or more values in the section have been set specifically for this camera and differ from the global defaults.
+- **Profile-colored dot**: when you are viewing a [camera profile](./profiles.md), a dot in that profile's assigned color indicates the section is **overridden by that profile**. Each profile is given its own distinct color so you can tell at a glance which sections it changes.
+- **Amber dot**: this section has **unsaved changes**. It appears alongside the **Modified** badge whenever you have pending edits in the section that haven't been saved yet.

-Hover over any dot to see a tooltip describing what it means. Open a section to see exactly which fields are overridden — the section header indicates how many fields differ from the global (or base) configuration.
+Hover over any dot to see a tooltip describing what it means. Open a section to see exactly which fields are overridden: the section header indicates how many fields differ from the global (or base) configuration.

 ## Configuration File Location

 For users who prefer to edit the YAML configuration file directly, it is recommended to start with a minimal configuration and add to it as described in [the getting started guide](../guides/getting_started.md).

- **Home Assistant App:** `/addon_configs/<addon_directory>/config.yml` — see [directory list](#accessing-app-config-dir)
+- **Home Assistant App:** `/addon_configs/<addon_directory>/config.yml` (see [directory list](#accessing-app-config-dir))
 - **All other installations:** Map to `/config/config.yml` inside the container

 It can be named `config.yml` or `config.yaml`, but if both files exist `config.yml` will be preferred and `config.yaml` will be ignored.
@@ -100,7 +100,7 @@ VS Code supports JSON schemas for automatically validating configuration files.

 ## Environment Variable Substitution

-Frigate supports the use of environment variables starting with `FRIGATE_` **only** where specifically indicated in the [reference config](./advanced/reference.md). For example, the following values can be replaced at runtime by using environment variables:
+Frigate supports the use of environment variables starting with `FRIGATE_` **only** where specifically indicated in the [reference config](./advanced/reference.md). See [substitution sources and precedence](./advanced/system.md#substitution-sources-and-precedence) for where those values can come from, including `secrets.yaml`. For example, the following values can be replaced at runtime by using environment variables:

 ```yaml
 mqtt:
@@ -130,7 +130,8 @@ go2rtc:

 ```yaml
 genai:
-  api_key: "{FRIGATE_GENAI_API_KEY}"
+  my_provider:
+    api_key: "{FRIGATE_GENAI_API_KEY}"
 ```

 ## Common configuration examples
@@ -153,7 +154,7 @@ Here are some common starter configuration examples. These can be configured thr

 1. Navigate to <NavPath path="Settings > System > MQTT" /> and configure the MQTT connection to your Home Assistant Mosquitto broker
 2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `Raspberry Pi (H.264)`
-3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`
+3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown
 4. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
 5. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
 6. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -171,10 +172,9 @@ mqtt:
 ffmpeg:
  hwaccel_args: preset-rpi-64-h264

-detectors:
-  coral:
-    type: edgetpu
-    device: usb
+models:
+  - devices:
+      - edgetpu:usb

 record:
  enabled: True
@@ -232,7 +232,7 @@ cameras:

 1. Navigate to <NavPath path="Settings > System > MQTT" /> and set **Enable MQTT** to off
 2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `VAAPI (Intel/AMD GPU)`
-3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`
+3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown
 4. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
 5. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
 6. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -248,10 +248,9 @@ mqtt:
 ffmpeg:
  hwaccel_args: preset-vaapi

-detectors:
-  coral:
-    type: edgetpu
-    device: usb
+models:
+  - devices:
+      - edgetpu:usb

 record:
  enabled: True
@@ -309,8 +308,8 @@ cameras:

 1. Navigate to <NavPath path="Settings > System > MQTT" /> and configure the connection to your MQTT broker
 2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `VAAPI (Intel/AMD GPU)`
-3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `openvino` and **Device** `AUTO`
-4. On the same page, in the **Custom Model** tab, configure the OpenVINO model path and settings
+3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Intel GPU** from the **Hardware** dropdown
+4. On the same model, open the **Custom Model** tab and configure the OpenVINO model path and settings
 5. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
 6. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
 7. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -328,15 +327,12 @@ mqtt:
 ffmpeg:
  hwaccel_args: preset-vaapi

-detectors:
-  ov:
-    type: openvino
-    device: AUTO
-
-model:
-  width: 300
-  height: 300
-  input_tensor: nhwc
+models:
+  - devices:
+      - openvino:AUTO
+    width: 300
+    height: 300
+    input_tensor: nhwc
  input_pixel_format: bgr
  path: /openvino-model/ssdlite_mobilenet_v2.xml
  labelmap_path: /openvino-model/coco_91cl_bkgr.txt
@@ -0,0 +1,244 @@
+---
+id: config_overrides
+title: Global and Camera-Level Configuration
+---
+
+import ConfigTabs from "@site/src/components/ConfigTabs";
+import TabItem from "@theme/TabItem";
+import NavPath from "@site/src/components/NavPath";
+
+Most of Frigate's configuration can be set once for all cameras and then adjusted for individual cameras. The global value acts as the default for every camera, and any camera can override it.
+
+This page explains how that inheritance works. For a tour of the Settings UI itself, see [Frigate Configuration](./config.md).
+
+## The basics
+
+Set a value globally and every camera uses it. Set the same value on a camera and that camera uses its own value instead.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+1. Navigate to <NavPath path="Settings > Global configuration > Object detection" /> and set **Detect FPS** to `5`. Every camera now detects at 5 fps.
+2. Navigate to <NavPath path="Settings > Camera configuration > Object detection" />, select the `driveway` camera, and set **Detect FPS** to `10`.
+
+The `driveway` camera now detects at 10 fps. Every other camera still uses the global value of 5.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+detect:
+  fps: 5 # every camera detects at 5 fps
+
+cameras:
+  front_door:
+    ffmpeg: ...
+  driveway:
+    ffmpeg: ...
+    detect:
+      fps: 10 # except this one
+```
+
+`front_door` inherits `fps: 5`, and `driveway` uses `10`.
+
+</TabItem>
+</ConfigTabs>
+
+## Overrides apply per value, not per section
+
+Overriding one value in a section does not detach the rest of that section. Everything you don't set on the camera still comes from the global configuration.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+If you set a camera's **Motion threshold** but leave **Contour area** alone, only the threshold is overridden. The contour area continues to follow <NavPath path="Settings > Global configuration > Motion detection" />, and changing it there still affects that camera.
+
+Open a section to see which values are overridden: the section header indicates how many fields differ from the global configuration.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+motion:
+  threshold: 30
+  contour_area: 10
+
+cameras:
+  driveway:
+    motion:
+      threshold: 40
+```
+
+The `driveway` camera ends up with `threshold: 40` and `contour_area: 10`. Only the value you wrote was overridden.
+
+</TabItem>
+</ConfigTabs>
+
+## Returning a camera to the global value
+
+<ConfigTabs>
+<TabItem value="ui">
+
+A camera section that has its own values shows an **Overridden** badge. To remove the override and go back to inheriting, use the **Reset to Global** button at the bottom of the section.
+
+</TabItem>
+<TabItem value="yaml">
+
+Frigate treats a camera value as an override because it is written in the config file, not because it differs from the global value. Repeating the global value under a camera still creates an override:
+
+```yaml
+snapshots:
+  enabled: true
+
+cameras:
+  driveway:
+    snapshots:
+      enabled: true # this is an override, even though it matches
+```
+
+If you later change the global `snapshots.enabled` to `false`, `driveway` keeps saving snapshots, because it has its own value. To make a camera follow the global value again, delete the key from the camera rather than setting it to match.
+
+</TabItem>
+</ConfigTabs>
+
+## Lists replace, maps merge
+
+This is the distinction that surprises people most.
+
+**Lists are replaced entirely.** A camera's list does not add to the global list, it takes its place.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+The camera page shows the objects the camera is currently tracking, starting from the global list. Changing that selection under <NavPath path="Settings > Camera configuration > Objects" /> replaces the list for that camera, so make sure every object you want tracked is selected, not just the ones you are adding.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+objects:
+  track:
+    - person
+    - car
+
+cameras:
+  backyard:
+    objects:
+      track:
+        - dog # backyard tracks ONLY dog, not person or car
+```
+
+To track `dog` in addition to the global objects, list all of them on the camera.
+
+</TabItem>
+</ConfigTabs>
+
+An empty list is a valid override, and is the normal way to opt a camera out of something:
+
+```yaml
+review:
+  alerts:
+    labels:
+      - person
+
+cameras:
+  street:
+    review:
+      alerts:
+        labels: [] # this camera never creates alerts
+```
+
+**Maps are merged key by key.** A camera can add an entry without redeclaring the others.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+Adding a filter for one object under <NavPath path="Settings > Camera configuration > Objects" /> does not remove the filters inherited from <NavPath path="Settings > Global configuration > Objects" />. The camera keeps both.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+objects:
+  filters:
+    person:
+      min_area: 5000
+
+cameras:
+  driveway:
+    objects:
+      filters:
+        car:
+          min_area: 10000
+```
+
+The `driveway` camera ends up with both the `car` filter it defined and the `person` filter from the global configuration.
+
+</TabItem>
+</ConfigTabs>
+
+## Which settings can be overridden
+
+Most, but not all. The [full reference config](./advanced/reference.md) is the authoritative source: sections that support camera-level overrides are marked with the comment `# NOTE: Can be overridden at the camera level`. In the UI, a setting can be overridden if it appears under both <NavPath path="Settings > Global configuration" /> and <NavPath path="Settings > Camera configuration" />.
+
+A few things worth knowing beyond that:
+
+- Some sections are **global only** and have no camera-level equivalent, including `go2rtc`, `genai` providers, `classification`, `telemetry`, `camera_groups`, and `ui`.
+- Some sections exist **only at the camera level**, such as `zones` and `onvif`.
+- Some sections are **partially overridable**, meaning a camera accepts only a few of the keys available globally. `face_recognition`, `lpr`, and `audio_transcription` work this way, and the reference config notes which keys apply.
+
+## Enrichments that must be enabled globally first
+
+License plate recognition and face recognition are special: the global setting is not just a default, it is a switch that must be on before any camera can use the feature. Enabling one on a camera while it is disabled globally is a configuration error, and Frigate will refuse to start:
+
+```
+Camera driveway has lpr enabled but lpr is disabled at the global level of the config. You must enable lpr at the global level.
+```
+
+Enable the feature globally, then turn it off on the cameras that don't need it.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+1. Navigate to <NavPath path="Settings > Global configuration > License plate recognition" /> and enable **LPR**.
+2. Navigate to <NavPath path="Settings > Camera configuration > License plate recognition" />, select each camera that should not run LPR, and disable the **Enable LPR** toggle.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+lpr:
+  enabled: true
+
+cameras:
+  driveway:
+    ffmpeg: ... # inherits lpr, enabled
+  backyard:
+    ffmpeg: ...
+    lpr:
+      enabled: false # opted out
+```
+
+</TabItem>
+</ConfigTabs>
+
+:::note
+
+This applies only to `lpr` and `face_recognition`, because the global setting controls whether the supporting background process starts at all. Other features do not work this way. Audio transcription, for example, can be enabled on a single camera without being enabled globally.
+
+:::
+
+## Profiles
+
+[Profiles](./profiles.md) add a further layer on top of everything described above. A profile is a named set of camera overrides that you can switch on and off while Frigate is running, for example to change detection and recording behavior when you leave the house.
+
+Profiles are applied on top of a camera's already-resolved configuration, so a profile value wins over both the camera and the global value while that profile is active. Profiles cover a subset of the camera sections and do not modify your config file.
+
+## Summary
+
+- A camera inherits every value you don't set on it.
+- Overriding one value does not detach the rest of the section.
+- Writing a value on a camera overrides it, even if it matches the global value. Remove it to inherit again.
+- Lists replace the global list. Maps merge into it.
+- An empty list is an override, not an omission.
+- `lpr` and `face_recognition` must be enabled globally before a camera can use them.
@@ -11,7 +11,7 @@ Object classification allows you to train a custom MobileNetV2 classification mo

 :::info

-Training a custom object classification model requires a one-time internet connection to download MobileNetV2 base weights. Once trained, the model runs fully offline. See [Network Requirements](/frigate/network_requirements#one-time-model-downloads) for details.
+Training a custom object classification model requires an internet connection to download MobileNetV2 base weights. By default these weights are not cached in `/config/`, so they are downloaded again after the container is recreated. Once trained, the model runs fully offline. See [Network Requirements](/frigate/network_requirements#one-time-model-downloads) for details.

 :::

@@ -137,7 +137,7 @@ If examples for some of your classes do not appear in the grid, you can continue

 :::tip Diversity matters far more than volume

-Selecting dozens of nearly identical images is one of the fastest ways to degrade model performance. MobileNetV2 can overfit quickly when trained on homogeneous data — the model learns what _that exact moment_ looked like rather than what actually defines the class. **This is why Frigate does not implement bulk training in the UI.**
+Selecting dozens of nearly identical images is one of the fastest ways to degrade model performance. MobileNetV2 can overfit quickly when trained on homogeneous data. The model learns what _that exact moment_ looked like rather than what actually defines the class. **This is why Frigate does not implement bulk training in the UI.**

 For more detail, see [Frigate Tip: Best Practices for Training Face and Custom Classification Models](https://github.com/blakeblackshear/frigate/discussions/21374).

@@ -155,7 +155,7 @@ For more detail, see [Frigate Tip: Best Practices for Training Face and Custom C

 :::tip `none` works differently from named classes

-Named classes work best with visually uniform examples — every Buddy photo should look like Buddy. The `none` class needs the opposite: visual diversity across sizes, framings, and qualities, because at inference it has to absorb everything that isn't one of your named classes. Don't apply the same "only keep large, well-framed images" rule to `none` that you would to a named class. Mix in small crops, partial views, and false positives deliberately - otherwise the model has no signal for "small/ambiguous thing = not one of my known classes" and will force those crops into a named class by default.
+Named classes work best with visually uniform examples. Every Buddy photo should look like Buddy. The `none` class needs the opposite: visual diversity across sizes, framings, and qualities, because at inference it has to absorb everything that isn't one of your named classes. Don't apply the same "only keep large, well-framed images" rule to `none` that you would to a named class. Mix in small crops, partial views, and false positives deliberately - otherwise the model has no signal for "small/ambiguous thing = not one of my known classes" and will force those crops into a named class by default.

 :::

@@ -11,7 +11,7 @@ State classification allows you to train a custom MobileNetV2 classification mod

 :::info

-Training a custom state classification model requires a one-time internet connection to download MobileNetV2 base weights. Once trained, the model runs fully offline. See [Network Requirements](/frigate/network_requirements#one-time-model-downloads) for details.
+Training a custom state classification model requires an internet connection to download MobileNetV2 base weights. By default these weights are not cached in `/config/`, so they are downloaded again after the container is recreated. Once trained, the model runs fully offline. See [Network Requirements](/frigate/network_requirements#one-time-model-downloads) for details.

 :::

@@ -73,9 +73,13 @@ classification:
        interval: 10 # also run every N seconds (optional)
        cameras:
          front:
-            crop: [0, 180, 220, 400]
+            # [x1, y1, x2, y2] as decimals between 0 and 1, relative to the
+            # camera's detect resolution
+            crop: [0.0, 0.25, 0.3, 0.85]
 ```

+Crop coordinates are normalized: each value is a fraction of the camera's `detect` width or height, not a pixel value. Drawing the crop in the UI wizard writes these values for you.
+
 An optional config, `save_attempts`, can be set as a key under the model name. This defines the number of classification attempts to save in the Recent Classifications tab. For state classification models, the default is 100.

 </TabItem>
@@ -103,7 +107,7 @@ Once some images are assigned, training will begin automatically.

 :::tip Diversity matters far more than volume

-Selecting dozens of nearly identical images is one of the fastest ways to degrade model performance. MobileNetV2 can overfit quickly when trained on homogeneous data — the model learns what _that exact moment_ looked like rather than what actually defines the state. This often leads to models that work perfectly under the original conditions but become unstable when day turns to night, weather changes, or seasonal lighting shifts. **This is why Frigate does not implement bulk training in the UI.**
+Selecting dozens of nearly identical images is one of the fastest ways to degrade model performance. MobileNetV2 can overfit quickly when trained on homogeneous data. The model learns what _that exact moment_ looked like rather than what actually defines the state. This often leads to models that work perfectly under the original conditions but become unstable when day turns to night, weather changes, or seasonal lighting shifts. **This is why Frigate does not implement bulk training in the UI.**

 For more detail, see [Frigate Tip: Best Practices for Training Face and Custom Classification Models](https://github.com/blakeblackshear/frigate/discussions/21374).

@@ -6,6 +6,7 @@ title: Face Recognition
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 Face recognition identifies known individuals by matching detected faces with previously learned facial data. When a known `person` is recognized, their name will be added as a `sub_label`. This information is included in the UI, filters, as well as in notifications.

@@ -86,7 +87,7 @@ Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
 - **Detection threshold**: Face detection confidence score required before recognition runs. This field only applies to the standalone face detection model; `min_score` should be used to filter for models that have face detection built in.
  - Default: `0.7`
 - **Minimum face area**: Minimum size (in pixels) a face must be before recognition runs. Depending on the resolution of your camera's `detect` stream, you can increase this value to ignore small or distant faces.
-  - Default: `500` pixels
+  - Default: `750` pixels

 </TabItem>
 <TabItem value="yaml">
@@ -95,7 +96,7 @@ Navigate to <NavPath path="Settings > Enrichments > Face recognition" />.
 face_recognition:
  enabled: true
  detection_threshold: 0.7
-  min_area: 500
+  min_area: 750
 ```

 </TabItem>
@@ -151,6 +152,14 @@ Follow these steps to begin:

 ## Creating a Robust Training Set

+:::tip
+
+**The short version:** Start with a few clear, front-facing photos of each person. As faces are detected in the Recent Recognitions tab, train clear images that scored lower, adding variety (different angles, lighting, and expressions) slowly. Diversity matters far more than volume, and low-quality images hurt recognition more than they help.
+
+For a step-by-step narrative of these best practices (and the same principles applied to state and object classification), see the [Frigate Tips: Best Practices for Training](https://github.com/blakeblackshear/frigate/discussions/21374) discussion.
+
+:::
+
 The number of images needed for a sufficient training set for face recognition varies depending on several factors:

 - Diversity of the dataset: A dataset with diverse images, including variations in lighting, pose, and facial expressions, will require fewer images per person than a less diverse dataset.
@@ -181,9 +190,27 @@ When choosing images to include in the face training set it is recommended to al

 The Recent Recognitions tab in the face library displays recent face recognition attempts. Detected face images are grouped according to the person they were identified as potentially matching.

-Each face image is labeled with a name (or `Unknown`) along with the confidence score of the recognition attempt. While each image can be used to train the system for a specific person, not all images are suitable for training.
+Each face image is labeled with a name (or `Unknown`) along with the confidence score of that recognition attempt. Images are grouped by the person they were matched against, not by who they actually are, so a group labeled with a person's name can contain a crop that is really someone else but happened to score as a partial match. The name and score shown on each individual crop describe that single attempt.

-Refer to the guidelines below for best practices on selecting images for training.
+While each image can be used to train the system for a specific person, not all images are suitable for training. Refer to the guidelines below for best practices on selecting images for training.
+
+### How Frigate Decides Who a Person Is
+
+Recognition does not happen one frame at a time. While a `person` is in view, Frigate runs face recognition on many frames, not just a single frame. The final `sub_label` is decided from all of those attempts together, weighted by the area of each face (larger, closer faces count more), not from any single frame.
+
+This has a few practical consequences:
+
+- A handful of wrong guesses on blurry or distant frames usually do not change the result. If Frigate sees a person as "Tom, Tom, Sam, Tom, Tom," it will still conclude the person was Tom.
+- The goal is not for every individual face crop to be correct. The goal is for each person to be recognized correctly overall, across all the faces captured while they were present.
+- A single very high confidence match will not by itself assign a sub label. Recognition must be consistent. See [I see scores above the threshold in the Recent Recognitions tab, but a sub label wasn't assigned?](#i-see-scores-above-the-threshold-in-the-recent-recognitions-tab-but-a-sub-label-wasnt-assigned) below.
+
+### Which Faces Are Worth Training?
+
+Whether a face is worth training has little to do with what it was recognized as. A crop is a good training candidate when all of these are true:
+
+- It did not already score high and correctly. Faces that are already recognized confidently add little and increase the risk of over-fitting.
+- It is clear enough to be useful: not blurry, not heavily off-axis, not infrared (gray-scale). If it is hard for you to make out the face, it will not help the model.
+- It adds something new: a different angle, lighting, expression, or distance than what you already have.

 ### Step 1 - Building a Strong Foundation

@@ -199,39 +226,81 @@ Once front-facing images are performing well, start choosing slightly off-angle

 ## FAQ

-### How do I debug Face Recognition issues?
+### Getting Recognition Working
+
+<FaqItem id="how-do-i-debug-face-recognition-issues" question="How do I debug Face Recognition issues?">

 Start with the [Usage](#usage) section and re-read the [Model Requirements](#model-requirements) above.

-1. Ensure `person` is being _detected_. A `person` will automatically be scanned by Frigate for a face. Any detected faces will appear in the Recent Recognitions tab in the Frigate UI's Face Library.
+1. Enable debug logs to see exactly what Frigate is doing.
+   - Enable debug logs for face recognition by adding `frigate.data_processing.real_time.face: debug` to your `logger` configuration. Restart Frigate after this change.
+
+     ```yaml
+     logger:
+       default: info
+       logs:
+         # highlight-next-line
+         frigate.data_processing.real_time.face: debug
+     ```
+
+   - These logs report where the pipeline stopped for each `person` object, such as no face being found within the person's bounding box, the detected face being smaller than `min_area`, or a face being recognized but scoring too low.
+   - If you see no face-related messages at all, also add `frigate.embeddings.maintainer: debug` to confirm that the face processor was created at startup and that `person` updates are reaching it.
+
+2. Ensure `person` is being _detected_. A `person` will automatically be scanned by Frigate for a face. Any detected faces will appear in the Recent Recognitions tab in the Frigate UI's Face Library.

   If you are using a Frigate+ or `face` detecting model:
-   - Watch the debug view (Settings --> Debug) to ensure that `face` is being detected along with `person`.
+   - Watch the [debug view](/usage/live#the-single-camera-view) to ensure that `face` is being detected along with `person`.
   - You may need to adjust the `min_score` for the `face` object if faces are not being detected.

   If you are **not** using a Frigate+ or `face` detecting model:
   - Check your `detect` stream resolution and ensure it is sufficiently high enough to capture face details on `person` objects.
   - You may need to lower your `detection_threshold` if faces are not being detected.

-2. Any detected faces will then be _recognized_.
+3. Any detected faces will then be _recognized_.
   - Make sure you have trained at least one face per the recommendations above.
   - Adjust `recognition_threshold` settings per the suggestions [above](#advanced-configuration).

-### Detection does not work well with blurry images?
+</FaqItem>

-Accuracy is definitely a going to be improved with higher quality cameras / streams. It is important to look at the DORI (Detection Observation Recognition Identification) range of your camera, if that specification is posted. This specification explains the distance from the camera that a person can be detected, observed, recognized, and identified. The identification range is the most relevant here, and the distance listed by the camera is the furthest that face recognition will realistically work.
+<FaqItem id="does-face-recognition-run-on-the-recording-stream" question="Does face recognition run on the recording stream?">
+
+Face recognition does not run on the recording stream, this would be suboptimal for many reasons:
+
+1. The latency of accessing the recordings means the notifications would not include the names of recognized people because recognition would not complete until after.
+2. The embedding models used run on a set image size, so larger images will be scaled down to match this anyway.
+3. Motion clarity is much more important than extra pixels, over-compression and motion blur are much more detrimental to results than resolution.
+
+</FaqItem>
+
+### Improving Accuracy and Training
+
+<FaqItem id="detection-does-not-work-well-with-blurry-images" question="Detection does not work well with blurry images?">
+
+Accuracy is definitely going to be improved with higher quality cameras / streams. It is important to look at the DORI (Detection Observation Recognition Identification) range of your camera, if that specification is posted. This specification explains the distance from the camera that a person can be detected, observed, recognized, and identified. The identification range is the most relevant here, and the distance listed by the camera is the furthest that face recognition will realistically work.

 Some users have also noted that setting the stream in camera firmware to a constant bit rate (CBR) leads to better image clarity than with a variable bit rate (VBR).

-### Why can't I bulk upload photos?
+</FaqItem>
+
+<FaqItem id="can-i-train-faces-for-people-who-only-appear-at-night" question="Can I train faces for people who only appear at night?">
+
+The embedding models are trained on color images, so gray-scale and infrared (IR) faces sit in a different feature distribution and are more easily confused with other people. Prefer color images, and avoid mixing gray-scale samples in early while you are building a foundation. If someone only ever appears at night, gray-scale training is acceptable, but keep those samples limited and as clear as possible, and add them only once color recognition is stable for your other people.
+
+</FaqItem>
+
+<FaqItem id="why-cant-i-bulk-upload-photos" question="Why can't I bulk upload photos?">

 It is important to methodically add photos to the library, bulk importing photos (especially from a general photo library) will lead to over-fitting in that particular scenario and hurt recognition performance.

-### Why can't I bulk reprocess faces?
+</FaqItem>
+
+<FaqItem id="why-cant-i-bulk-reprocess-faces" question="Why can't I bulk reprocess faces?">

 Face embedding models work by breaking apart faces into different features. This means that when reprocessing an image, only images from a similar angle will have its score affected.

-### Why do unknown people score similarly to known people?
+</FaqItem>
+
+<FaqItem id="why-do-unknown-people-score-similarly-to-known-people" question="Why do unknown people score similarly to known people?">

 This can happen for a few different reasons, but this is usually an indicator that the training set needs to be improved. This is often related to over-fitting:

@@ -241,33 +310,54 @@ This can happen for a few different reasons, but this is usually an indicator th

 Review your face collections and remove most of the unclear or low-quality images. Then, use the **Reprocess** button on each face in the **Train** tab to evaluate how the changes affect recognition scores.

-Avoid training on images that already score highly, as this can lead to over-fitting. Instead, focus on relatively clear images that score lower - ideally with different lighting, angles, and conditions—to help the model generalize more effectively.
+Avoid training on images that already score highly, as this can lead to over-fitting. Instead, focus on relatively clear images that score lower (ideally with different lighting, angles, and conditions) to help the model generalize more effectively.

-### Frigate misidentified a face. Can I tell it that a face is "not" a specific person?
+</FaqItem>
+
+<FaqItem id="should-i-correct-a-face-that-was-recognized-as-the-wrong-person" question="Should I correct a face that was recognized as the wrong person?">
+
+Only if it is a good image. Reassigning a face does add it to that person's training set, but two things are true at once:
+
+- Reassigning a single misclassified frame has a small effect. The image is weighted against every other sample for that person, so correcting 1 frame out of 20 will not move recognition much. Occasional wrong guesses on poor frames are normal and do not need to be fixed.
+- Reassigning a poor image (blurry, off-angle, low-resolution, gray-scale) can hurt more than the misidentification did, because low-quality samples degrade recognition for that whole person.
+
+So the decision is about image quality, not about the wrong label. If the crop is clear, well-lit, and reasonably front-facing, and it scored low or was wrong, assigning it to the correct person is useful. If you can barely make out the face yourself, ignore it; do not train it just to correct the label.
+
+If a person is repeatedly misidentified, do not keep reassigning the same frame. Instead, remove low-quality or misleading images and add a few high-quality samples to the correct person. See [Why do unknown people score similarly to known people?](#why-do-unknown-people-score-similarly-to-known-people) above.
+
+</FaqItem>
+
+<FaqItem id="frigate-misidentified-a-face-can-i-tell-it-that-a-face-is-not-a-specific-person" question={'Frigate misidentified a face. Can I tell it that a face is "not" a specific person?'}>

 No, face recognition does not support negative training (i.e., explicitly telling it who someone is _not_). Instead, the best approach is to improve the training data by using a more diverse and representative set of images for each person.
 For more guidance, refer to the section above on improving recognition accuracy.

-### I see scores above the threshold in the Recent Recognitions tab, but a sub label wasn't assigned?
+This also applies to a stranger who is repeatedly matched to a known person (for example, a delivery driver recognized as you). Do not create a profile for them and do not reassign their faces to yourself, as this pollutes your training set and makes recognition worse. Leave the detection as unknown and improve the known person's training set instead. Face recognition learns who someone is, not who they are not.

-The Frigate considers the recognition scores across all recognition attempts for each person object. The scores are continually weighted based on the area of the face, and a sub label will only be assigned to person if a person is confidently recognized consistently. This avoids cases where a single high confidence recognition would throw off the results.
+</FaqItem>

-### Can I use other face recognition software like DoubleTake at the same time as the built in face recognition?
+<FaqItem id="i-see-scores-above-the-threshold-in-the-recent-recognitions-tab-but-a-sub-label-wasnt-assigned" question="I see scores above the threshold in the Recent Recognitions tab, but a sub label wasn't assigned?">
+
+Frigate considers the recognition scores across all recognition attempts for each person object. The scores are continually weighted based on the area of the face, and a sub label will only be assigned to person if a person is confidently recognized consistently. This avoids cases where a single high confidence recognition would throw off the results.
+
+</FaqItem>
+
+### Compatibility and Maintenance
+
+<FaqItem id="can-i-use-other-face-recognition-software-like-doubletake-at-the-same-time-as-the-built-in-face-recognition" question="Can I use other face recognition software like DoubleTake at the same time as the built in face recognition?">

 No, using another face recognition service will interfere with Frigate's built in face recognition. When using double-take the sub_label feature must be disabled if the built in face recognition is also desired.

-### Does face recognition run on the recording stream?
+</FaqItem>

-Face recognition does not run on the recording stream, this would be suboptimal for many reasons:
-
-1. The latency of accessing the recordings means the notifications would not include the names of recognized people because recognition would not complete until after.
-2. The embedding models used run on a set image size, so larger images will be scaled down to match this anyway.
-3. Motion clarity is much more important than extra pixels, over-compression and motion blur are much more detrimental to results than resolution.
-
-### I get an unknown error when taking a photo directly with my iPhone
+<FaqItem id="i-get-an-unknown-error-when-taking-a-photo-directly-with-my-iphone" question="I get an unknown error when taking a photo directly with my iPhone">

 By default iOS devices will use HEIC (High Efficiency Image Container) for images, but this format is not supported for uploads. Choosing `large` as the format instead of `original` will use JPG which will work correctly.

-### How can I delete the face database and start over?
+</FaqItem>
+
+<FaqItem id="how-can-i-delete-the-face-database-and-start-over" question="How can I delete the face database and start over?">

 Frigate does not store anything in its database related to face recognition. You can simply delete all of your faces through the Frigate UI or remove the contents of the `/media/frigate/clips/faces` directory.
+
+</FaqItem>
@@ -7,27 +7,27 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

-Some presets of FFmpeg args are provided by default to make the configuration easier. All presets can be seen in [this file](https://github.com/blakeblackshear/frigate/blob/master/frigate/ffmpeg_presets.py).
+Frigate ships with a set of FFmpeg presets to keep your configuration short and readable. Each preset expands to a longer list of FFmpeg arguments at runtime. You can see exactly what every preset expands to in [this file](https://github.com/blakeblackshear/frigate/blob/master/frigate/ffmpeg_presets.py).

-### Hwaccel Presets
+In the config file you reference a preset by its name (for example, `preset-vaapi`). In the UI, the same preset is shown with a friendly label (for example, **VAAPI (Intel/AMD GPU)**). Both refer to the same thing: the tables below list the config name alongside the label you'll see in the UI.

-It is highly recommended to use hwaccel presets in the config. These presets not only replace the longer args, but they also give Frigate hints of what hardware is available and allows Frigate to make other optimizations using the GPU such as when encoding the birdseye restream or when scaling a stream that has a size different than the native stream size.
+### Hwaccel (Hardware Acceleration) Presets {#hwaccel-presets}

-See [the hwaccel docs](/configuration/hardware_acceleration_video.md) for more info on how to setup hwaccel for your GPU / iGPU.
+Hardware acceleration arguments tell FFmpeg to decode your camera's video stream on a GPU or integrated graphics chip instead of the CPU, which dramatically lowers CPU usage. Using a preset is highly recommended. Beyond replacing a long list of arguments, each preset also tells Frigate what hardware is available so it can offload additional work to the GPU, for example, encoding the Birdseye restream or scaling a stream whose resolution differs from the camera's native size.

-| Preset                | Usage                          | Other Notes                                           |
-| --------------------- | ------------------------------ | ----------------------------------------------------- |
-| preset-rpi-64-h264    | 64 bit Rpi with h264 stream    |                                                       |
-| preset-rpi-64-h265    | 64 bit Rpi with h265 stream    |                                                       |
-| preset-vaapi          | Intel & AMD VAAPI              | Check hwaccel docs to ensure correct driver is chosen |
-| preset-intel-qsv-h264 | Intel QSV with h264 stream     | If issues occur recommend using vaapi preset instead  |
-| preset-intel-qsv-h265 | Intel QSV with h265 stream     | If issues occur recommend using vaapi preset instead  |
-| preset-nvidia         | Nvidia GPU                     |                                                       |
-| preset-jetson-h264    | Nvidia Jetson with h264 stream |                                                       |
-| preset-jetson-h265    | Nvidia Jetson with h265 stream |                                                       |
-| preset-rkmpp          | Rockchip MPP                   | Use image with \*-rk suffix and privileged mode       |
+See [the hardware acceleration docs](/configuration/hardware_acceleration_video.md) for details on setting up hardware acceleration for your GPU / iGPU, then select the preset that matches your hardware.

-Select the appropriate hwaccel preset for your hardware.
+| Preset (YAML config)  | UI Label                | Usage                             | Notes                                                           |
+| --------------------- | ----------------------- | --------------------------------- | --------------------------------------------------------------- |
+| preset-rpi-64-h264    | Raspberry Pi (H.264)    | 64-bit Raspberry Pi, H.264 stream |                                                                 |
+| preset-rpi-64-h265    | Raspberry Pi (H.265)    | 64-bit Raspberry Pi, H.265 stream |                                                                 |
+| preset-vaapi          | VAAPI (Intel/AMD GPU)   | Intel or AMD GPU via VAAPI        | Check the hwaccel docs to ensure the correct driver is selected |
+| preset-intel-qsv-h264 | Intel QuickSync (H.264) | Intel QuickSync, H.264 stream     | If you have issues, use the VAAPI preset instead                |
+| preset-intel-qsv-h265 | Intel QuickSync (H.265) | Intel QuickSync, H.265 stream     | If you have issues, use the VAAPI preset instead                |
+| preset-nvidia         | NVIDIA GPU              | NVIDIA GPU                        |                                                                 |
+| preset-jetson-h264    | NVIDIA Jetson (H.264)   | NVIDIA Jetson, H.264 stream       |                                                                 |
+| preset-jetson-h265    | NVIDIA Jetson (H.265)   | NVIDIA Jetson, H.265 stream       |                                                                 |
+| preset-rkmpp          | Rockchip RKMPP          | Rockchip MPP                      | Use an image with the `-rk` suffix and run in privileged mode   |

 <ConfigTabs>
 <TabItem value="ui">
@@ -53,25 +53,25 @@ cameras:

 ### Input Args Presets

-Input args presets help make the config more readable and handle use cases for different types of streams to ensure maximum compatibility.
+Input arguments are passed to FFmpeg before your camera source and control how Frigate connects to and reads the stream: the transport protocol, timeouts, reconnection behavior, and how the stream is probed. The right input args ensure a reliable connection and maximum compatibility for each type of stream.

-See [the camera specific docs](/configuration/camera_specific.md) for more info on non-standard cameras and recommendations for using them in Frigate.
+See [the camera-specific docs](/configuration/camera_specific.md) for more on non-standard cameras and recommendations for using them in Frigate.

-| Preset                           | Usage                     | Other Notes                                                                                      |
-| -------------------------------- | ------------------------- | ------------------------------------------------------------------------------------------------ |
-| preset-http-jpeg-generic         | HTTP Live Jpeg            | Recommend restreaming live jpeg instead                                                          |
-| preset-http-mjpeg-generic        | HTTP Mjpeg Stream         | Recommend restreaming mjpeg stream instead                                                       |
-| preset-http-reolink              | Reolink HTTP-FLV Stream   | Only for reolink http, not when restreaming as rtsp                                              |
-| preset-rtmp-generic              | RTMP Stream               |                                                                                                  |
-| preset-rtsp-generic              | RTSP Stream               | This is the default when nothing is specified                                                    |
-| preset-rtsp-restream             | RTSP Stream from restream | Use for rtsp restream as source for frigate                                                      |
-| preset-rtsp-restream-low-latency | RTSP Stream from restream | Use for rtsp restream as source for frigate to lower latency, may cause issues with some cameras |
-| preset-rtsp-udp                  | RTSP Stream via UDP       | Use when camera is UDP only                                                                      |
-| preset-rtsp-blue-iris            | Blue Iris RTSP Stream     | Use when consuming a stream from Blue Iris                                                       |
+| Preset (config)                  | UI Label                                  | Usage                       | Notes                                                                           |
+| -------------------------------- | ----------------------------------------- | --------------------------- | ------------------------------------------------------------------------------- |
+| preset-http-jpeg-generic         | HTTP JPEG (Generic)                       | HTTP live JPEG              | Restreaming the live JPEG is recommended instead                                |
+| preset-http-mjpeg-generic        | HTTP MJPEG (Generic)                      | HTTP MJPEG stream           | Restreaming the MJPEG stream is recommended instead                             |
+| preset-http-reolink              | HTTP - Reolink Cameras                    | Reolink HTTP-FLV stream     | Only for Reolink HTTP, not when restreaming as RTSP                             |
+| preset-rtmp-generic              | RTMP (Generic)                            | RTMP stream                 |                                                                                 |
+| preset-rtsp-generic              | RTSP (Generic)                            | RTSP stream                 | The default when no input args are specified                                    |
+| preset-rtsp-restream             | RTSP - Restream from go2rtc               | RTSP stream from a restream | Use when a go2rtc restream is the source for Frigate                            |
+| preset-rtsp-restream-low-latency | RTSP - Restream from go2rtc (Low Latency) | RTSP stream from a restream | Lowers latency for a go2rtc restream source; may cause issues with some cameras |
+| preset-rtsp-udp                  | RTSP - UDP                                | RTSP stream over UDP        | Use when the camera only supports UDP                                           |
+| preset-rtsp-blue-iris            | RTSP - Blue Iris                          | Blue Iris RTSP stream       | Use when consuming a stream from Blue Iris                                      |

 :::warning

-It is important to be mindful of input args when using restream because you can have a mix of protocols. `http` and `rtmp` presets cannot be used with `rtsp` streams. For example, when using a reolink cam with the rtsp restream as a source for record the preset-http-reolink will cause a crash. In this case presets will need to be set at the stream level. See the example below.
+Be mindful of input arguments when restreaming, because you can end up with a mix of protocols. The `http` and `rtmp` presets cannot be used with `rtsp` streams. For example, using a Reolink camera with an RTSP restream as the recording source while `preset-http-reolink` is applied will cause a crash. In cases like this, set the preset at the stream level instead. See the example below.

 :::

@@ -96,13 +96,15 @@ cameras:

 ### Output Args Presets

-Output args presets help make the config more readable and handle use cases for different types of streams to ensure consistent recordings.
+Output arguments are passed to FFmpeg after your camera source and control how recordings are written: which codecs are used and whether audio and video are copied as-is or re-encoded. The right output args ensure consistent, playable recordings for each type of stream.

-| Preset                           | Usage                             | Other Notes                                                                                                                                                                                              |
-| -------------------------------- | --------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| preset-record-generic            | Record WITHOUT audio              | If your camera doesn't have audio, or if you don't want to record audio, use this option                                                                                                                 |
-| preset-record-generic-audio-copy | Record WITH original audio        | Use this to enable audio in recordings                                                                                                                                                                   |
-| preset-record-generic-audio-aac  | Record WITH transcoded aac audio  | This is the default when no option is specified. Use it to transcode audio to AAC. If the source is already in AAC format, use preset-record-generic-audio-copy instead to avoid unnecessary re-encoding |
-| preset-record-mjpeg              | Record an mjpeg stream            | Recommend restreaming mjpeg stream instead                                                                                                                                                               |
-| preset-record-jpeg               | Record live jpeg                  | Recommend restreaming live jpeg instead                                                                                                                                                                  |
-| preset-record-ubiquiti           | Record ubiquiti stream with audio | Recordings with ubiquiti non-standard audio                                                                                                                                                              |
+| Preset (config)                  | UI Label                        | Usage                               | Notes                                                                                                                                                             |
+| -------------------------------- | ------------------------------- | ----------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| preset-record-generic            | Record (Generic, no audio)      | Record without audio                | Use this if your camera has no audio, or if you don't want to record audio                                                                                        |
+| preset-record-generic-audio-copy | Record (Generic + Copy Audio)   | Record with the original audio      | Use this to keep the camera's audio in recordings without re-encoding                                                                                             |
+| preset-record-generic-audio-aac  | Record (Generic + Audio to AAC) | Record with audio transcoded to AAC | The default when no output args are specified. Transcodes audio to AAC. If the source is already AAC, use `preset-record-generic-audio-copy` to avoid re-encoding |
+| preset-record-mjpeg              | Record - MJPEG Cameras          | Record an MJPEG stream              | Restreaming the MJPEG stream is recommended instead                                                                                                               |
+| preset-record-jpeg               | Record - JPEG Cameras           | Record a live JPEG                  | Restreaming the live JPEG is recommended instead                                                                                                                  |
+| preset-record-ubiquiti           | Record - Ubiquiti Cameras       | Record a Ubiquiti stream with audio | Handles Ubiquiti's non-standard audio format                                                                                                                      |
+
+These presets apply to the `record` output args. If [sub stream recording](/configuration/record#sub-stream-recording) is enabled, the same args are used for the `record_sub` role unless `output_args.record_sub` is set, which accepts the same presets and manual args.
@@ -6,12 +6,46 @@ title: Configuring Generative AI
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 ## Configuration

-A Generative AI provider can be configured in the global config, which will make the Generative AI features available for use. There are currently 4 native providers available to integrate with Frigate. Other providers that support the OpenAI standard API can also be used. See the OpenAI-Compatible section below.
+A Generative AI provider can be configured in the global config, which will make the Generative AI features available for use. There are currently 5 native providers available to integrate with Frigate. Other providers that support the OpenAI standard API can also be used. See the OpenAI-Compatible section below.

-To use Generative AI, you must define a single provider at the global level of your Frigate configuration. If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.
+`genai` is a map of named providers. Each key under `genai` is a name you choose, and its value is that provider's settings:
+
+<ConfigTabs>
+<TabItem value="ui">
+
+1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
+   - Click **Add** and enter a **Provider name**. Any name of letters, numbers, hyphens, and underscores is accepted, but it cannot be changed from the UI after the provider is created.
+   - Set **Provider** to the service you are using (e.g., `ollama`)
+   - Set **Base URL**, **API key**, and **Model** as required by that provider
+   - Set **Roles** to the roles this provider should handle.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+genai:
+  my_provider: # any name you like
+    provider: ollama
+    base_url: http://localhost:11434
+    model: qwen3-vl:4b
+    roles:
+      - descriptions
+      - embeddings
+      - chat
+```
+
+</TabItem>
+</ConfigTabs>
+
+The examples on this page all use `my_provider`, but the name is arbitrary and is only used to reference the provider elsewhere in the config (for example, `semantic_search.model`).
+
+Each provider handles one or more **roles**: `chat`, `descriptions`, and `embeddings`. A provider handles all three by default, and each role may be assigned to exactly one provider. Define a single provider if you want it to do everything, or split the roles across several providers using the `roles` option.
+
+If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.

 ## Local Providers

@@ -25,15 +59,23 @@ Running Generative AI models on CPU is not recommended, as high inference times

 ### Recommended Local Models

-You must use a vision-capable model with Frigate. The following models are recommended for local deployment:
+#### Vision models

-| Model         | Notes                                                                                                                                                                |
-| ------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `qwen3-vl`    | Strong visual and situational understanding, enhanced ability to identify smaller objects and interactions with object.                                              |
-| `qwen3.5`     | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
-| `gemma4`      | Strong situational understanding, sometimes resorts to more vague terms like 'interacts' instead of assigning a specific action.                                     |
-| `Intern3.5VL` | Relatively fast with good vision comprehension                                                                                                                       |
-| `gemma3`      | Slower model with good vision and temporal understanding                                                                                                             |
+You must use a vision-capable model with Frigate. The following models are recommended for local deployment of the `descriptions` and `chat` roles:
+
+| Model               | Notes                                                                                                                                                                |
+| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `qwen3-vl`          | Strong visual and situational understanding, enhanced ability to identify smaller objects and interactions with object.                                              |
+| `qwen3.6`/`qwen3.8` | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
+| `gemma4`            | Strong situational understanding, sometimes resorts to more vague terms like 'interacts' instead of assigning a specific action.                                     |
+
+#### Embedding models
+
+The `embeddings` role needs a different kind of model. Text queries are matched against the stored image embeddings, so the model must be trained to place images and text into the same vector space. A chat or description model will still return vectors when asked, but those vectors are not trained for retrieval and text searches will return poor matches with no error to indicate why.
+
+| Model                | Notes                                                                                                                                                               |
+| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Must be served by llama.cpp started with `--embeddings` and `--mmproj`. |

 :::info

@@ -56,7 +98,7 @@ Frigate manages reasoning per task automatically:
 - **Description tasks** (object descriptions, review descriptions, review summaries) are synthesis-only and benefit from concise, direct output, so Frigate disables thinking for these calls when the model exposes a per-request toggle.
 - **Chat** lets you toggle thinking on or off from the composer when the configured model supports it.

-You can use a pure instruct, hybrid, or thinking-capable model with Frigate — no extra configuration is required to disable thinking for descriptions.
+You can use a pure instruct, hybrid, or thinking-capable model with Frigate. No extra configuration is required to disable thinking for descriptions.

 ### llama.cpp

@@ -79,23 +121,26 @@ All llama.cpp native options can be passed through `provider_options`, including
   - Set **Provider** to `llamacpp`
   - Set **Base URL** to your llama.cpp server address (e.g., `http://localhost:8080`)
   - Set **Model** to the name of your model
-   - Under **Provider Options**, set `context_size` to tell Frigate your context size so it can send the appropriate amount of information
+   - Optionally, under **Provider Options**, set `context_size` to override the context size Frigate detects from the server

 </TabItem>
 <TabItem value="yaml">

 ```yaml
 genai:
-  provider: llamacpp
-  base_url: http://localhost:8080
-  model: your-model-name
-  provider_options:
-    context_size: 16000 # Tell Frigate your context size so it can send the appropriate amount of information.
+  my_provider:
+    provider: llamacpp
+    base_url: http://localhost:8080
+    model: your-model-name
+    provider_options:
+      context_size: 16000 # Optional, overrides the context size reported by the server.
 ```

 </TabItem>
 </ConfigTabs>

+Frigate queries the llama.cpp server for the model's context size at startup and logs it along with the other detected capabilities. If `context_size` is set in `provider_options`, that value is always used instead, even when the server reports its own.
+
 ### Ollama

 [Ollama](https://ollama.com/) allows you to self-host large language models and keep everything running locally. It is highly recommended to host this server on a machine with an Nvidia graphics card, or on a Apple silicon Mac for best performance.
@@ -128,13 +173,14 @@ Note that Frigate will not automatically download the model you specify in your

 ```yaml
 genai:
-  provider: ollama
-  base_url: http://localhost:11434
-  model: qwen3-vl:4b
-  provider_options: # other Ollama client options can be defined
-    keep_alive: -1
-    options:
-      num_ctx: 8192 # make sure the context matches other services that are using ollama
+  my_provider:
+    provider: ollama
+    base_url: http://localhost:11434
+    model: qwen3-vl:4b
+    provider_options: # other Ollama client options can be defined
+      keep_alive: -1
+      options:
+        num_ctx: 8192 # make sure the context matches other services that are using ollama
 ```

 </TabItem>
@@ -150,11 +196,12 @@ For OpenAI-compatible servers (such as llama.cpp) that don't expose the configur

 ```yaml
 genai:
-  provider: openai
-  base_url: http://your-llama-server
-  model: your-model-name
-  provider_options:
-    context_size: 8192 # Specify the configured context size
+  my_provider:
+    provider: openai
+    base_url: http://your-llama-server
+    model: your-model-name
+    provider_options:
+      context_size: 8192 # Specify the configured context size
 ```

 This ensures Frigate uses the correct context window size when generating prompts.
@@ -177,10 +224,11 @@ This ensures Frigate uses the correct context window size when generating prompt

 ```yaml
 genai:
-  provider: openai
-  base_url: http://your-server:port
-  api_key: your-api-key # May not be required for local servers
-  model: your-model-name
+  my_provider:
+    provider: openai
+    base_url: http://your-server:port
+    api_key: your-api-key # May not be required for local servers
+    model: your-model-name
 ```

 </TabItem>
@@ -218,19 +266,21 @@ Ollama also supports [cloud models](https://ollama.com/cloud), where model infer

 ```yaml
 genai:
-  provider: ollama
-  base_url: http://localhost:11434
-  model: cloud-model-name
+  my_provider:
+    provider: ollama
+    base_url: http://localhost:11434
+    model: cloud-model-name
 ```

 or when using Ollama Cloud directly

 ```yaml
 genai:
-  provider: ollama
-  base_url: https://ollama.com
-  model: cloud-model-name
-  api_key: your-api-key
+  my_provider:
+    provider: ollama
+    base_url: https://ollama.com
+    model: cloud-model-name
+    api_key: your-api-key
 ```

 </TabItem>
@@ -268,9 +318,10 @@ To start using Gemini, you must first get an API key from [Google AI Studio](htt

 ```yaml
 genai:
-  provider: gemini
-  api_key: "{FRIGATE_GEMINI_API_KEY}"
-  model: gemini-2.5-flash
+  my_provider:
+    provider: gemini
+    api_key: "{FRIGATE_GEMINI_API_KEY}"
+    model: gemini-2.5-flash
 ```

 </TabItem>
@@ -280,12 +331,13 @@ genai:

 To use a different Gemini-compatible API endpoint, set the `provider_options` with the `base_url` key to your provider's API URL. For example:

-```yaml {4,5}
+```yaml {5,6}
 genai:
-  provider: gemini
-  ...
-  provider_options:
-    base_url: https://...
+  my_provider:
+    provider: gemini
+    ...
+    provider_options:
+      base_url: https://...
 ```

 Other HTTP options are available, see the [python-genai documentation](https://github.com/googleapis/python-genai).
@@ -294,7 +346,7 @@ Other HTTP options are available, see the [python-genai documentation](https://g

 ### OpenAI

-OpenAI does not have a free tier for their API. With the release of gpt-4o, pricing has been reduced and each generation should cost fractions of a cent if you choose to go this route.
+OpenAI does not have a free tier for their API.

 #### Supported Models

@@ -319,9 +371,10 @@ To start using OpenAI, you must first [create an API key](https://platform.opena

 ```yaml
 genai:
-  provider: openai
-  api_key: "{FRIGATE_OPENAI_API_KEY}"
-  model: gpt-4o
+  my_provider:
+    provider: openai
+    api_key: "{FRIGATE_OPENAI_API_KEY}"
+    model: gpt-4o
 ```

 </TabItem>
@@ -337,13 +390,14 @@ To use a different OpenAI-compatible API endpoint, set the `OPENAI_BASE_URL` env

 For OpenAI-compatible servers (such as llama.cpp) that don't expose the configured context size in the API response, you can manually specify the context size in `provider_options`:

-```yaml {5,6}
+```yaml {6,7}
 genai:
-  provider: openai
-  base_url: http://your-llama-server
-  model: your-model-name
-  provider_options:
-    context_size: 8192 # Specify the configured context size
+  my_provider:
+    provider: openai
+    base_url: http://your-llama-server
+    model: your-model-name
+    provider_options:
+      context_size: 8192 # Specify the configured context size
 ```

 This ensures Frigate uses the correct context window size when generating prompts.
@@ -378,11 +432,91 @@ To start using Azure OpenAI, you must first [create a resource](https://learn.mi

 ```yaml
 genai:
-  provider: azure_openai
-  base_url: https://instance.cognitiveservices.azure.com/openai/responses?api-version=2025-04-01-preview
-  model: gpt-5-mini
-  api_key: "{FRIGATE_OPENAI_API_KEY}"
+  my_provider:
+    provider: azure_openai
+    base_url: https://instance.cognitiveservices.azure.com/openai/responses?api-version=2025-04-01-preview
+    model: gpt-5-mini
+    api_key: "{FRIGATE_OPENAI_API_KEY}"
 ```

 </TabItem>
 </ConfigTabs>
+
+## FAQ
+
+<FaqItem id="how-do-i-debug-genai-issues" question="How do I debug GenAI issues?">
+
+Frigate's Generative AI features are configured and enabled separately. [Review descriptions and summaries](/configuration/genai/genai_review) live under `review.genai`, and [object descriptions](/configuration/genai/genai_objects) live under `objects.genai`. Configuring a provider on this page does not enable either feature, and enabling one does not enable the other. Decide which of the two is not working, then work through the steps below.
+
+1. Confirm a provider is available and holds the `descriptions` role.
+   - Review descriptions, review summaries, and object descriptions all use the provider that has the `descriptions` role assigned in <NavPath path="Settings > Enrichments > Generative AI > Roles" /> (`genai.<provider>.roles`).
+   - A provider is contacted the first time one of its roles is actually used. A provider holding the `embeddings` role for semantic search is initialized during startup, while a `descriptions` provider is not initialized until the first description is requested, which may be well after boot.
+   - In <NavPath path="Settings > Enrichments > Generative AI" />, use **Refresh models** next to the model field. It queries the provider for its model list and is a quick way to verify that the base URL, API key, and network path between Frigate and your provider are correct.
+
+2. Confirm the feature you expect is actually enabled.
+   - Object descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Objects > GenAI object config > Enable GenAI" /> (`objects.genai.enabled`), either globally or per camera. This is the most common reason custom prompts appear to be ignored while review summaries are still being generated.
+   - Review descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Review > GenAI config > Enable GenAI descriptions" /> (`review.genai.enabled`). Once enabled, alerts are described by default but detections are not, so a detection-only review item will never get a summary unless **Enable GenAI for detections** (`review.genai.detections`) is also on.
+
+3. If object descriptions are never requested, check the filters that skip generation.
+   - <NavPath path="Settings > Global configuration > Objects > GenAI object config > GenAI objects" /> (`objects.genai.objects`) limits generation to specific labels, and **Required zones** (`objects.genai.required_zones`) requires the object to have entered one of those zones. If either is set and does not match, Frigate skips the request silently.
+   - Thumbnails are only collected while an object is moving. Objects that go stationary early contribute fewer frames.
+   - **Use snapshots** (`objects.genai.use_snapshot`) requires snapshots to be enabled for the camera. If the snapshot cannot be read, Frigate logs `Cannot load snapshot for <id>, file not found` and no description is generated.
+   - **Send on end** (`objects.genai.send_triggers.tracked_object_end`) is on by default. If you have turned it off in favor of **Early GenAI trigger** (`objects.genai.send_triggers.after_significant_updates`), descriptions are only requested once that number of updates is reached.
+
+4. Enable debug logs to see exactly what Frigate is doing. Restart Frigate after this change. The next step also requires a restart, so turn both on at the same time to avoid restarting twice.
+
+   ```yaml
+   logger:
+     default: info
+     logs:
+       # highlight-start
+       frigate.genai: debug
+       frigate.data_processing.post.object_descriptions: debug
+       frigate.data_processing.post.review_descriptions: debug
+       # highlight-end
+   ```
+
+5. Save the exact images and prompts that were sent to your provider.
+   - Turn on **Save thumbnails** for the feature you are debugging (`review.genai.debug_save_thumbnails` or `objects.genai.debug_save_thumbnails`). Both features write to `/media/frigate/clips/genai-requests/`, and these files are admin-only.
+   - Review descriptions write `genai-requests/<review_id>/` containing the numbered frames that were sent, plus `prompt.txt` and `response.txt` with the exact prompt and the raw, unparsed model response.
+   - Review summary reports write `genai-requests/<start_ts>-<end_ts>/prompt.txt` and `response.txt`. No images are involved, since a report summarizes existing review descriptions.
+   - Object descriptions write `genai-requests/<event_id>/` containing the numbered thumbnails. The prompt for object descriptions is not written to a file, it is only visible in the debug logs from step 4.
+   - Look at the saved images before blaming the model. If the object is small, blurry, or out of frame, no prompt will fix the result. For object descriptions, consider turning on **Use snapshots** (`objects.genai.use_snapshot`) to send a higher quality image. For review items, consider setting **Review image source** (`review.genai.image_source`) to `recordings` for 480p frames instead of the lower resolution preview frames.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+For review descriptions, navigate to <NavPath path="Settings > Global configuration > Review" /> and set **GenAI config > Save thumbnails** to on.
+
+For object descriptions, navigate to <NavPath path="Settings > Global configuration > Objects" />, expand **GenAI object config**, and set **Save thumbnails** to on.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+review:
+  genai:
+    enabled: true
+    # highlight-next-line
+    debug_save_thumbnails: true
+
+objects:
+  genai:
+    enabled: true
+    # highlight-next-line
+    debug_save_thumbnails: true
+```
+
+</TabItem>
+</ConfigTabs>
+
+6. Verify the prompt is what you think it is.
+   - Object description prompts are the ones you control directly. A camera-level <NavPath path="Settings > Camera configuration > Objects > GenAI object config > Caption prompt" /> (`objects.genai.prompt`) overrides the global one, and an entry in **Object prompts** (`objects.genai.object_prompts`) for a label overrides both for that label. Only `{label}`, `{sub_label}`, and `{camera}` are substituted.
+   - Review description prompts are built by Frigate and request a structured JSON response, so they are not fully replaceable. The parts you control are <NavPath path="Settings > Global configuration > Review > GenAI config > Activity context prompt" /> (`review.genai.activity_context_prompt`) and **Additional concerns** (`review.genai.additional_concerns`). Keep the activity context prompt general, since overly specific rules will sway the model's threat level scoring.
+
+7. If descriptions are generated but the results are poor or inconsistent, look at the model and the context window.
+   - Empty fields, missing `shortSummary` values, or `Failed to parse review description` errors usually mean the model is not following the requested JSON schema. Smaller models struggle with structured output. Try a larger parameter size or one of the [recommended models](#recommended-local-models).
+   - Frigate calculates how many frames to send from the context size the provider reports. If your server reports a different value than it is actually running with, frames will be truncated or the request will fail. Pin the value by adding `context_size` under <NavPath path="Settings > Enrichments > Generative AI > Provider options" /> (`genai.<provider>.provider_options`), and for Ollama also confirm `options.num_ctx` there matches the context you have configured.
+   - Check **Review Description Speed** and **Object Description Speed** in <NavPath path="System metrics > Enrichments" />. If inference takes tens of seconds, requests will queue behind each other and descriptions will appear to stop. For Ollama, review `OLLAMA_NUM_PARALLEL`, `OLLAMA_MAX_QUEUE`, and `OLLAMA_MAX_LOADED_MODELS` so that concurrent requests from Frigate are handled the way you expect.
+
+</FaqItem>
@@ -52,9 +52,10 @@ You can define custom prompts at the global level and per-object type. To config

 ```yaml
 genai:
-  provider: ollama
-  base_url: http://localhost:11434
-  model: qwen3-vl:8b-instruct
+  my_provider:
+    provider: ollama
+    base_url: http://localhost:11434
+    model: qwen3-vl:8b-instruct

 objects:
  genai:
@@ -112,3 +113,7 @@ Many providers also have a public facing chat interface for their models. Downlo
 - OpenAI - [ChatGPT](https://chatgpt.com)
 - Gemini - [Google AI Studio](https://aistudio.google.com)
 - Ollama - [Open WebUI](https://docs.openwebui.com/)
+
+## Troubleshooting
+
+If descriptions are not being generated, or the generated descriptions are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).
@@ -201,3 +201,7 @@ Along with individual review item summaries, Generative AI can also produce a si
 Review reports can be requested via the [API](/integrations/api/generate-review-summary-review-summarize-start-start-ts-end-end-ts-post) by sending a POST request to `/api/review/summarize/start/{start_ts}/end/{end_ts}` with Unix timestamps.

 For Home Assistant users, there is a built-in service (`frigate.review_summarize`) that makes it easy to request review reports as part of automations or scripts. This allows you to automatically generate daily summaries, vacation reports, or custom time period reports based on your specific needs.
+
+## Troubleshooting
+
+If summaries are not being generated, or the generated summaries are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).
@@ -15,7 +15,7 @@ Frigate uses the bundled go2rtc to power a number of key features:

 :::tip[Most users no longer need to configure go2rtc by hand]

-The **camera setup wizard** is the recommended way to add cameras. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />, and the wizard probes your camera and writes its configuration for you — including the go2rtc restream and the live stream mapping — so go2rtc is set up automatically.
+The [**camera setup wizard**](cameras.md#adding-a-camera-with-the-add-camera-wizard) is the recommended way to add cameras. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />, and the wizard probes your camera and writes its configuration for you, including the go2rtc restream and the live stream mapping, so go2rtc is set up automatically.

 This guide is mainly useful if you are **upgrading from an older version and have existing cameras that don't yet use go2rtc**, or if you want to fine-tune a stream by hand (for example, to transcode a codec your browser can't play). The [go2rtc troubleshooting guide](/troubleshooting/go2rtc) applies regardless of how your cameras were added.

@@ -23,9 +23,9 @@ This guide is mainly useful if you are **upgrading from an older version and hav

 ## Adding a go2rtc stream manually

-If you added your cameras with the wizard, go2rtc is already configured — you can skip straight to [troubleshooting](/troubleshooting/go2rtc). The steps below are for upgrading users with existing cameras that aren't using go2rtc yet, or for anyone who prefers to configure a stream by hand.
+If you added your cameras with the wizard, go2rtc is already configured. You can skip straight to [troubleshooting](/troubleshooting/go2rtc). The steps below are for upgrading users with existing cameras that aren't using go2rtc yet, or for anyone who prefers to configure a stream by hand.

-Configure go2rtc to connect to your camera by adding the stream you want to use for live view. Avoid changing any other parts of your config at this step. Note that go2rtc supports [many different stream types](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#module-streams), not just rtsp.
+Configure go2rtc to connect to your camera by adding the stream you want to use for live view. Avoid changing any other parts of your config at this step. Note that go2rtc supports [many different stream types](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#module-streams), not just rtsp.

 :::tip

@@ -63,8 +63,10 @@ After adding this to the config, restart Frigate and try to watch the live strea

 ## Troubleshooting

-If your stream won't play, has no audio, uses excessive CPU, or otherwise misbehaves, see the dedicated [go2rtc troubleshooting guide](/troubleshooting/go2rtc). It walks through how to isolate where the problem is and covers the most common issues — unsupported codecs, H.265/HEVC, audio, WebRTC and two-way talk, hardware-accelerated transcoding with FFmpeg 8, and camera-specific quirks.
+If your stream won't play, has no audio, uses excessive CPU, or otherwise misbehaves, see the dedicated [go2rtc troubleshooting guide](/troubleshooting/go2rtc). It walks through how to isolate where the problem is and covers the most common issues: unsupported codecs, H.265/HEVC, audio, WebRTC and two-way talk, hardware-accelerated transcoding with FFmpeg 8, and camera-specific quirks.

 ## Homekit Configuration

-To add camera streams to Homekit Frigate must be configured in docker to use `host` networking mode. Once that is done, you can use the go2rtc WebUI (accessed via port 1984, which is disabled by default) to share export a camera to Homekit. Any changes made will automatically be saved to `/config/go2rtc_homekit.yml`.
+To export camera streams to HomeKit, Frigate must be configured in docker to use `host` networking mode. HomeKit settings are stored in `/config/go2rtc_homekit.yml` rather than in your Frigate config, and are edited through the go2rtc config editor at `http://<frigate_host>:1984/editor.html`. Pairings are saved back to that file automatically.
+
+See the [HomeKit integration docs](/integrations/homekit) for the full setup, including the video and audio requirements HomeKit places on the stream.
@@ -17,8 +17,6 @@ Some types of hardware acceleration are detected and used automatically, but you
 - Check the logs: A message will either say that hardware acceleration was automatically detected, or there will be a warning that no hardware acceleration was automatically detected
 - If hardware acceleration is specified in the config, verification can be done by ensuring the logs are free from errors. There is no CPU fallback for hardware acceleration.

-:::info
-
 Frigate supports presets for optimal hardware accelerated video decoding:

 **AMD**
@@ -49,14 +47,10 @@ Frigate supports presets for optimal hardware accelerated video decoding:

 Depending on your system, these presets may not be compatible, and you may need to use manual hwaccel args to take advantage of your hardware. More information on hardware accelerated decoding for ffmpeg can be found here: https://trac.ffmpeg.org/wiki/HWAccelIntro

-:::
-
 ## Intel-based CPUs

 Frigate can utilize most Intel integrated GPUs and Arc GPUs to accelerate video decoding.

-:::info
-
 **Recommended hwaccel Preset**

 | CPU Generation     | Intel Driver | Recommended Preset  | Notes                                       |
@@ -68,8 +62,6 @@ Frigate can utilize most Intel integrated GPUs and Arc GPUs to accelerate video
 | Intel Arc A-series | iHD / Xe     | preset-intel-qsv-\* |                                             |
 | Intel Arc B-series | iHD / Xe     | preset-intel-qsv-\* | Requires host kernel 6.12+                  |

-:::
-
 :::note

 The default driver is `iHD`. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `config.yml` for HA App users](advanced/system.md#environment_vars).
@@ -320,8 +312,9 @@ ffmpeg:

 :::note

-If running Frigate through Docker, you either need to run in privileged mode or
-map the `/dev/video*` devices to Frigate. With Docker Compose add:
+If running Frigate through Docker, map the relevant `/dev/video*` devices into
+the container. Running in privileged mode also works but grants far more access
+than needed. With Docker Compose add:

 ```yaml {4-5}
 services:
@@ -485,7 +478,7 @@ Error marking filters as finished
 Restarting ffmpeg...
 ```

-you should try to uprade to FFmpeg 7. This can be done using this config option:
+you should try to upgrade to FFmpeg 7. This can be done using this config option:

 ```yaml
 ffmpeg:
@@ -6,6 +6,7 @@ title: License Plate Recognition (LPR)
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 Frigate can recognize license plates on vehicles and automatically add the detected characters to the `recognized_license_plate` field or a [known](#matching) name as a `sub_label` to tracked objects of type `car` or `motorcycle`. A common use case may be to read the license plates of cars pulling into a driveway or cars passing by on a street.

@@ -283,8 +284,8 @@ Navigate to <NavPath path="Settings > Enrichments > License plate recognition" /
 | Field                          | Description                                                                                           |
 | ------------------------------ | ----------------------------------------------------------------------------------------------------- |
 | **Enable LPR**                 | Set to on                                                                                             |
-| **Minimum plate area**         | Set to `1500` — ignore plates with an area (length x width) smaller than 1500 pixels                  |
-| **Min plate length**           | Set to `4` — only recognize plates with 4 or more characters                                          |
+| **Minimum plate area**         | Set to `1500` to ignore plates with an area (length x width) smaller than 1500 pixels                  |
+| **Min plate length**           | Set to `4` to only recognize plates with 4 or more characters                                          |
 | **Known plates > Wife's Car**  | `ABC-1234`, `ABC-I234` (accounts for potential confusion between the number one and capital letter I) |
 | **Known plates > Johnny**      | `J*N-*234` (matches JHN-1234 and JMN-I234; `*` matches any number of characters)                      |
 | **Known plates > Sally**       | `[S5]LL 1234` (matches both SLL 1234 and 5LL 1234)                                                    |
@@ -473,7 +474,7 @@ Navigate to <NavPath path="Settings > Camera configuration > License plate recog
 | Field                 | Description                                                                      |
 | --------------------- | -------------------------------------------------------------------------------- |
 | **Enable LPR**        | Set to on                                                                        |
-| **Enhancement level** | Set to `3` (optional — enhances the image before trying to recognize characters) |
+| **Enhancement level** | Set to `3` (optional, enhances the image before trying to recognize characters) |

 Navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> and add your camera streams.

@@ -481,7 +482,7 @@ Navigate to <NavPath path="Settings > Camera configuration > Object detection" /

 | Field                       | Description                                                                                                                  |
 | --------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
-| **Enable object detection** | Set to off — disables Frigate's standard object detection pipeline                                                           |
+| **Enable object detection** | Set to off to disable Frigate's standard object detection pipeline                                                           |
 | **Detect FPS**              | Set to `5`. Increase if necessary, though high values may slow down Frigate's enrichments pipeline and use considerable CPU. |
 | **Detect width**            | Set to `1920` (recommended value, but depends on your camera)                                                                |
 | **Detect height**           | Set to `1080` (recommended value, but depends on your camera)                                                                |
@@ -490,7 +491,7 @@ Navigate to <NavPath path="Settings > Camera configuration > Objects" />.

 | Field                | Description                                                                            |
 | -------------------- | -------------------------------------------------------------------------------------- |
-| **Objects to track** | Set to an empty list — required when not using a Frigate+ model for dedicated LPR mode |
+| **Objects to track** | Set to an empty list, required when not using a Frigate+ model for dedicated LPR mode |

 Navigate to <NavPath path="Settings > Camera configuration > Motion detection" />.

@@ -591,7 +592,9 @@ By selecting the appropriate configuration, users can optimize their dedicated L

 ## FAQ

-### Why isn't my license plate being detected and recognized?
+### Detection and Recognition
+
+<FaqItem id="why-isnt-my-license-plate-being-detected-and-recognized" question="Why isn't my license plate being detected and recognized?">

 Ensure that:

@@ -606,29 +609,43 @@ Recognized plates will show as object labels in the debug view and will appear i

 If you are still having issues detecting plates, start with a basic configuration and see the debugging tips below.

-### Can I run LPR without detecting `car` or `motorcycle` objects?
+</FaqItem>
+
+<FaqItem id="can-i-run-lpr-without-detecting-car-or-motorcycle-objects" question={<>Can I run LPR without detecting <code>car</code> or <code>motorcycle</code> objects?</>}>

 In normal LPR mode, Frigate requires a `car` or `motorcycle` to be detected first before recognizing a license plate. If you have a dedicated LPR camera, you can change the camera `type` to `"lpr"` to use the Dedicated LPR Camera algorithm. This comes with important caveats, though. See the [Dedicated LPR Cameras](#dedicated-lpr-cameras) section above.

-### How can I improve detection accuracy?
+</FaqItem>
+
+<FaqItem id="how-can-i-improve-detection-accuracy" question="How can I improve detection accuracy?">

 - Use high-quality cameras with good resolution.
 - Adjust `detection_threshold` and `recognition_threshold` values.
 - Define a `format` regex to filter out invalid detections.

-### Does LPR work at night?
+</FaqItem>
+
+<FaqItem id="does-lpr-work-at-night" question="Does LPR work at night?">

 Yes, but performance depends on camera quality, lighting, and infrared capabilities. Make sure your camera can capture clear images of plates at night.

-### Can I limit LPR to specific zones?
+</FaqItem>
+
+<FaqItem id="can-i-limit-lpr-to-specific-zones" question="Can I limit LPR to specific zones?">

 LPR, like other Frigate enrichments, runs at the camera level rather than the zone level. While you can't restrict LPR to specific zones directly, you can control when recognition runs by setting a `min_area` value to filter out smaller detections.

-### How can I match known plates with minor variations?
+</FaqItem>
+
+<FaqItem id="how-can-i-match-known-plates-with-minor-variations" question="How can I match known plates with minor variations?">

 Use `match_distance` to allow small character mismatches. Alternatively, define multiple variations in `known_plates`.

-### How do I debug LPR issues?
+</FaqItem>
+
+### Performance and Troubleshooting
+
+<FaqItem id="how-do-i-debug-lpr-issues" question="How do I debug LPR issues?">

 Start with ["Why isn't my license plate being detected and recognized?"](#why-isnt-my-license-plate-being-detected-and-recognized). If you are still having issues, work through these steps.

@@ -671,7 +688,7 @@ lpr:
 3. Ensure your plates are being _detected_.

   If you are using a Frigate+ or `license_plate` detecting model:
-   - Watch the debug view (Settings --> Debug) to ensure that `license_plate` is being detected.
+   - Watch the [Debug view](/usage/live#the-single-camera-view) to ensure that `license_plate` is being detected.
   - View MQTT messages for `frigate/events` to verify detected plates.
   - You may need to adjust your `min_score` and/or `threshold` for the `license_plate` object if your plates are not being detected.

@@ -680,21 +697,28 @@ lpr:
   - You may need to adjust your `detection_threshold` if your plates are not being detected.

 4. Ensure the characters on detected plates are being _recognized_.
+   - Check the **Plate recognition** inference time in Enrichment metrics (<NavPath path="System metrics > Enrichments" />). High inference times (> 100ms) could lead to poor recognition results, especially for dedicated LPR cameras where the plate crosses the frame quickly.
   - Enable `debug_save_plates` to save images of detected text on plates to the clips directory (`/media/frigate/clips/lpr`). Ensure these images are readable and the text is clear.
   - Watch the debug view to see plates recognized in real-time. For non-dedicated LPR cameras, the `car` or `motorcycle` label will change to the recognized plate when LPR is enabled and working.
   - Adjust `recognition_threshold` settings per the suggestions [above](#advanced-configuration).

-### Will LPR slow down my system?
+</FaqItem>
+
+<FaqItem id="will-lpr-slow-down-my-system" question="Will LPR slow down my system?">

 LPR's performance impact depends on your hardware. Ensure you have at least 4GB RAM and a capable CPU or GPU for optimal results. If you are running the Dedicated LPR Camera mode, resource usage will be higher compared to users who run a model that natively detects license plates. Tune your motion detection settings for your dedicated LPR camera so that the license plate detection model runs only when necessary.

-### I am seeing a YOLOv9 plate detection metric in Enrichment Metrics, but I have a Frigate+ or custom model that detects `license_plate`. Why is the YOLOv9 model running?
+</FaqItem>
+
+<FaqItem id="i-am-seeing-a-yolov9-plate-detection-metric-in-enrichment-metrics-but-i-have-a-frigate-or-custom-model-that-detects-license_plate-why-is-the-yolov9-model-running" question={<>I am seeing a YOLOv9 plate detection metric in Enrichment Metrics, but I have a Frigate+ or custom model that detects <code>license_plate</code>. Why is the YOLOv9 model running?</>}>

 The YOLOv9 license plate detector model will run (and the metric will appear) if you've enabled LPR but haven't defined `license_plate` as an object to track, either at the global or camera level.

 If you are detecting `car` or `motorcycle` on cameras where you don't want to run LPR, make sure you disable LPR it at the camera level. And if you do want to run LPR on those cameras, make sure you define `license_plate` as an object to track.

-### It looks like Frigate picked up my camera's timestamp or overlay text as the license plate. How can I prevent this?
+</FaqItem>
+
+<FaqItem id="it-looks-like-frigate-picked-up-my-cameras-timestamp-or-overlay-text-as-the-license-plate-how-can-i-prevent-this" question="It looks like Frigate picked up my camera's timestamp or overlay text as the license plate. How can I prevent this?">

 This could happen if cars or motorcycles travel close to your camera's timestamp or overlay text. You could either move the text through your camera's firmware, or apply a mask to it in Frigate.

@@ -702,6 +726,10 @@ If you are using a model that natively detects `license_plate`, add an _object m

 If you are not using a model that natively detects `license_plate` or you are using dedicated LPR camera mode, only a _motion mask_ over your text is required.

-### I see "Error running ... model" in my logs, or my inference time is very high. How can I fix this?
+</FaqItem>
+
+<FaqItem id="i-see-error-running--model-in-my-logs-or-my-inference-time-is-very-high-how-can-i-fix-this" question={'I see "Error running ... model" in my logs, or my inference time is very high. How can I fix this?'}>

 This usually happens when your GPU is unable to compile or use one of the LPR models. Set your `device` to `CPU` and try again. GPU acceleration only provides a slight performance increase, and the models are lightweight enough to run without issue on most CPUs.
+
+</FaqItem>
@@ -6,6 +6,7 @@ title: Live View
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 Frigate intelligently displays your camera streams on the Live view dashboard. By default, Frigate employs "smart streaming" where camera images update once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any motion or active objects are detected, cameras seamlessly switch to a live stream.

@@ -33,7 +34,7 @@ If you are using go2rtc, you should adjust the following settings in your camera

 - Video codec: **H.264** - provides the most compatible video codec with all Live view technologies and browsers. Avoid any kind of "smart codec" or "+" codec like _H.264+_ or _H.265+_. as these non-standard codecs remove keyframes (see below).
 - Audio codec: **AAC** - provides the most compatible audio codec with all Live view technologies and browsers that support audio.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes. For many users this may not be an issue, but it should be noted that a 1x i-frame interval will cause more storage utilization if you are using the stream for the `record` role as well.
+- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://web.archive.org/web/20251213190836/https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes. For many users this may not be an issue, but it should be noted that a 1x i-frame interval will cause more storage utilization if you are using the stream for the `record` role as well.

 The default video and audio codec on your camera may not always be compatible with your browser, which is why setting them to H.264 and AAC is recommended. See the [go2rtc docs](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness) for codec support information.

@@ -195,7 +196,7 @@ services:

 :::

-See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.8.3#module-webrtc) for more information about this.
+See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#module-webrtc) for more information about this.

 ### Two way talk

@@ -271,9 +272,9 @@ cameras:

 Each camera has three possible states, surfaced as a status selector in **Settings → Global configuration → Camera management**:

- **On** — streams are processed normally. Object detection, recording, and Live view are active.
- **Off** — Frigate's ffmpeg processes are paused. Recording stops, object detection is paused, and the Live dashboard displays a blank image with a "Camera is off" message. The camera is still visible in the Live dashboard and its past review items, tracked objects, and historical footage remain accessible via the UI. The Off state persists across Frigate restarts via a `.runtime_state.json` file alongside `config.yml` (see [Runtime toggle persistence](#runtime-toggle-persistence)).
- **Disabled** — the change is saved to your configuration file (`enabled: False`). The camera stops immediately, Frigate stops ffmpeg processes, and all live and historical UI elements for the camera are no longer visible but remains retained on disk. The camera is still listed in **Settings → Global configuration → Camera management** so it can be re-enabled. **A restart of Frigate is required to bring a disabled camera back to On.**
+- **On**: streams are processed normally. Object detection, recording, and Live view are active.
+- **Off**: Frigate's ffmpeg processes are paused. Recording stops, object detection is paused, and the Live dashboard displays a blank image with a "Camera is off" message. The camera is still visible in the Live dashboard and its past review items, tracked objects, and historical footage remain accessible via the UI. The Off state persists across Frigate restarts via a `.runtime_state.json` file alongside `config.yml` (see [Runtime toggle persistence](#runtime-toggle-persistence)).
+- **Disabled**: the change is saved to your configuration file (`enabled: False`). The camera stops immediately, Frigate stops ffmpeg processes, and all live and historical UI elements for the camera are no longer visible but remains retained on disk. The camera is still listed in **Settings → Global configuration → Camera management** so it can be re-enabled. **A restart of Frigate is required to bring a disabled camera back to On.**

 #### Turning a camera on or off

@@ -302,7 +303,7 @@ If you want a camera's historical data (review items, tracked objects, footage)

 #### Runtime toggle persistence

-The Live view toggles for **camera on/off**, **detect**, **recordings**, **snapshots**, and **audio detection** — along with the equivalent MQTT `/set` topics — write the new state to `.runtime_state.json` next to your `config.yml`. The file is replayed on Frigate startup so your last-known toggle states survive a restart. Two interactions worth knowing:
+The Live view toggles for **camera on/off**, **detect**, **recordings**, **snapshots**, and **audio detection** (along with the equivalent MQTT `/set` topics) write the new state to `.runtime_state.json` next to your `config.yml`. The file is replayed on Frigate startup so your last-known toggle states survive a restart. Two interactions worth knowing:

 - **Settings UI saves win.** When you save a field through **Settings → Global configuration**, the matching entry is cleared from `.runtime_state.json` so the new value in your config file is the durable source.
 - **Switching profiles clears all runtime overrides.** Activating or deactivating a [profile](/configuration/profiles) is treated as a deliberate state change, so the file is wiped to avoid stale overrides replaying on top of the new profile.
@@ -333,7 +334,7 @@ When your browser runs into problems playing back your camera streams, it will l

 - **stalled**
  - What it means: Playback has stalled because the player has fallen too far behind live (extended buffering or no data arriving).
-  - What to try: This is usually indicative of the browser struggling to decode too many high-resolution streams at once. Try selecting a lower-bandwidth stream (substream), reduce the number of live streams open, improve the network connection, or lower the camera resolution. Also check your camera's keyframe (I-frame) interval — shorter intervals make playback start and recover faster. You can also try increasing the timeout value in the UI pane of Frigate's settings.
+  - What to try: This is usually indicative of the browser struggling to decode too many high-resolution streams at once. Try selecting a lower-bandwidth stream (substream), reduce the number of live streams open, improve the network connection, or lower the camera resolution. Also check your camera's keyframe (I-frame) interval: shorter intervals make playback start and recover faster. You can also try increasing the timeout value in <NavPath path="Settings > UI" /> .

  - Possible console messages from the player code:
    - `Buffer time (10 seconds) exceeded, browser may not be playing media correctly.`
@@ -341,96 +342,155 @@ When your browser runs into problems playing back your camera streams, it will l

 ## Live view FAQ

-1. **Why don't I have audio in my Live view?**
+### Getting Live View Working

-   You must use go2rtc to hear audio in your live streams. If you have go2rtc already configured, you need to ensure your camera is sending PCMA/PCMU or AAC audio. If you can't change your camera's audio codec, you need to [transcode the audio](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg) using go2rtc.
+<FaqItem id="why-dont-i-have-audio-in-my-live-view" question="Why don't I have audio in my Live view?">

-   Note that the low bandwidth mode player is a video-only stream. You should not expect to hear audio when in low bandwidth mode, even if you've set up go2rtc.
+You must use go2rtc to hear audio in your live streams. If you have go2rtc already configured, you need to ensure your camera is sending PCMA/PCMU or AAC audio. If you can't change your camera's audio codec, you need to [transcode the audio](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg) using go2rtc.

-2. **Frigate shows that my live stream is in "low bandwidth mode". What does this mean?**
+If the audio controls don't appear in the UI at all, verify that the Live view is actually using your go2rtc stream. If your go2rtc stream names don't match your Frigate camera name, you must map them with the `live -> streams` config (see [Setting Streams For Live UI](#setting-streams-for-live-ui) above); otherwise the UI falls back to the video-only jsmpeg player.

-   Frigate intelligently selects the live streaming technology based on a number of factors (user-selected modes like two-way talk, camera settings, browser capabilities, available bandwidth) and prioritizes showing an actual up-to-date live view of your camera's stream as quickly as possible.
+Note that the low bandwidth mode player is a video-only stream. You should not expect to hear audio when in low bandwidth mode, even if you've set up go2rtc.

-   When you have go2rtc configured, Live view initially attempts to load and play back your stream with a clearer, fluent stream technology (MSE). An initial timeout, a low bandwidth condition that would cause buffering of the stream, or decoding errors in the stream will cause Frigate to switch to the stream defined by the `detect` role, using the jsmpeg format. This is what the UI labels as "low bandwidth mode". On Live dashboards, the mode will automatically reset when smart streaming is configured and activity stops. Continuous streaming mode does not have an automatic reset mechanism, but you can use the _Reset_ option to force a reload of your stream.
+</FaqItem>

-   If you are using continuous streaming or you are loading more than a few high resolution streams at once on the dashboard, your browser may struggle to begin playback of your streams before the timeout. Frigate always prioritizes showing a live stream as quickly as possible, even if it is a lower quality jsmpeg stream. You can use the "Reset" link/button to try loading your high resolution stream again.
+<FaqItem id="i-have-unmuted-some-cameras-on-my-dashboard-but-i-do-not-hear-sound-why" question="I have unmuted some cameras on my dashboard, but I do not hear sound. Why?">

-   Errors in stream playback (e.g., connection failures, codec issues, or buffering timeouts) that cause the fallback to low bandwidth mode (jsmpeg) are logged to the browser console for easier debugging. These errors may include:
-   - Network issues (e.g., MSE or WebRTC network connection problems).
-   - Unsupported codecs or stream formats (e.g., H.265 in WebRTC, which is not supported in some browsers).
-   - Buffering timeouts or low bandwidth conditions causing fallback to jsmpeg.
-   - Browser compatibility problems (e.g., iOS Safari limitations with MSE).
+If your camera is streaming (as indicated by a red dot in the upper right, or if it has been set to continuous streaming mode), your browser may be blocking audio until you interact with the page. This is an intentional browser limitation. See [this article](https://developer.mozilla.org/en-US/docs/Web/Media/Autoplay_guide#autoplay_availability). Many browsers have a whitelist feature to change this behavior.

-   To view browser console logs:
-   1. Open the Frigate Live View in your browser.
-   2. Open the browser's Developer Tools (F12 or right-click > Inspect > Console tab).
-   3. Reproduce the error (e.g., load a problematic stream or simulate network issues).
-   4. Look for messages prefixed with the camera name.
+</FaqItem>

-   These logs help identify if the issue is player-specific (MSE vs. WebRTC) or related to camera configuration (e.g., go2rtc streams, codecs). If you see frequent errors:
-   - Verify your camera's H.264/AAC settings (see [Frigate's camera settings recommendations](#camera-settings-recommendations)).
-   - Check go2rtc configuration for transcoding (e.g., audio to AAC/OPUS).
-   - Test with a different stream via the UI dropdown (if `live -> streams` is configured).
-   - For WebRTC-specific issues, ensure port 8555 is forwarded and candidates are set (see [WebRTC Extra Configuration](#webrtc-extra-configuration)).
-   - If your cameras are streaming at a high resolution, your browser may be struggling to load all of the streams before the buffering timeout occurs. Frigate prioritizes showing a true live view as quickly as possible. If the fallback occurs often, change your live view settings to use a lower bandwidth substream.
+<FaqItem id="my-live-view-shows-a-black-screen-or-doesnt-load-but-the-debug-view-works-why" question="My live view shows a black screen or doesn't load, but the debug view works. Why?">

-3. **It doesn't seem like my cameras are streaming on the Live dashboard. Why?**
+The debug view plays the `detect` stream processed by Frigate itself, while the Live view plays your go2rtc stream directly in the browser. If the debug view works but the Live view doesn't, your browser usually can't decode what the camera is sending, most often H.265 video or an incompatible audio track.

-   On the default Live dashboard ("All Cameras"), your camera images will update once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any activity is detected, cameras seamlessly switch to a full-resolution live stream. If you want to customize this behavior, use a camera group.
+Work through the [go2rtc troubleshooting guide](/troubleshooting/go2rtc#live-view-is-black-buffering-or-stuck-in-low-bandwidth-mode) to isolate the problem. Two fixes resolve the majority of cases:

-4. **I see a strange diagonal line on my live view, but my recordings look fine. How can I fix it?**
+1. Restream through go2rtc's FFmpeg module by prefixing your source with `ffmpeg:`, for example `- ffmpeg:rtsp://user:password@192.168.1.5:554/stream`.
+2. If that doesn't help, transcode to compatible codecs: `- ffmpeg:rtsp://user:password@192.168.1.5:554/stream#video=h264#audio=aac#hardware`.

-   This is caused by incorrect dimensions set in your detect width or height (or incorrectly auto-detected), causing the jsmpeg player's rendering engine to display a slightly distorted image. You should enlarge the width and height of your `detect` resolution up to a standard aspect ratio (example: 640x352 becomes 640x360, and 800x443 becomes 800x450, 2688x1520 becomes 2688x1512, etc). If changing the resolution to match a standard (4:3, 16:9, or 32:9, etc) aspect ratio does not solve the issue, you can enable "compatibility mode" in your camera group dashboard's stream settings. Depending on your browser and device, more than a few cameras in compatibility mode may not be supported, so only use this option if changing your `detect` width and height fails to resolve the color artifacts and diagonal line.
+</FaqItem>

-5. **How does "smart streaming" work?**
+<FaqItem id="how-do-i-get-the-best-live-view-experience-in-home-assistant" question="How do I get the best live view experience in Home Assistant?">

-   Because a static image of a scene looks exactly the same as a live stream with no motion or activity, smart streaming updates your camera images once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any activity (motion or object/audio detection) occurs, cameras seamlessly switch to a live stream.
+For a full-resolution, low-latency live view in Home Assistant dashboards, use the [Advanced Camera Card](https://card.camera) with the [go2rtc live provider](https://card.camera/#/configuration/cameras/live-provider?id=go2rtc), which streams directly from Frigate's bundled go2rtc. This also supports audio and [two-way talk](#two-way-talk) on capable cameras. See the [Home Assistant integration docs](/integrations/home-assistant) for setup.

-   This static image is pulled from the stream defined in your config with the `detect` role. When activity is detected, images from the `detect` stream immediately begin updating at ~5 frames per second so you can see the activity until the live player is loaded and begins playing. This usually only takes a second or two. If the live player times out, buffers, or has streaming errors, the jsmpeg player is loaded and plays a video-only stream from the `detect` role. When activity ends, the players are destroyed and a static image is displayed until activity is detected again, and the process repeats.
+</FaqItem>

-   Smart streaming depends on having your camera's motion `threshold` and `contour_area` config values dialed in. Use the Motion Tuner in Settings in the UI to tune these values in real-time.
+### Streaming Behavior

-   This is Frigate's default and recommended setting because it results in a significant bandwidth savings, especially for high resolution cameras.
+<FaqItem id="how-does-smart-streaming-work" question={'How does "smart streaming" work?'}>

-6. **I have unmuted some cameras on my dashboard, but I do not hear sound. Why?**
+Because a static image of a scene looks exactly the same as a live stream with no motion or activity, smart streaming updates your camera images once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any activity (motion or object/audio detection) occurs, cameras seamlessly switch to a live stream.

-   If your camera is streaming (as indicated by a red dot in the upper right, or if it has been set to continuous streaming mode), your browser may be blocking audio until you interact with the page. This is an intentional browser limitation. See [this article](https://developer.mozilla.org/en-US/docs/Web/Media/Autoplay_guide#autoplay_availability). Many browsers have a whitelist feature to change this behavior.
+This static image is pulled from the stream defined in your config with the `detect` role. When activity is detected, images from the `detect` stream immediately begin updating at ~5 frames per second so you can see the activity until the live player is loaded and begins playing. This usually only takes a second or two. If the live player times out, buffers, or has streaming errors, the jsmpeg player is loaded and plays a video-only stream from the `detect` role. When activity ends, the players are destroyed and a static image is displayed until activity is detected again, and the process repeats.

-7. **My camera streams have lots of visual artifacts / distortion.**
+Smart streaming depends on having your camera's motion `threshold` and `contour_area` config values dialed in. Use the Motion Tuner in Settings in the UI to tune these values in real-time.

-   Some cameras don't include the hardware to support multiple connections to the high resolution stream, and this can cause unexpected behavior. In this case it is recommended to [restream](./restream.md) the high resolution stream so that it can be used for live view and recordings.
+This is Frigate's default and recommended setting because it results in a significant bandwidth savings, especially for high resolution cameras.

-8. **Why does my camera stream switch aspect ratios on the Live dashboard?**
+</FaqItem>

-   Your camera may change aspect ratios on the dashboard because Frigate uses different streams for different purposes. With go2rtc and Smart Streaming, Frigate shows a static image from the `detect` stream when no activity is present, and switches to the live stream when motion is detected. The camera image will change size if your streams use different aspect ratios.
+<FaqItem id="it-doesnt-seem-like-my-cameras-are-streaming-on-the-live-dashboard-why" question="It doesn't seem like my cameras are streaming on the Live dashboard. Why?">

-   To prevent this, make the `detect` stream match the go2rtc live stream's aspect ratio (resolution does not need to match, just the aspect ratio). You can either adjust the camera's output resolution or set the `width` and `height` values in your config's `detect` section to a resolution with an aspect ratio that matches.
+On the default Live dashboard ("All Cameras"), your camera images will update once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any activity is detected, cameras seamlessly switch to a full-resolution live stream. If you want to customize this behavior, use a camera group.

-   Example: Resolutions from two streams
-   - Mismatched (may cause aspect ratio switching on the dashboard):
-     - Live/go2rtc stream: 1920x1080 (16:9)
-     - Detect stream: 640x352 (~1.82:1, not 16:9)
+</FaqItem>

-   - Matched (prevents switching):
-     - Live/go2rtc stream: 1920x1080 (16:9)
-     - Detect stream: 640x360 (16:9)
+<FaqItem id="frigate-shows-that-my-live-stream-is-in-low-bandwidth-mode-what-does-this-mean" question={'Frigate shows that my live stream is in "low bandwidth mode". What does this mean?'}>

-   You can update the detect settings in your camera config to match the aspect ratio of your go2rtc live stream. For example:
+Frigate intelligently selects the live streaming technology based on a number of factors (user-selected modes like two-way talk, camera settings, browser capabilities, available bandwidth) and prioritizes showing an actual up-to-date live view of your camera's stream as quickly as possible.

-   ```yaml
-   cameras:
-     front_door:
-       detect:
-         width: 640
-         height: 360 # set this to 360 instead of 352
-       ffmpeg:
-         inputs:
-           - path: rtsp://127.0.0.1:8554/front_door # main stream 1920x1080
-             roles:
-               - record
-           - path: rtsp://127.0.0.1:8554/front_door_sub # sub stream 640x352
-             roles:
-               - detect
-   ```
+When you have go2rtc configured, Live view initially attempts to load and play back your stream with a clearer, fluent stream technology (MSE). An initial timeout, a low bandwidth condition that would cause buffering of the stream, or decoding errors in the stream will cause Frigate to switch to the stream defined by the `detect` role, using the jsmpeg format. This is what the UI labels as "low bandwidth mode". On Live dashboards, the mode will automatically reset when smart streaming is configured and activity stops. Continuous streaming mode does not have an automatic reset mechanism, but you can use the _Reset_ option to force a reload of your stream.

-   The same applies to your `record` stream: if its aspect ratio differs from your `detect` stream, your recordings will appear in a different shape than the live view. For consistent framing across live view and recordings, use the same aspect ratio for all of a camera's streams (the resolution can still differ).
+If you are using continuous streaming or you are loading more than a few high resolution streams at once on the dashboard, your browser may struggle to begin playback of your streams before the timeout. Frigate always prioritizes showing a live stream as quickly as possible, even if it is a lower quality jsmpeg stream. You can use the "Reset" link/button to try loading your high resolution stream again.
+
+Errors in stream playback (e.g., connection failures, codec issues, or buffering timeouts) that cause the fallback to low bandwidth mode (jsmpeg) are logged to the browser console for easier debugging. These errors may include:
+
+- Network issues (e.g., MSE or WebRTC network connection problems).
+- Unsupported codecs or stream formats (e.g., H.265 in WebRTC, which is not supported in some browsers).
+- Buffering timeouts or low bandwidth conditions causing fallback to jsmpeg.
+- Browser compatibility problems (e.g., iOS Safari limitations with MSE).
+
+To view browser console logs:
+
+1. Open the Frigate Live View in your browser.
+2. Open the browser's Developer Tools (F12 or right-click > Inspect > Console tab).
+3. Reproduce the error (e.g., load a problematic stream or simulate network issues).
+4. Look for messages prefixed with the camera name.
+
+These logs help identify if the issue is player-specific (MSE vs. WebRTC) or related to camera configuration (e.g., go2rtc streams, codecs). If you see frequent errors:
+
+- Verify your camera's H.264/AAC settings (see [Frigate's camera settings recommendations](#camera-settings-recommendations)).
+- Check go2rtc configuration for transcoding (e.g., audio to AAC/OPUS).
+- Test with a different stream via the UI dropdown (if `live -> streams` is configured).
+- For WebRTC-specific issues, ensure port 8555 is forwarded and candidates are set (see [WebRTC Extra Configuration](#webrtc-extra-configuration)).
+- If your cameras are streaming at a high resolution, your browser may be struggling to load all of the streams before the buffering timeout occurs. Frigate prioritizes showing a true live view as quickly as possible. If the fallback occurs often, change your live view settings to use a lower bandwidth substream.
+
+</FaqItem>
+
+<FaqItem id="why-is-my-live-view-delayed-or-lagging-behind-real-time" question="Why is my live view delayed or lagging behind real time?">
+
+A delay when a stream first starts is usually caused by your camera's I-frame (keyframe) interval. Playback cannot begin until a keyframe arrives, so an interval set higher than your camera's frame rate makes the stream take longer to start. Set the I-frame interval to match the frame rate (or "1x" on Reolink) per the [camera settings recommendations](#camera-settings-recommendations).
+
+A stream that starts on time but falls further behind live is buffering, which is usually the browser struggling to decode too many high-resolution streams at once. Select a lower-bandwidth substream for your dashboards (see [Setting Streams For Live UI](#setting-streams-for-live-ui)), reduce the number of streams open at once, or improve the network connection between your browser and Frigate. Frigate's player automatically speeds up playback to catch up to live after buffering, and falls back to low bandwidth mode if it stalls for too long. The _Reset_ option forces a fresh connection at the live edge.
+
+</FaqItem>
+
+<FaqItem id="why-does-frigate-prefer-mse-over-webrtc-for-live-view" question="Why does Frigate prefer MSE over WebRTC for live view?">
+
+Frigate prefers MSE because it delivers a better out-of-the-box experience than WebRTC on nearly every axis that matters for a security camera system. MSE is an open standard optimized and supported by all modern browsers, works without any extra configuration (WebRTC requires port forwarding and candidate setup, and lacks H.265 support in some browsers), and requires no internet access for NAT traversal. More importantly, MSE runs over TCP, so every frame arrives and is decoded in order, so nothing is ever silently skipped. WebRTC optimizes for latency over UDP by discarding late or incomplete frames, which works against you on cellular or spotty Wi-Fi: you can end up with frozen video, visual corruption, or gaps in the feed without ever knowing you missed something. Frigate's enhanced MSE player has adaptive speed playback and has been tuned for latency and connection robustness that meets or exceeds WebRTC, so you get near-real-time playback with a guarantee that when the video plays, every frame is actually there - which, for an NVR whose whole purpose is letting you see what happened, matters more than shaving fractions of a second off a latency number. That's why Frigate defaults to MSE and reserves WebRTC for cases that require it, like two-way talk.
+
+</FaqItem>
+
+### Video Quality Issues
+
+<FaqItem id="i-see-a-strange-diagonal-line-on-my-live-view-but-my-recordings-look-fine-how-can-i-fix-it" question="I see a strange diagonal line on my live view, but my recordings look fine. How can I fix it?">
+
+This is caused by incorrect dimensions set in your detect width or height (or incorrectly auto-detected), causing the jsmpeg player's rendering engine to display a slightly distorted image. You should enlarge the width and height of your `detect` resolution up to a standard aspect ratio (example: 640x352 becomes 640x360, and 800x443 becomes 800x450, 2688x1520 becomes 2688x1512, etc). If changing the resolution to match a standard (4:3, 16:9, or 32:9, etc) aspect ratio does not solve the issue, you can enable "compatibility mode" in your camera group dashboard's stream settings. Depending on your browser and device, more than a few cameras in compatibility mode may not be supported, so only use this option if changing your `detect` width and height fails to resolve the color artifacts and diagonal line.
+
+</FaqItem>
+
+<FaqItem id="my-camera-streams-have-lots-of-visual-artifacts-or-distortion" question="My camera streams have lots of visual artifacts / distortion.">
+
+Some cameras don't include the hardware to support multiple connections to the high resolution stream, and this can cause unexpected behavior. In this case it is recommended to [restream](./restream.md) the high resolution stream so that it can be used for live view and recordings.
+
+</FaqItem>
+
+<FaqItem id="why-does-my-camera-stream-switch-aspect-ratios-on-the-live-dashboard" question="Why does my camera stream switch aspect ratios on the Live dashboard?">
+
+Your camera may change aspect ratios on the dashboard because Frigate uses different streams for different purposes. With go2rtc and Smart Streaming, Frigate shows a static image from the `detect` stream when no activity is present, and switches to the live stream when motion is detected. The camera image will change size if your streams use different aspect ratios.
+
+To prevent this, make the `detect` stream match the go2rtc live stream's aspect ratio (resolution does not need to match, just the aspect ratio). You can either adjust the camera's output resolution or set the `width` and `height` values in your config's `detect` section to a resolution with an aspect ratio that matches.
+
+Example: Resolutions from two streams
+
+- Mismatched (may cause aspect ratio switching on the dashboard):
+  - Live/go2rtc stream: 1920x1080 (16:9)
+  - Detect stream: 640x352 (~1.82:1, not 16:9)
+
+- Matched (prevents switching):
+  - Live/go2rtc stream: 1920x1080 (16:9)
+  - Detect stream: 640x360 (16:9)
+
+You can update the detect settings in your camera config to match the aspect ratio of your go2rtc live stream. For example:
+
+```yaml
+cameras:
+  front_door:
+    detect:
+      width: 640
+      height: 360 # set this to 360 instead of 352
+    ffmpeg:
+      inputs:
+        - path: rtsp://127.0.0.1:8554/front_door # main stream 1920x1080
+          roles:
+            - record
+        - path: rtsp://127.0.0.1:8554/front_door_sub # sub stream 640x352
+          roles:
+            - detect
+```
+
+The same applies to your `record` stream: if its aspect ratio differs from your `detect` stream, your recordings will appear in a different shape than the live view. For consistent framing across live view and recordings, use the same aspect ratio for all of a camera's streams (the resolution can still differ).
+
+</FaqItem>
@@ -7,9 +7,11 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

+Frigate has two kinds of masks: motion masks and object filter masks. Both are narrow tools for fine-tuning, **not for hiding an area from Frigate**. Masks should be used sparingly; in most cases where users reach for one, a [zone](zones.md) with [`required_zones`](zones.md#restricting-alerts-and-detections-to-specific-zones) is the right tool instead. See [Which tool do I need?](#which-tool-do-i-need) and [Common mistakes](#common-mistakes) below if you're new to Frigate's mask behavior.
+
 ## Motion masks

-Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the Debug feed (Settings --> Debug) with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. _Over-masking will make it more difficult for objects to be tracked._
+Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the [Debug view](/usage/live#the-single-camera-view) with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. _Over-masking will make it more difficult for objects to be tracked._

 See [further clarification](#further-clarification) below on why you may not want to use a motion mask.

@@ -21,7 +23,16 @@ Object filter masks can be used to filter out stubborn false positives in fixed

 ![object mask](/img/bottom-center-mask.jpg)

-## Creating masks
+## Which tool do I need?
+
+| What you're trying to do                                                                                                                                                                  | Recommended tool                                                                                            | How it works                                                                                                                                                                                |
+| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Only get alerts/detections for activity in the areas you care about, ignoring activity elsewhere (e.g., alert when someone enters your yard, but not when they walk past on the sidewalk) | A [zone](zones.md) combined with [`required_zones`](zones.md#restricting-alerts-and-detections-to-specific-zones) | Frigate keeps detecting and tracking activity everywhere in the frame, but a review item is only created once the bottom-center of an object's bounding box enters a required zone. |
+| Stop a stubborn false positive at a specific fixed spot (e.g., a tree base that keeps being detected as a person)                                                                         | An **object filter mask** for that object type                                                              | Any detection of that object type whose bounding-box bottom-center lands inside the mask is treated as a false positive and discarded.                                                      |
+| Ignore motion in an area that obviously isn't an object of interest (e.g., the camera timestamp, sky, flags, treetops swaying)                                                            | A **motion mask**                                                                                           | Motion inside the mask is ignored when deciding whether to run object detection. Objects can still be detected in a motion masked area if motion elsewhere in the frame triggers detection. |
+| Stop tracking an object type altogether on this camera (e.g., you never care about cats)                                                                                                  | Remove the object from the camera's [`objects.track`](objects.md) list                                      | Frigate skips this object type entirely on this camera, regardless of where it appears.                                                                                                     |
+
+## Using the mask creator

 <ConfigTabs>
 <TabItem value="ui">
@@ -124,3 +135,14 @@ This is what `required_zones` are for. You should define a zone (remember this i
 > Maybe my specific situation just warrants this. I've just been having a hard time understanding the relevance of this information - it seems to be that it's exactly what would be expected when "masking out" an area of ANY image.

 That may be the case for you. Frigate will definitely work harder tracking people on the sidewalk to make sure it doesn't miss anyone who steps foot on your stoop. The trade off with the way you have it now is slower recognition of objects and potential misses. That may be acceptable based on your needs. Also, if your resolution is low enough on the detect stream, your regions may already be so big that they grab the entire object anyway.
+
+## Common mistakes
+
+**"I added a motion mask to ignore my driveway/sidewalk."**
+A motion mask doesn't hide an area from Frigate. Objects can still be detected and tracked inside a masked area. The mask only stops motion _in that area_ from triggering object detection. If you want activity on the sidewalk to never produce a review item, define a [zone](zones.md) over the area you DO care about (your stoop, your driveway) and add it to [`required_zones`](zones.md#restricting-alerts-and-detections-to-specific-zones). Frigate will still see people on the sidewalk, but it won't create an alert until they cross into the zone.
+
+**"I added an object filter mask because I don't care about cars in my yard."**
+Object filter masks are for stubborn false positives at fixed locations, not for filtering whole areas or whole object types. If you only want alerts when a car enters the driveway, use a [zone](zones.md) with [`required_zones`](zones.md#restricting-alerts-and-detections-to-specific-zones). If you don't care about a whole object type on this camera, remove it from [`objects.track`](objects.md).
+
+**"I masked everything except a thin strip on my stoop."**
+Heavy masking hurts tracking. Frigate uses motion near a tracked object's previous bounding box to decide where to look in the next frame; with most of the frame masked, an object walking from an unmasked area into a masked one effectively disappears and gets picked up as a "new" object when it reappears. For example: someone walks down your sidewalk, stops under a tree (masked area) to tie their shoe, then continues. Frigate sees that as two separate people and can create two separate review items. Because Frigate needs several consecutive frames above the confidence threshold to commit to a detection, each re-appearance can also delay or miss alerts. Use [`required_zones`](zones.md#restricting-alerts-and-detections-to-specific-zones) for "only alert me about this spot" and leave the surrounding area unmasked so tracking stays intact.
@@ -59,6 +59,8 @@ Metrics are available at `/api/metrics` by default. No additional Frigate config
 - `frigate_storage_used_bytes{storage=""}` - Storage used bytes
 - `frigate_storage_mount_type{mount_type="", storage=""}` - Storage mount type info

+These gauges report the operating system's figures for the whole filesystem (the same numbers as `df`), not Frigate's own recording footprint. For how this differs from the recordings usage shown in the UI, see [Understanding storage usage](/configuration/record#understanding-storage-usage).
+
 ### Service Metrics

 - `frigate_service_uptime_seconds` - Uptime in seconds
@@ -11,7 +11,7 @@ import NavPath from "@site/src/components/NavPath";

 Frigate uses motion detection as a first line check to see if there is anything happening in the frame worth checking with object detection.

-Once motion is detected, it tries to group up nearby areas of motion together in hopes of identifying a rectangle in the image that will capture the area worth inspecting. These are the red "motion boxes" you see in the debug viewer.
+Once motion is detected, it tries to group up nearby areas of motion together in hopes of identifying a rectangle in the image that will capture the area worth inspecting. These are the red "motion boxes" you see in the [debug viewer](/usage/live#the-single-camera-view).

 ## The Goal

@@ -66,7 +66,7 @@ motion:
 </TabItem>
 </ConfigTabs>

-Lower values mean motion detection is more sensitive to changes in color, making it more likely for example to detect motion when a brown dogs blends in with a brown fence or a person wearing a red shirt blends in with a red car. If the threshold is too low however, it may detect things like grass blowing in the wind, shadows, etc. to be detected as motion.
+Lower values mean motion detection is more sensitive to changes in color, making it more likely for example to detect motion when a brown dog blends in with a brown fence or a person wearing a red shirt blends in with a red car. If the threshold is too low however, it may detect things like grass blowing in the wind, shadows, etc. to be detected as motion.

 Watching the motion boxes in the debug view, increase the threshold until you only see motion that is visible to the eye. Once this is done, it is important to test and ensure that desired motion is still detected.

@@ -151,7 +151,7 @@ motion:

 Large changes in motion like PTZ moves and camera switches between Color and IR mode should result in a pause in object detection. `lightning_threshold` defines the percentage of the image used to detect these substantial changes. Increasing this value makes motion detection more likely to treat large changes (like IR mode switches) as valid motion. Decreasing it makes motion detection more likely to ignore large amounts of motion, such as a person approaching a doorbell camera.

-Note that `lightning_threshold` does **not** stop motion-based recordings from being saved — it only prevents additional motion analysis after the threshold is exceeded, reducing false positive object detections during high-motion periods (e.g. storms or PTZ sweeps) without interfering with recordings.
+Note that `lightning_threshold` does **not** stop motion-based recordings from being saved. It only prevents additional motion analysis after the threshold is exceeded, reducing false positive object detections during high-motion periods (e.g. storms or PTZ sweeps) without interfering with recordings.

 :::warning

@@ -194,10 +194,10 @@ This option is handy when you want to prevent large transient changes from trigg

 :::warning

-When the skip threshold is exceeded, **no motion is reported** for that frame, meaning **nothing is recorded** for that frame. That means you can miss something important, like a PTZ camera auto-tracking an object or activity while the camera is moving. If you prefer to guarantee that every frame is saved, leave this unset and accept occasional recordings containing scene noise — they typically only take up a few megabytes and are quick to scan in the timeline UI.
+When the skip threshold is exceeded, **no motion is reported** for that frame, meaning **nothing is recorded** for that frame. That means you can miss something important, like a PTZ camera auto-tracking an object or activity while the camera is moving. If you prefer to guarantee that every frame is saved, leave this unset and accept occasional recordings containing scene noise. They typically only take up a few megabytes and are quick to scan in the timeline UI.

 :::

 ## Reviewing Detected Motion

-To review what the detector picked up — or to search past recordings for motion in a specific region — see [Reviewing Motion](/usage/review#reviewing-motion) on the Review page.
+To review what the detector picked up, or to search past recordings for motion in a specific region, see [Reviewing Motion](/usage/review#reviewing-motion) on the Review page.
@@ -6,6 +6,7 @@ title: Notifications
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";

 # Notifications

@@ -21,7 +22,7 @@ Push notifications require internet access from the Frigate server to the browse

 In order to use notifications the following requirements must be met:

- Frigate must be accessed via a secure `https` connection ([see the authorization docs](/configuration/authentication)).
+- Frigate must be accessed via a secure `https` connection while signed in as a Frigate user ([see the authorization docs](/configuration/authentication)).
 - A supported browser must be used. Currently Chrome, Firefox, and Safari are known to be supported.
 - In order for notifications to be usable externally, Frigate must be accessible externally.
 - For iOS devices, some users have also indicated that the Notifications switch needs to be enabled in iOS Settings --> Apps --> Safari --> Advanced --> Features.
@@ -85,7 +86,13 @@ cameras:

 ### Registration

-Once notifications are enabled, press the `Register for Notifications` button on all devices that you would like to receive notifications on. This will register the background worker. After this Frigate must be restarted and then notifications will begin to be sent.
+Once notifications are enabled, press the `Register This Device` button on all devices that you would like to receive notifications on. This will register the background worker. After this Frigate must be restarted and then notifications will begin to be sent.
+
+:::warning
+
+Each registration is attached to the Frigate user account you are signed in as, so you must register over a secure connection to the authenticated port (`8971`). Reverse proxies and tunnels should point at port `8971`.
+
+:::

 ## Supported Notifications

@@ -104,3 +111,62 @@ Different platforms handle notifications differently, some settings changes may
 ### Android

 Most Android phones have battery optimization settings. To get reliable Notification delivery the browser (Chrome, Firefox) should have battery optimizations disabled. If Frigate is running as a PWA then the Frigate app should have battery optimizations disabled as well.
+
+## Notifications FAQ
+
+<FaqItem id="how-do-i-debug-notifications-issues" question="How do I debug notifications issues?">
+
+Push notifications involve Frigate, your browser, and your browser vendor's push service, so it helps to work from the server outward.
+
+1. Enable debug logs for the push client by adding `frigate.comms.webpush: debug` to your `logger` configuration. Restart Frigate after this change.
+
+   ```yaml
+   logger:
+     default: info
+     logs:
+       # highlight-next-line
+       frigate.comms.webpush: debug
+   ```
+
+   These logs show exactly where a notification stopped, including:
+   - `Email must be provided for push notifications to be sent` means the global `email` field is empty and nothing will ever be sent.
+   - `Sending test notification` and `Sending push notification for <camera>, review ID <id>` mean Frigate handed the message off to the push service.
+   - `Skipping notification for <camera> - in global cooldown period` (or `camera-specific cooldown period`) means your [cooldown](#configuration) values suppressed it.
+   - `Notifications for <camera> are currently suspended` means notifications were suspended from <NavPath path="Settings > Notifications" /> or MQTT.
+   - `Notification endpoint expired for <user>, received 410` means that device's subscription is no longer valid and it must be re-registered.
+   - `Failed to send notification to <user> :: <status>` means the push service rejected the message. A `401` or `403` usually points at a VAPID or `email` problem, and a `5xx` is a problem on the push service's end.
+   - If you see no messages at all when an alert occurs, the notification was never queued. Confirm an actual **alert** was created (notifications are not sent for detections), and that notifications are enabled both globally and for that camera.
+
+2. Verify the basics that most reports come down to:
+   - Frigate must be reached over `https` with a certificate your device trusts. Browsers silently refuse to register a service worker otherwise, and a self-signed certificate that is not installed as trusted on the device will fail.
+   - On iOS, notifications only work when Frigate has been installed to the Home Screen via **Share > Add to Home Screen** and opened from that icon. Safari and Chrome tabs cannot receive web push on iOS.
+   - Each device must be registered individually, and Frigate must be restarted after registering before anything can be sent, including test notifications.
+   - The Frigate server needs outbound internet access to the browser vendor's push service. See [Network Requirements](/frigate/network_requirements#push-notifications).
+
+3. Test from the UI. Use the `Send a test notification` button in <NavPath path="Settings > Notifications" />. If the log shows `Sending test notification` but nothing arrives on the device, the problem is between the push service and your device rather than in Frigate.
+
+4. Check the browser side on the device that is not receiving notifications:
+   - Confirm the site's notification permission is set to **Allow** in your browser or OS settings, and that a focus/do not disturb mode is not hiding them.
+   - In desktop browsers, open Developer Tools > Application > Service Workers and confirm `notifications-worker.js` is registered and activated. Unregistering it and registering the device again will rebuild a broken subscription.
+   - Check the browser console and your reverse proxy logs for failures loading `/notifications-worker.js` or errors on `/api/notifications/register`.
+
+</FaqItem>
+
+<FaqItem id="why-did-notifications-stop-arriving-after-working-for-a-while" question="Why did notifications stop arriving after working for a while?">
+
+Push subscriptions are issued by the browser vendor and can be revoked, most often after a browser update, after clearing site data, or when a device has been offline for an extended period. When this happens the device still appears registered in Frigate, but the push service rejects the message. The debug logs will show `Notification endpoint expired` with a `404` or `410` status.
+
+Unregister and re-register the affected device from <NavPath path="Settings > Notifications" />, then restart Frigate.
+
+</FaqItem>
+
+<FaqItem id="why-am-i-not-getting-notifications-for-one-specific-camera" question="Why am I not getting notifications for one specific camera?">
+
+Work through these in order:
+
+- Notifications are only sent for **alerts**. If the camera is producing detections instead, adjust the camera's `review > alerts > labels` so the objects you care about are classified as alerts.
+- Confirm notifications are enabled for that camera in <NavPath path="Settings > Camera configuration > Notifications" />.
+- Check the camera's `cooldown` value, and remember that the global cooldown applies across all cameras. A busy camera can consume the global cooldown and suppress a quieter one.
+- If [authentication](/configuration/authentication) is enabled with roles, users only receive notifications for the cameras their role grants access to.
+
+</FaqItem>
@@ -7,7 +7,7 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

-There are several types of object filters that can be used to reduce false positive rates.
+There are several types of object filters that can be used to reduce [false positive](/frigate/glossary#false-positive) rates.

 ## Object Scores

@@ -26,9 +26,9 @@ In frame 2, the score is below the `min_score` value, so Frigate ignores it and

 The **top score** is the highest computed score the tracked object has ever reached during its lifetime. Because the computed score rises and falls as new frames come in, the top score can be thought of as the peak confidence Frigate had in the object. In Frigate's UI (such as the Tracking Details pane in Explore), you may see all three values:

- **Score** — the raw detector score for that single frame.
- **Computed Score** — the median of the most recent score history at that moment. This is the value compared against `threshold`.
- **Top Score** — the highest computed score reached so far for the tracked object.
+- **Score**: the raw detector score for that single frame.
+- **Computed Score**: the median of the most recent score history at that moment. This is the value compared against `threshold`.
+- **Top Score**: the highest computed score reached so far for the tracked object.

 ### Minimum Score

@@ -36,7 +36,7 @@ Any detection below `min_score` will be immediately thrown out and never tracked

 ### Threshold

-`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create an tracked object. If `threshold` is too high then true positive tracked objects may be missed due to the object never scoring high enough.
+`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create a tracked object. If `threshold` is too high then true positive tracked objects may be missed due to the object never scoring high enough.

 ## Configuring Object Scores

@@ -144,8 +144,8 @@ cameras:

 ### Zones

-[Required zones](/configuration/zones.md) can be a great tool to reduce false positives that may be detected in the sky or other areas that are not of interest. The required zones will only create tracked objects for objects that enter the zone.
+[Required zones](/configuration/zones.md#restricting-alerts-and-detections-to-specific-zones) can be a great tool to reduce false positives that may be detected in the sky or other areas that are not of interest. The required zones will only create tracked objects for objects that enter the zone.

 ### Object Masks

-[Object Filter Masks](/configuration/masks) are a last resort but can be useful when false positives are in the relatively same place but can not be filtered due to their size or shape. Object filter masks can be configured in <NavPath path="Settings > Camera configuration > Masks / Zones" />.
+[Object Filter Masks](/configuration/masks#object-filter-masks) are a last resort but can be useful when false positives are in the relatively same place but can not be filtered due to their size or shape. Object filter masks can be configured in <NavPath path="Settings > Camera configuration > Masks / Zones" />.
@@ -14,13 +14,13 @@ Profiles allow you to define named sets of camera configuration overrides that c
 Profiles operate as a two-level system:

 1. **Profile definitions** are declared at the top level of your config under `profiles`. Each definition has a machine name (the key) and a `friendly_name` for display in the UI.
-2. **Camera profile overrides** are declared under each camera's `profiles` section, keyed by the profile name. Only the settings you want to change need to be specified — everything else is inherited from the camera's base configuration.
+2. **Camera profile overrides** are declared under each camera's `profiles` section, keyed by the profile name. Only the settings you want to change need to be specified. Everything else is inherited from the camera's base configuration.

 When a profile is activated, Frigate merges each camera's profile overrides on top of its base config. When the profile is deactivated, all cameras revert to their original settings. Only one profile can be active at a time.

 :::info

-Profile changes are applied in-memory and take effect immediately — no restart is required. The active profile is persisted across Frigate restarts (stored in the `/config/.profiles` file).
+Profile changes are applied in-memory and take effect immediately. No restart is required. The active profile is persisted across Frigate restarts (stored in the `/config/.profiles` file).

 :::

@@ -33,10 +33,10 @@ The easiest way to define profiles is to use the Frigate UI. Profiles can also b
 <ConfigTabs>
 <TabItem value="ui">

-1. **Create a profile** — Navigate to <NavPath path="Settings > Global configuration > Profiles" />. Click the **Add Profile** button, enter a name (and optionally a profile ID).
-2. **Configure overrides** — Navigate to a camera configuration section (e.g. Motion detection, Record, Notifications). In the top right, two buttons will appear - choose a camera and a profile from the profile selector to edit overrides for that camera and section. Only the fields you change will be stored as overrides — fields that require a restart are hidden since profiles are applied at runtime. You can click the **Remove Profile Override** button to clear overrides.
-3. **Activate a profile** — Use the **Profiles** option in Frigate's main menu to choose a profile. Alternatively, in Settings, navigate to <NavPath path="Settings > Global configuration > Profiles" />, then choose a profile in the Active Profile dropdown to activate it. The active profile is also shown in the status bar at the bottom of the screen on desktop browsers.
-4. **Delete a profile** — Navigate to <NavPath path="Settings > Global configuration > Profiles" />, then click the trash icon for a profile. This removes the profile definition and all camera overrides associated with it.
+1. **Create a profile**: Navigate to <NavPath path="Settings > Global configuration > Profiles" />. Click the **Add Profile** button, enter a name (and optionally a profile ID).
+2. **Configure overrides**: Navigate to a camera configuration section (e.g. Motion detection, Record, Notifications). In the top right, two buttons will appear - choose a camera and a profile from the profile selector to edit overrides for that camera and section. Only the fields you change will be stored as overrides. Fields that require a restart are hidden since profiles are applied at runtime. You can click the **Remove Profile Override** button to clear overrides.
+3. **Activate a profile**: Use the **Profiles** option in Frigate's main menu to choose a profile. Alternatively, in Settings, navigate to <NavPath path="Settings > Global configuration > Profiles" />, then choose a profile in the Active Profile dropdown to activate it. The active profile is also shown in the status bar at the bottom of the screen on desktop browsers.
+4. **Delete a profile**: Navigate to <NavPath path="Settings > Global configuration > Profiles" />, then click the trash icon for a profile. This removes the profile definition and all camera overrides associated with it.

 </TabItem>
 <TabItem value="yaml">
@@ -126,7 +126,7 @@ Only the fields you explicitly set in a profile override are applied. All other

 ## Activating Profiles

-Profiles can be activated and deactivated via the Frigate UI, [MQTT](/integrations/mqtt#frigateprofileset), or the Home Assistant integration.
+Profiles can be activated and deactivated via the Frigate UI, [MQTT](/integrations/mqtt#frigateprofileset), the [HTTP API](../integrations/api/camera-set-camera-camera-name-set-feature-sub-command-put.api.mdx), or the Home Assistant integration.

 In the Frigate UI, open the Settings cog and select **Profiles** from the submenu to see all defined profiles. From there you can activate any profile or deactivate the current one. The active profile is indicated in the UI so you always know which profile is in effect.

@@ -232,6 +232,27 @@ No. Only one profile can be active at a time. Activating a new profile automatic

 When you delete a base zone or mask in the Frigate UI, any profile overrides for that entry are deleted automatically as part of the same operation. If you remove a base entry by editing your config file directly and leave a profile override behind, the config will fail validation at startup until the orphaned override is removed as well.

+### How do I make a YAML profile track no objects at all?
+
+Set the tracked object list explicitly to an empty list in the profile:
+
+```yaml
+cameras:
+  front_door:
+    profiles:
+      home:
+        objects:
+          track: []
+```
+
+Leaving the `objects` section empty (or omitting `track`) does not clear the list. Empty sections set no fields, so the profile inherits the full tracked object list from the base config, including anything set at the global level. The same applies to other lists, such as `audio.listen`.
+
 ### Why are some settings missing when I configure a profile override?

 Fields that require a Frigate restart to take effect cannot be overridden by profiles, since profiles are applied at runtime without restarting. Those fields are hidden when editing a profile override and can only be changed on the base configuration.
+
+### Can I schedule profiles to be enabled or disabled at certain times?
+
+Not within Frigate itself. Frigate is an NVR, not an automation platform, so it intentionally does not include a scheduler for activating profiles. Instead, activate profiles from an automation platform that already handles time- and event-based triggers well, such as [Home Assistant](https://www.home-assistant.io/) or [Node-RED](https://nodered.org/). These integrate with Frigate and give you far more robust and flexible scheduling than a built-in scheduler could.
+
+If you prefer something lightweight, a simple script driven by a cron job that toggles profiles on a schedule works too.
@@ -170,9 +170,9 @@ record:

 The `pre_capture` and `post_capture` values define the **time window** around a review item, but only recording segments that also match the configured **retention mode** are actually kept on disk.

- **`mode: all`** — Retains every segment within the capture window, regardless of whether motion was detected.
- **`mode: motion`** (default) — Only retains segments within the capture window that contain motion. This includes segments with active tracked objects, since object motion implies motion. Segments without any motion are discarded even if they fall within the pre/post capture range.
- **`mode: active_objects`** — Only retains segments within the capture window where tracked objects were actively moving. Segments with general motion but no active objects are discarded.
+- **`mode: all`**: Retains every segment within the capture window, regardless of whether motion was detected.
+- **`mode: motion`** (default): Only retains segments within the capture window that contain motion. This includes segments with active tracked objects, since object motion implies motion. Segments without any motion are discarded even if they fall within the pre/post capture range.
+- **`mode: active_objects`**: Only retains segments within the capture window where tracked objects were actively moving. Segments with general motion but no active objects are discarded.

 This means that with the default `motion` mode, you may see less footage than the configured pre/post capture duration if parts of the capture window had no motion.

@@ -197,11 +197,7 @@ Because recording segments are written in 10 second chunks, pre-capture timing d

 ### Where to view pre/post capture footage

-Pre and post capture footage is included in the **recording timeline**, visible in the History view. Note that pre/post capture settings only affect which recording segments are **retained on disk** — they do not change the start and end points shown in the UI. The History view will still center on the review item's actual time range, but you can scrub backward and forward through the retained pre/post capture footage on the timeline. The Explore view shows object-specific clips that are trimmed to when the tracked object was actually visible, so pre/post capture time will not be reflected there.
-
-## Will Frigate delete old recordings if my storage runs out?
-
-If there is less than an hour left of storage, the oldest hour of recordings will be deleted and a message will be printed in the Frigate logs. This emergency cleanup deletes the oldest recordings first regardless of retention settings to reclaim space as quickly as possible.
+Pre and post capture footage is included in the **recording timeline**, visible in the History view. Note that pre/post capture settings only affect which recording segments are **retained on disk**. They do not change the start and end points shown in the UI. The History view will still center on the review item's actual time range, but you can scrub backward and forward through the retained pre/post capture footage on the timeline. The Explore view shows object-specific clips that are trimmed to when the tracked object was actually visible, so pre/post capture time will not be reflected there.

 ## Configuring Recording Retention

@@ -279,6 +275,163 @@ record:

 This configuration will retain recording segments that overlap with alerts and detections for 10 days. Because multiple tracked objects can reference the same recording segments, this avoids storing duplicate footage for overlapping tracked objects and reduces overall storage needs.

+## Sub Stream Recording
+
+In addition to the main recording stream, Frigate can record a second, lower quality stream for each camera. This serves two purposes:
+
+- **Quality selection during playback**: A quality selector (`Auto`, `Original`, or `Low`) appears in History view for cameras with sub stream recording enabled. `Original` and `Low` play only that stream's recordings. Time ranges where the selected stream has no footage are skipped during playback, and the selector notes when the selected stream has no recordings at all in the viewed time range. With `Auto` (the default), playback prefers the original quality and automatically falls back to the low quality stream when the connection cannot keep up, or for time ranges where the original recordings have expired. The selector shows each stream's video codec and audio details beneath the options; footage recorded by older Frigate versions shows no details.
+- **Extended retention**: Sub stream recordings have their own retention settings, fully independent of the main recordings. By giving the low quality recordings a longer retention period, you can keep weeks or months of low quality history using a fraction of the storage, and that history remains playable after the main recordings expire. Playback falls back to the low quality recordings automatically, and the timeline shows a muted treatment for time ranges where only low quality footage remains. Timeline previews are kept for as long as either stream still has recordings, so scrubbing works across the whole retained history.
+
+### Configuring sub stream recording
+
+Sub stream recording uses the `record_sub` input role. This role can be assigned to the same input as `detect`, so in the common case where detect already uses the camera's sub stream, no additional camera connection is needed. Like the main recording stream, sub stream segments are copied directly from the camera stream without re-encoding, so the recording quality is determined by the source stream.
+
+The following examples keep 7 days of full quality continuous recordings and 60 days of low quality continuous recordings:
+
+<ConfigTabs>
+<TabItem value="ui">
+
+Navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> and select the camera.
+
+- In **Camera inputs**, enable the **Record (Sub Stream)** role on the stream you want to record at low quality, commonly the same stream that has the **Detect** role. Only one stream may have this role, and it cannot be assigned to the same stream as the **Record** role.
+
+Navigate to <NavPath path="Settings > Camera configuration > Recording" /> and select the camera.
+
+- Set **Enable recording** to on
+- Set **Continuous retention > Retention days** to `7`
+- Set **Sub stream recording > Enable sub stream recording** to on
+- Set **Sub stream recording > Sub stream continuous retention > Retention days** to `60`
+
+The camera setup wizard also offers the **Record (Sub Stream)** role when assigning stream roles for a newly added camera.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+cameras:
+  front_door:
+    ffmpeg:
+      inputs:
+        - path: rtsp://camera/main
+          roles:
+            - record
+        - path: rtsp://camera/sub
+          roles:
+            - detect
+            - record_sub
+    record:
+      enabled: true
+      continuous:
+        days: 7
+      sub:
+        enabled: true
+        continuous:
+          days: 60
+```
+
+If your camera does not provide a suitable sub stream (or the sub stream is already used at a resolution you don't want to record), you can use a go2rtc transcode as the source for `record_sub` instead:
+
+```yaml
+go2rtc:
+  streams:
+    front_door: rtsp://camera/main
+    front_door_lq: ffmpeg:front_door#video=h264#width=854#hardware
+
+cameras:
+  front_door:
+    ffmpeg:
+      inputs:
+        - path: rtsp://127.0.0.1:8554/front_door
+          input_args: preset-rtsp-restream
+          roles:
+            - detect
+            - record
+        - path: rtsp://127.0.0.1:8554/front_door_lq
+          input_args: preset-rtsp-restream
+          roles:
+            - record_sub
+    record:
+      enabled: true
+      continuous:
+        days: 7
+      sub:
+        enabled: true
+        continuous:
+          days: 60
+```
+
+</TabItem>
+</ConfigTabs>
+
+The `record.sub` config supports the same retention structure as the main recording config: `continuous`, `motion`, `alerts`, and `detections` each with their own `days` (and `mode` for alerts and detections). The pre-capture and post-capture windows for alerts and detections are taken from the main `record.alerts` and `record.detections` config. Extending `sub.alerts.days` or `sub.detections.days` beyond the main values also keeps those review items visible in the review timeline for the longer window, with playback falling back to the low quality stream once the main recordings expire.
+
+:::note
+
+Recording must be enabled (`record.enabled`) for sub stream recording to run, and Frigate will fail to start if `record.sub.enabled` is set without a `record_sub` role assigned to one of the camera's inputs.
+
+:::
+
+### How Auto picks a quality
+
+`Auto` measures throughput on every segment download and compares it against the original stream's bitrate (computed from the recorded footage itself). Playback drops to the low quality stream when any of these happen:
+
+- A freeze lasts 4 seconds (10 seconds when it starts within 2 seconds of a seek, since the seek target is rarely buffered), or freezes total 7 seconds within the last minute.
+- 3 downloads in a row measure below the original bitrate plus 10%, dropping quality before a stall ever becomes visible.
+- No first frame appears within 10 seconds, or loading fails outright.
+
+Playback returns to full quality only when measured throughput exceeds the original bitrate by 50%, checked continuously while playing the low quality stream and again at each new hour. The asymmetric thresholds (1.1x to drop, 1.5x to return) keep a borderline connection from switching back and forth.
+
+The most recent measurement is remembered on the device: a connection last measured below the original bitrate (or below 3 Mbps when the bitrate is not yet known) starts playback on the low quality stream so a first frame appears immediately, then upgrades within a few segments if the speed allows.
+
+The quality selector shows which stream Auto is currently playing and why. A browser with Data Saver enabled stays on the low quality stream, a browser that cannot decode the original stream's codec (for example H.265 without HEVC support) plays the low quality stream for that camera, and pinning `Original` or `Low` bypasses Auto entirely.
+
+### Sub stream output args
+
+By default the sub stream is recorded with the same [output args](/configuration/ffmpeg_presets#output-args-presets) as the main recording stream, so it inherits any customization made to `ffmpeg.output_args.record`. Setting `ffmpeg.output_args.record_sub` gives the sub stream its own args instead. Like all `ffmpeg` config, this can be set globally or per camera.
+
+The most common reason to set this is a pair of streams whose audio differs. Many cameras send AAC on the main stream but PCM on the sub stream, and PCM cannot be copied into an mp4 recording. Copying the main stream's audio avoids re-encoding audio that is already AAC, while the sub stream still needs to be transcoded:
+
+```yaml
+ffmpeg:
+  output_args:
+    # main stream audio is already AAC, so copy it
+    record: preset-record-generic-audio-copy
+    # sub stream audio is PCM, so transcode it to AAC
+    record_sub: preset-record-generic-audio-aac
+```
+
+Other reasons to set this are recording a sub stream whose codec needs a different preset than the main stream, such as `preset-record-mjpeg`, or forcing a matching audio sample rate across the two streams with manual args ending in `-c:a aac -ar 16000`.
+
+:::warning
+
+Avoid removing audio from only one of the two streams (for example with `-an`). When one stream has audio and the other does not, playback of time ranges that combine both qualities is silent, so stripping audio from the sub stream also silences the merged timeline.
+
+:::
+
+### Which stream do features use?
+
+As a general rule, features that read recordings prefer the main stream and fall back to the sub stream for time ranges where the main recordings have expired. Analytics features use only the main stream.
+
+| Feature                                                                                  | Stream used                                                                                                   |
+| ---------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
+| Recording playback (History and Review)                                                  | Both (main preferred with sub fallback by default), or exactly one stream when a quality is selected manually |
+| Tracking details and Explore clip playback                                               | Main, falling back to sub where the main recordings have expired                                              |
+| Exports and clip downloads                                                               | Main; sub is used when no main recordings remain in the range (streams are never mixed in one file)           |
+| Frames grabbed from a recording in History (download snapshot, submit frame to Frigate+) | Main preferred, sub fallback                                                                                  |
+| Audio extraction (e.g., transcription)                                                   | Main preferred, sub fallback                                                                                  |
+| Motion search                                                                            | Main only                                                                                                     |
+| Review timeline motion data                                                              | Main only                                                                                                     |
+| Storage usage statistics                                                                 | Both streams counted, and listed separately per camera                                                        |
+
+This table covers only features that read recordings from disk. Tracked object snapshots and thumbnails (the images shown in Explore and sent with notifications, and the images submitted to Frigate+ from a tracked object) are captured live from the `detect` stream as the object is tracked, never from recordings, so sub stream recording does not affect them.
+
+### Trade-offs
+
+- Recording a second stream increases overall storage use. The increase is typically small relative to the main recordings, since the low quality stream is much smaller. Both streams are cached before being written to disk, so cache use goes up as well. See [the `/tmp/cache` area is separate](#the-tmpcache-area-is-separate) if you start seeing `No space left on device` errors after enabling it.
+- The go2rtc transcode approach continuously encodes the low quality stream, which uses CPU or GPU resources. This cost only applies to the transcode path; recording the camera's native sub stream does not re-encode. See the [go2rtc hardware acceleration documentation](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg) for accelerating the transcode.
+- Many camera sub streams do not include audio. If the source stream has no audio, the low quality recordings will not have audio.
+- **Matching video codecs and audio settings between the two streams gives the smoothest playback.** When playback combines both qualities on one timeline (the default `Auto` behavior: for example original quality during events with low quality in between, or low quality history after the original recordings expire) and the streams use different video codecs or audio settings, for example H.265 on the main stream and H.264 on the sub stream, or 16 kHz audio on one and 8 kHz on the other, playback still works: Frigate inserts a decoder reset at each quality transition, which can cause a barely-perceptible pause there. Configuring both streams in the camera's firmware to use the same video codec, audio codec, and sample rate makes transitions fully seamless, and a mismatched audio sample rate can also be corrected with [sub stream output args](#sub-stream-output-args). If one stream has audio and the other does not, combined time ranges play **without audio**; selecting a single quality with the playback selector always keeps that stream's audio.
+
 ## Can I have "continuous" recordings, but only at certain times?

 Using Frigate UI, Home Assistant, or MQTT, cameras can be automated to only record in certain situations or at certain times.
@@ -355,3 +508,63 @@ Setting `verbose: true` writes a detailed report of every orphaned file and data
 This operation uses considerable CPU resources and includes a safety threshold that aborts if more than 50% of files would be deleted. Only run when necessary. If you set `force: true` the safety threshold will be bypassed; do not use `force` unless you are certain the deletions are intended.

 :::
+
+## Understanding storage usage
+
+The storage usage Frigate reports will not exactly match what the operating system reports with `df` or `du`. This is expected, not a bug. The sections below explain how Frigate derives its storage figures and why they differ from the disk's own accounting.
+
+### How Frigate measures recording usage
+
+The **Recordings** value on the Storage Metrics page (<NavPath path="System > Storage" />), and the per-camera **Camera Storage** breakdown, is the sum of the recording segment sizes Frigate has written, taken from Frigate's database. It is **not** computed by a scan of the disk. Frigate tracks usage this way by design: repeatedly walking the entire drive to total its size would keep hard drives spun up and add unnecessary I/O.
+
+The disk **total** shown beside it, and the free-space figure Frigate uses to decide when to delete recordings, instead come from the operating system's report for the whole filesystem mounted at `/media/frigate`. As a result, the **Unused** value on the page is _total disk capacity minus Frigate's recordings_, not the drive's real free space, which will be lower whenever anything else is stored on the disk.
+
+### What counts toward usage, and why it won't match `df`
+
+Only **recording segments** (`/media/frigate/recordings`) are included in the recordings storage total. Plenty of other things consume real disk space but are **not** part of that number:
+
+- **Snapshots and thumbnails** (`/media/frigate/clips`): see [Snapshots](/configuration/snapshots). These are retained independently of recordings.
+- **Preview videos** and **review thumbnails** (also under `/media/frigate/clips`).
+- **Exports** (`/media/frigate/exports`): exports are never removed by retention.
+- **The database, downloaded detection models, and face / license plate training images** (stored under `/config`).
+- **Debug images from enrichments** (`/media/frigate/clips`): when enabled, License Plate Recognition's `debug_save_plates` and GenAI's `debug_save_thumbnails` save plate crops and request images for troubleshooting.
+
+These files are the usual explanation for an "other" or seemingly unaccounted bucket of space: it is real, it is Frigate's, and it simply isn't part of the _recordings_ total. They are also why comparing the **Recordings** figure to `df -h` always shows a gap: `df` additionally counts any non-Frigate data on the disk, filesystem overhead and reserved blocks (ext4 reserves ~5% for root by default, so a disk can read "full" before recordings approach the total), and recently deleted recordings whose space has not yet been reclaimed.
+
+:::tip
+
+The Storage page is not intended to be a system-wide disk monitor: it shows how much space _Frigate's recordings_ use. To see true disk usage, use `df -h` (free space) and `du -sh` (per-directory usage) on the host.
+
+:::
+
+### Free space and the `/media/frigate` mount
+
+Frigate reports the capacity and free space of whatever filesystem is actually mounted at `/media/frigate` **inside the container**. If an external drive or network share isn't truly mounted there (a missing `/etc/fstab` entry, a share that was offline when the container started, or a host that doesn't pass the path through), the container falls back to the host's OS disk, and Frigate will correctly report that smaller disk instead of the drive you intended.
+
+If the reported capacity doesn't match your drive, the mount is the place to look, not Frigate. Verify what is actually mounted from inside the container:
+
+```bash
+docker exec -it frigate df -h /media/frigate
+docker exec -it frigate mount | grep media
+```
+
+See the [storage mount layout](/frigate/installation#storage) for how the volumes are expected to be configured.
+
+### The `/tmp/cache` area is separate
+
+Recording segments are first written to `/tmp/cache`, a small, in-memory (`tmpfs`) area, before being checked and moved to `/media/frigate/recordings`. Because it is separate and small, `/tmp/cache` can fill up and produce `No space left on device` errors even when the recordings disk has plenty of room. They are different storage areas. See [Recordings troubleshooting](/troubleshooting/recordings) for diagnosing cache and slow-storage issues.
+
+### When the metrics don't match what's on disk
+
+Because usage is tracked in the database, deleting recording files directly on disk, or files left behind after an upgrade, will not update the reported usage, and can even push it above 100%. Frigate is unaware of files it didn't record and won't count or remove them automatically. Use [Syncing Media Files With Disk](#syncing-media-files-with-disk) to reconcile the database with what is actually on disk.
+
+## Will Frigate delete old recordings if my storage runs out?
+
+Yes. Frigate continuously checks the **free space of the disk** holding `/media/frigate/recordings`. This is different from adding up the size of every recording: free space is a single number the operating system already tracks, so Frigate can ask for it instantly without reading through your files or spinning up the disk, which is exactly why it relies on this check rather than scanning the drive. When less than roughly one hour of recording space remains (estimated from the current recording bitrate, **not** a fixed percentage), Frigate deletes the oldest recordings to reclaim space and logs a message. This emergency cleanup removes the oldest recordings first **regardless of retention settings**.
+
+Two consequences follow from this being based on whole-disk free space:
+
+- Because the check uses the disk's real free space, **anything** filling the drive, including non-Frigate files, can trigger deletion of your oldest recordings.
+- Cleanup can run while a meaningful percentage of the disk is still free (for example, with high bitrates or many cameras), because the threshold is "less than ~1 hour of recording headroom," not "X% full."
+
+Frequent emergency cleanups usually mean your configured retention exceeds what the disk can hold. Reduce your retention days so the normal retention cleanup keeps up and the emergency path rarely triggers.
@@ -11,7 +11,7 @@ import NavPath from "@site/src/components/NavPath";

 Frigate can restream your video feed as an RTSP feed for other applications such as Home Assistant to utilize it at `rtsp://<frigate_host>:8554/<camera_name>`. Port 8554 must be open. [This allows you to use a video feed for detection in Frigate and Home Assistant live view at the same time without having to make two separate connections to the camera](#reduce-connections-to-camera). The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate.

-Frigate uses [go2rtc](https://github.com/AlexxIT/go2rtc/tree/v1.9.13) to provide its restream and MSE/WebRTC capabilities. The go2rtc config is hosted at the `go2rtc` in the config, see [go2rtc docs](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#configuration) for more advanced configurations and features.
+Frigate uses [go2rtc](https://github.com/AlexxIT/go2rtc/tree/v1.9.14) to provide its restream and MSE/WebRTC capabilities. The go2rtc config is hosted at the `go2rtc` in the config, see [go2rtc docs](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#configuration) for more advanced configurations and features.

 :::note

@@ -61,7 +61,7 @@ Configure the go2rtc stream and point the camera inputs at the local restream.
 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > System > go2rtc streams" /> and add stream entries for each camera. Then navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> for each camera. For each input, choose **Restream (go2rtc)** and pick the matching stream from the dropdown — Frigate uses the local restream URL (`rtsp://127.0.0.1:8554/<camera_name>`) and the `preset-rtsp-restream` input args for that input automatically. (Choose **Manual input path** instead to type a URL directly.)
+Navigate to <NavPath path="Settings > System > go2rtc streams" /> and add stream entries for each camera. Then navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> for each camera. For each input, choose **Restream (go2rtc)** and pick the matching stream from the dropdown. Frigate uses the local restream URL (`rtsp://127.0.0.1:8554/<camera_name>`) and the `preset-rtsp-restream` input args for that input automatically. (Choose **Manual input path** instead to type a URL directly.)

 </TabItem>
 <TabItem value="yaml">
@@ -111,7 +111,7 @@ Two connections are made to the camera. One for the sub stream, one for the rest
 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > System > go2rtc streams" /> and add stream entries for each camera and its sub stream. Then navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> for each camera and add separate inputs for the main and sub streams. Set each input's source to **Restream (go2rtc)** and pick the matching stream from the dropdown — Frigate uses the local restream URL and the `preset-rtsp-restream` input args for that input automatically.
+Navigate to <NavPath path="Settings > System > go2rtc streams" /> and add stream entries for each camera and its sub stream. Then navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> for each camera and add separate inputs for the main and sub streams. Set each input's source to **Restream (go2rtc)** and pick the matching stream from the dropdown. Frigate uses the local restream URL and the `preset-rtsp-restream` input args for that input automatically.

 </TabItem>
 <TabItem value="yaml">
@@ -221,7 +221,7 @@ For security reasons, the `echo:`, `expr:`, and `exec:` stream sources are disab

 If you attempt to use these sources in your configuration, the streams will be removed and an error message will be printed in the logs.

-To enable these sources, you must set the environment variable `GO2RTC_ALLOW_ARBITRARY_EXEC=true`. This can be done in your Docker Compose file or container environment:
+To enable these sources, you must set the environment variable `GO2RTC_ALLOW_ARBITRARY_EXEC=true`. This can be done in your Docker Compose file or container environment, or for Home Assistant App users with the `go2rtc_allow_arbitrary_exec` option in the App's configuration. The `environment_vars` section of the Frigate config can't enable it:

 ```yaml
 environment:
@@ -236,7 +236,7 @@ Enabling arbitrary exec sources allows execution of arbitrary commands through g

 ## Advanced Restream Configurations

-The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-exec) source in go2rtc can be used for custom ffmpeg commands and other applications. An example is below:
+The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.14#source-exec) source in go2rtc can be used for custom ffmpeg commands and other applications. An example is below:

 :::warning

@@ -23,7 +23,7 @@ In 0.14 and later, all of that is bundled into a single review item which starts

 ## Alerts and Detections

-Not every segment of video captured by Frigate may be of the same level of interest to you. Video of people who enter your property may be a different priority than those walking by on the sidewalk. For this reason, Frigate categorizes review items as _alerts_ and _detections_. By default, all person and car objects are considered alerts. You can refine categorization of your review items by configuring required zones for them.
+Not every segment of video captured by Frigate may be of the same level of interest to you. Video of people who enter your property may be a different priority than those walking by on the sidewalk. For this reason, Frigate categorizes review items as _alerts_ and _detections_. By default, all person and car objects are considered alerts. You can refine categorization of your review items by configuring [required zones](/configuration/zones#restricting-alerts-and-detections-to-specific-zones) for them.

 :::note

@@ -121,6 +121,31 @@ cameras:
 </TabItem>
 </ConfigTabs>

+## Categorizing manual events
+
+Events created with the [create manual event API](../integrations/api/create-event-events-camera-name-label-create-post.api.mdx) are categorized with the same label lists, using the label from the request path:
+
+1. If alerts are enabled and the label is listed in `review -> alerts -> labels`, the review item is an alert.
+2. Otherwise, if detections are enabled and the label is listed in `review -> detections -> labels`, the review item is a detection.
+3. If the label is in neither list, the review item is an alert, or no review item is created if alerts are disabled.
+
+This means manual events are alerts unless you explicitly list their label as a detection label. For example, to have PIR sensors create detections instead of alerts, post to `/api/events/front_door/pir_sensor/create` with the following config:
+
+```yaml {5-7}
+cameras:
+  front_door:
+    review:
+      detections:
+        labels:
+          - pir_sensor
+```
+
+:::note
+
+Required zones do not apply to manual events, since they are created through the API rather than by the object tracker. Setting `review -> alerts -> labels` to an empty list also does not stop manual events from becoming alerts, as a label in neither list still falls back to an alert.
+
+:::
+
 ## Restricting review items to specific zones

 By default a review item will be created if any `review -> alerts -> labels` and `review -> detections -> labels` are detected anywhere in the camera frame. You will likely want to configure review items to only be created when the object enters an area of interest, [see the zone docs for more information](./zones.md#restricting-alerts-and-detections-to-specific-zones)
@@ -7,7 +7,7 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

-Semantic Search in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This feature works by creating _embeddings_ — numerical vector representations — for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results.
+Semantic Search in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This feature works by creating _embeddings_, numerical vector representations, for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results.

 Frigate uses models from [Jina AI](https://huggingface.co/jinaai) to create and save embeddings to Frigate's database. All of this runs locally.

@@ -163,8 +163,8 @@ genai:
    model: your-model-name
    roles:
      - embeddings
-      - vision
-      - tools
+      - descriptions
+      - chat

 semantic_search:
  enabled: True
@@ -222,11 +222,11 @@ See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_

 ## Usage and Best Practices

-For tips on getting the best results from Semantic Search — choosing between thumbnail and description search, phrasing queries effectively, and combining search with the other Explore filters — see [Usage and best practices](/usage/explore#usage-and-best-practices) in the Usage docs.
+For tips on getting the best results from Semantic Search (choosing between thumbnail and description search, phrasing queries effectively, and combining search with the other Explore filters), see [Usage and best practices](/usage/explore#usage-and-best-practices) in the Usage docs.

 ## Triggers

-Triggers utilize Semantic Search to automate actions when a tracked object matches a specified image or description. Triggers can be configured so that Frigate executes a specific actions when a tracked object's image or description matches a predefined image or text, based on a similarity threshold. Triggers are managed per camera and can be configured via the Frigate UI in the Settings page under the Triggers tab.
+Triggers utilize Semantic Search to automate actions when a tracked object matches a specified image or description. Triggers can be configured so that Frigate executes specific actions when a tracked object's image or description matches a predefined image or text, based on a similarity threshold. Triggers are managed per camera and can be configured via the Frigate UI in the Settings page under the Triggers tab.

 :::note

@@ -7,14 +7,14 @@ import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";

-A snapshot is a single still image that captures a tracked object at its best moment — the clearest frame Frigate saw while following that object across the scene. Unlike a [recording](./record.md), which is continuous video, a snapshot is one representative image saved per tracked object once tracking ends.
+A snapshot is a single still image that captures a tracked object at its best moment: the clearest frame Frigate saw while following that object across the scene. Unlike a [recording](./record.md), which is continuous video, a snapshot is one representative image saved per tracked object once tracking ends.

-When snapshots are enabled, Frigate saves one image to `/media/frigate/clips` for each tracked object, named `<camera>-<id>-clean.webp`. A clean image is always stored without any annotations (no timestamp, bounding boxes, or cropping) so you have an unmodified copy of the original frame. Annotations like bounding boxes and timestamps are applied on demand when a snapshot is requested [via the HTTP API](../integrations/api/event-snapshot-events-event-id-snapshot-jpg-get.api.mdx) — see [Rendering](#rendering) below.
+When snapshots are enabled, Frigate saves one image to `/media/frigate/clips` for each tracked object, named `<camera>-<id>-clean.webp`. A clean image is always stored without any annotations (no timestamp, bounding boxes, or cropping) so you have an unmodified copy of the original frame. Annotations like bounding boxes and timestamps are applied on demand when a snapshot is requested [via the HTTP API](../integrations/api/event-snapshot-events-event-id-snapshot-jpg-get.api.mdx). See [Rendering](#rendering) below.

 A few things to keep in mind:

 - Snapshots are saved per tracked object, so a camera with no detected objects produces no snapshots even if recording is enabled.
- Snapshots and recordings are configured and retained independently — enabling one does not enable the other.
+- Snapshots and recordings are configured and retained independently. Enabling one does not enable the other.
 - Snapshots are accessible in the UI in the Explore pane, which allows for quick submission to the Frigate+ service.
 - To only save snapshots for objects that enter a specific zone, [see the zone docs](./zones.md#restricting-snapshots-to-specific-zones).
 - Snapshots sent via MQTT are configured separately under the camera MQTT settings, not here.
@@ -132,7 +132,7 @@ snapshots:

 Frigate does not save every frame. It picks a single "best" frame for each tracked object based on detection confidence, object size, and the presence of key attributes like faces or license plates. Frames where the object touches the edge of the frame are deprioritized. That best frame is written to disk once tracking ends.

-MQTT snapshots are published more frequently — each time a better thumbnail frame is found during tracking, or when the current best image is older than `best_image_timeout` (default: 60s). These use their own annotation settings configured under the camera MQTT settings.
+MQTT snapshots are published more frequently: each time a better thumbnail frame is found during tracking, or when the current best image is older than `best_image_timeout` (default: 60s). These use their own annotation settings configured under the camera MQTT settings.

 ## Rendering

@@ -43,7 +43,7 @@ Let's look at an example use case: I want to record any cars that enter my drive

 One might simply think "Why not just run object detection any time there is motion around the driveway area and notify if the bounding box is in that zone?"

-With that approach, what video is related to the car that entered the driveway? Did it come from the left or right? Was it parked across the street for an hour before turning into the driveway? One approach is to just record 24/7 or for motion (on any changed changed pixels) and not attempt to do that at all. This is what most other NVRs do. Just don't even try to identify a start and end for that object since it's hard and you will be wrong some portion of the time.
+With that approach, what video is related to the car that entered the driveway? Did it come from the left or right? Was it parked across the street for an hour before turning into the driveway? One approach is to just record 24/7 or for motion (on any changed pixels) and not attempt to do that at all. This is what most other NVRs do. Just don't even try to identify a start and end for that object since it's hard and you will be wrong some portion of the time.

 Couldn't you just look at when motion stopped and started? Motion for a video feed is nothing more than looking for pixels that are different than they were in previous frames. If the car entered the driveway while someone was mowing the grass, how would you know which motion was for the car and which was for the person when they mow along the driveway or street? What if another car was driving the other direction on the street? Or what if its a windy day and the bush by your mailbox is blowing around?

@@ -61,4 +61,4 @@ Now you have to determine which of the bounding boxes in this frame should be ma

 Now let's assume that those other 3 cars were already being tracked as stationary objects, so the car driving down the street is a new 4th car. The object tracker knows we have had 3 cars and we now have 4. As the new car approaches the parked cars, the bounding boxes for all 4 cars is predicted based on the previous frames. The predicted boxes for the parked cars is pretty much a 100% overlap with the bounding boxes in the new frame. The parked cars are slam dunk matches to the tracking ids they had before and the only one left is the remaining bounding box which gets assigned to the new car. This results in a much lower error rate. Not perfect, but better.

-The most difficult scenario that causes IDs to be assigned incorrectly is when an object completely occludes another object. When a car drives in front of another car and its no longer visible, a bounding box disappeared and it's a bit of a toss up when assigning the id since it's difficult to know which one is in front of the other. This happens for cars passing in front of other cars fairly often. It's something that we want to improve in the future.
+The most difficult scenario that causes IDs to be assigned incorrectly is when an object completely occludes another object. When a car drives in front of another car and it's no longer visible, a bounding box disappeared and it's a bit of a toss up when assigning the id since it's difficult to know which one is in front of the other. This happens for cars passing in front of other cars fairly often. It's something that we want to improve in the future.
@@ -18,7 +18,7 @@ Zones cannot have the same name as a camera. If desired, a single zone can inclu

 Zones can be toggled on or off without removing them from the configuration. Disabled zones are completely ignored at runtime - objects will not be tracked for zone presence, and zones will not appear in the debug view. This is useful for temporarily disabling a zone during certain seasons or times of day without modifying the configuration.

-During testing, enable the Zones option for the Debug view of your camera (Settings --> Debug) so you can adjust as needed. The zone line will increase in thickness when any object enters the zone.
+During testing, enable the Zones option for the [Debug view](/usage/live#the-single-camera-view) of your camera so you can adjust as needed. The zone line will increase in thickness when any object enters the zone.

 ## Creating a Zone

@@ -61,7 +61,7 @@ Navigate to <NavPath path="Settings > Camera configuration > Review" />.

 | Field                              | Description                                                                               |
 | ---------------------------------- | ----------------------------------------------------------------------------------------- |
-| **Alerts config > Required zones** | Zones that an object must enter to be considered an alert; leave empty to allow any zone. |
+| **Alerts config > Required zones** | Set to `entire_yard` so an object must enter that zone to be considered an alert; leave empty to allow alerts anywhere in the frame. |

 </TabItem>
 <TabItem value="yaml">
@@ -82,7 +82,7 @@ cameras:
 </TabItem>
 </ConfigTabs>

-You may also want to filter detections to only be created when an object enters a secondary area of interest. For example, to trigger alerts when an object enters the inner area of the yard but detections when an object enters the edge of the yard:
+You may also want to filter detections to only be created when an object enters a secondary area of interest. For example, to trigger alerts when an object enters the inner area of the yard (an `inner_yard` zone) but detections when an object enters the edge of the yard (an `edge_yard` zone):

 <ConfigTabs>
 <TabItem value="ui">
@@ -91,8 +91,8 @@ Navigate to <NavPath path="Settings > Camera configuration > Review" />.

 | Field                                  | Description                                                                                  |
 | -------------------------------------- | -------------------------------------------------------------------------------------------- |
-| **Alerts config > Required zones**     | Zones that an object must enter to be considered an alert; leave empty to allow any zone.    |
-| **Detections config > Required zones** | Zones that an object must enter to be considered a detection; leave empty to allow any zone. |
+| **Alerts config > Required zones**     | Set to `inner_yard` so an object must enter that zone to be considered an alert; leave empty to allow alerts anywhere in the frame.       |
+| **Detections config > Required zones** | Set to `edge_yard` so an object must enter that zone to be considered a detection; leave empty to allow detections anywhere in the frame. |

 </TabItem>
 <TabItem value="yaml">
@@ -121,7 +121,7 @@ cameras:

 ### Restricting snapshots to specific zones

-To only save snapshots when an object enters a specific zone:
+To only save snapshots when an object enters a specific zone, for example an `entire_yard` zone:

 <ConfigTabs>
 <TabItem value="ui">
@@ -27,11 +27,11 @@ Larger resolutions **do** improve performance if the objects are very small in t

 ### Choosing a detect frame rate

-`detect.fps` controls how many times per second Frigate runs object detection — it does **not** need to match your camera's frame rate. The default of **5** is correct for the vast majority of cameras.
+`detect.fps` controls how many times per second Frigate runs object detection. It does **not** need to match your camera's frame rate. The default of **5** is correct for the vast majority of cameras.

 :::warning

-Most users who raise `detect.fps` above the default don't need to. Increasing it consumes more CPU/GPU (detection load scales directly with the frame rate) while providing **no benefit to tracking** once objects are already being followed smoothly. Leave it at **5** unless you have a specific scene that fails the test below, and confirm any change actually helps in the debug view.
+Most users who raise `detect.fps` above the default don't need to. Increasing it consumes more CPU/GPU (detection load scales directly with the frame rate) while providing **no benefit to tracking** once objects are already being followed smoothly. Leave it at **5** unless you have a specific scene that fails the test below, and confirm any change actually helps in the [debug view](/usage/live#the-single-camera-view).

 :::

@@ -47,7 +47,7 @@ Estimate how long an object is visible as it crosses the area of interest, aimin

 > **`detect.fps` ≈ 10 ÷ (seconds the object is in view)**

-Most objects — people walking or running, pets, and vehicles in a yard, driveway, or walkway — stay in view for two seconds or more, so the default of 5 fps is correct. Slowly try raising it to 10 (the recommended maximum) in increments only when objects routinely cross the entire frame in about a second, such as a camera aimed at a street or sidewalk with fast cross-traffic. Objects that transit in under a second cannot be tracked reliably at any practical rate, so reposition the camera instead.
+Most objects (people walking or running, pets, and vehicles in a yard, driveway, or walkway) stay in view for two seconds or more, so the default of 5 fps is correct. Slowly try raising it to 10 (the recommended maximum) in increments only when objects routinely cross the entire frame in about a second, such as a camera aimed at a street or sidewalk with fast cross-traffic. Objects that transit in under a second cannot be tracked reliably at any practical rate, so reposition the camera instead.

 :::tip

@@ -11,11 +11,11 @@ The higher-priority of the two [review item](#review-item) severities, the other

 ## Attribute

-A property detected on an [object](#object) that exists alongside its [label](#label). Unlike a [sub label](#sub-label), an object can carry several attributes at once. Some attributes come directly from the object detection [model](#model) — for example `face`, `license_plate`, or delivery carrier logos such as `amazon`, `ups`, and `fedex` — while others come from a [custom object classification model](/configuration/custom_classification/object_classification) configured with the `attribute` type. Attributes are visible in the Tracked Object Details pane in Explore, in `frigate/events` MQTT messages, and through the HTTP API.
+A property detected on an [object](#object) that exists alongside its [label](#label). Unlike a [sub label](#sub-label), an object can carry several attributes at once. Some attributes come directly from the object detection [model](#model) (for example `face`, `license_plate`, or delivery carrier logos such as `amazon`, `ups`, and `fedex`), while others come from a [custom object classification model](/configuration/custom_classification/object_classification) configured with the `attribute` type. Attributes are visible in the Tracked Object Details pane in Explore, in `frigate/events` MQTT messages, and through the HTTP API.

 ## Bounding Box

-A box returned by the object detection [model](#model) that outlines a detected [object](#object) in the frame. In the Debug view, bounding boxes are colored by object [label](#label).
+A box returned by the object detection [model](#model) that outlines a detected [object](#object) in the frame. In the [Debug view](/usage/live#the-single-camera-view), bounding boxes are colored by object [label](#label).

 ### Bounding Box Colors

@@ -30,15 +30,15 @@ The categories a classification [model](#model) is trained to distinguish betwee

 ## Detection

-The lower-priority of the two [review item](#review-item) severities, the other being an [alert](#alert). By default, any review item that does not qualify as an alert is a detection; the qualifying [labels](#label) and [zones](#zone) can be configured. Despite the name, a detection is a category of review item — not the same as the object detection performed by the [model](#model). [See the review docs for more info](/configuration/review)
+The lower-priority of the two [review item](#review-item) severities, the other being an [alert](#alert). By default, any review item that does not qualify as an alert is a detection; the qualifying [labels](#label) and [zones](#zone) can be configured. Despite the name, a detection is a category of review item, not the same as the object detection performed by the [model](#model). [See the review docs for more info](/configuration/review)

 ## False Positive

-An incorrect result from the object detection [model](#model), where it assigns the wrong [label](#label) to something in the frame — for example a dog identified as a person, or a chair identified as a dog. A person correctly identified in an area you want to ignore is not a false positive.
+An incorrect result from the object detection [model](#model), where it assigns the wrong [label](#label) to something in the frame, for example a dog identified as a person, or a chair identified as a dog. A person correctly identified in an area you want to ignore is not a false positive.

 ## Label

-The type assigned to a detected [object](#object) by the object detection [model](#model), drawn from the model's labelmap — for example `person`, `car`, or `dog`. Frigate tracks `person` by default; additional labels are tracked by adding them to the objects configuration. [See the available objects docs for the full list](/configuration/objects)
+The type assigned to a detected [object](#object) by the object detection [model](#model), drawn from the model's labelmap, for example `person`, `car`, or `dog`. Frigate tracks `person` by default; additional labels are tracked by adding them to the objects configuration. [See the available objects docs for the full list](/configuration/objects)

 ## Mask

@@ -46,7 +46,7 @@ There are two types of masks in Frigate. [See the mask docs for more info](/conf

 ### Motion Mask

-A motion mask stops [motion](#motion) in the masked area from triggering object detection. It does not stop an object from being detected when object detection runs because of motion in a nearby area. Use motion masks for parts of the frame that change constantly but never contain objects you care about — camera timestamps, the sky, the tops of trees, and so on.
+A motion mask stops [motion](#motion) in the masked area from triggering object detection. It does not stop an object from being detected when object detection runs because of motion in a nearby area. Use motion masks for parts of the frame that change constantly but never contain objects you care about: camera timestamps, the sky, the tops of trees, and so on.

 ### Object Mask

@@ -55,7 +55,7 @@ Frigate supports multiple different detectors that work on different types of ha
 **Most Hardware**

 - [Hailo](#hailo-8): The Hailo8 and Hailo8L AI Acceleration module is available in m.2 format with a HAT for RPi devices offering a wide range of compatibility with devices.
-  - [Supports many model architectures](../../configuration/object_detectors#configuration)
+  - [Supports many model architectures](../../configuration/object_detectors#configuration-hailo)
  - Runs best with tiny or small size models

 - [Google Coral EdgeTPU](#google-coral-tpu): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices.
@@ -68,26 +68,26 @@ Frigate supports multiple different detectors that work on different types of ha
 **AMD**

 - [ROCm](#rocm---amd-gpu): ROCm can run on AMD Discrete GPUs to provide efficient object detection
-  - [Supports limited model architectures](../../configuration/object_detectors#rocm-supported-models)
+  - [Supports limited model architectures](../../configuration/object_detectors#amdrocm-gpu-detector)
  - Runs best on discrete AMD GPUs

 **Apple Silicon**

 - [Apple Silicon](#apple-silicon): Apple Silicon is usable on all M1 and newer Apple Silicon devices to provide efficient and fast object detection
-  - [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#apple-silicon-supported-models)
+  - [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#apple-silicon-detector)
  - Runs well with any size models including large
  - Runs via ZMQ proxy which adds some latency, only recommended for local connection

 **Intel**

 - [OpenVino](#openvino---intel): OpenVino can run on Intel Arc GPUs, Intel integrated GPUs, and Intel NPUs to provide efficient object detection.
-  - [Supports majority of model architectures](../../configuration/object_detectors#openvino-supported-models)
+  - [Supports majority of model architectures](../../configuration/object_detectors#openvino-detector)
  - Runs best with tiny, small, or medium models

 **Nvidia**

 - [Nvidia GPU](#nvidia-gpus): Nvidia GPUs can provide efficient object detection.
-  - [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx-supported-models)
+  - [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx)
  - Runs well with any size models including large

 - <CommunityBadge /> [Jetson](#nvidia-jetson): Jetson devices are supported via the TensorRT or ONNX detectors when running Jetpack 6.
@@ -111,14 +111,14 @@ Frigate supports multiple different detectors that work on different types of ha

 ### Hailo-8

-Frigate supports both the Hailo-8 and Hailo-8L AI Acceleration Modules on compatible hardware platforms—including the Raspberry Pi 5 with the PCIe hat from the AI kit. The Hailo detector integration in Frigate automatically identifies your hardware type and selects the appropriate default model when a custom model isn’t provided.
+Frigate supports both the Hailo-8 and Hailo-8L AI Acceleration Modules on compatible hardware platforms, including the Raspberry Pi 5 with the PCIe hat from the AI kit. The Hailo detector integration in Frigate automatically identifies your hardware type and selects the appropriate default model when a custom model isn’t provided.

 **Default Model Configuration:**

 - **Hailo-8L:** Default model is **YOLOv6n**.
 - **Hailo-8:** Default model is **YOLOv6n**.

-In real-world deployments, even with multiple cameras running concurrently, Frigate has demonstrated consistent performance. Testing on x86 platforms—with dual PCIe lanes—yields further improvements in FPS, throughput, and latency compared to the Raspberry Pi setup.
+In real-world deployments, even with multiple cameras running concurrently, Frigate has demonstrated consistent performance. Testing on x86 platforms, with dual PCIe lanes, yields further improvements in FPS, throughput, and latency compared to the Raspberry Pi setup.

 | Name             | Hailo‑8 Inference Time | Hailo‑8L Inference Time |
 | ---------------- | ---------------------- | ----------------------- |
@@ -78,7 +78,7 @@ Users of the Snapcraft build of Docker cannot use storage locations outside your

 Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is **64MB**.

-The default shm size of **128MB** is fine for setups with **2 cameras** detecting at **720p**. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size, using [`--shm-size`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#shm_size) in Docker Compose).
+The default shm size of **128MB** is fine for setups with **2 cameras** detecting at **720p**. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size, using [`--shm-size`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#shm_size) in Docker Compose). If raising the shm size does not help, check your [process and file limits](#process-and-file-limits) as well.

 The Frigate container also stores logs in shm, which can take up to **40MB**, so make sure to take this into account in your math as well.

@@ -86,6 +86,30 @@ The Frigate container also stores logs in shm, which can take up to **40MB**, so

 The shm size cannot be set per container for Home Assistant Apps. However, this is probably not required since by default Home Assistant Supervisor allocates `/dev/shm` with half the size of your total memory. If your machine has 8GB of memory, chances are that Frigate will have access to up to 4GB without any additional configuration.

+### Process and file limits
+
+Frigate runs many processes and opens a number of shared memory files. Installs with a large number of cameras can exceed the default limits your container runtime applies.
+
+Hitting the PID limit logs `RuntimeError: can't start new thread`, often followed by a "Bus error" that makes it look like an shm sizing problem. Compare the current count against the max from inside the container:
+
+```bash
+cat /sys/fs/cgroup/pids.current
+cat /sys/fs/cgroup/pids.max
+```
+
+If these are close, raise the limit with [`--pids-limit`](https://docs.docker.com/engine/containers/resource_constraints/) (or `service.pids_limit` in Docker Compose).
+
+Running out of file descriptors logs `OSError: [Errno 24] Too many open files`. Raise the limit in Docker Compose:
+
+```yaml
+services:
+  frigate:
+    ulimits:
+      nofile:
+        soft: 65535
+        hard: 65535
+```
+
 ## Extra Steps for Specific Hardware

 The following sections contain additional setup steps that are only required if you are using specific hardware. If you are not using any of these hardware types, you can skip to the [Docker](#docker) installation section.
@@ -94,7 +118,7 @@ The following sections contain additional setup steps that are only required if

 By default, the Raspberry Pi limits the amount of memory available to the GPU. In order to use ffmpeg hardware acceleration, you must increase the available memory by setting `gpu_mem` to the maximum recommended value in `config.txt` as described in the [official docs](https://www.raspberrypi.org/documentation/computers/config_txt.html#memory-options).

-Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with it's own power supply. Some have reported success with <a href="https://amzn.to/3a2mH0P" target="_blank" rel="nofollow noopener sponsored">this</a> (affiliate link).
+Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with its own power supply. Some have reported success with <a href="https://amzn.to/3a2mH0P" target="_blank" rel="nofollow noopener sponsored">this</a> (affiliate link).

 ### Hailo-8

@@ -484,14 +508,13 @@ Generate a Frigate Docker Compose configuration based on your hardware and requi

 <DockerComposeGenerator/>

-
  </TabItem>
  <TabItem value="original" label="Example Docker Compose File">
 ```yaml
 services:
  frigate:
    container_name: frigate
-    privileged: true # this may not be necessary for all setups
+    # privileged: true # ONLY enable if your hardware requires it (see hardware-specific docs); prefer the device mappings below
    restart: unless-stopped
    stop_grace_period: 30s # allow enough time to shut down the various services
    image: ghcr.io/blakeblackshear/frigate:stable
@@ -523,6 +546,33 @@ services:
  </TabItem>
 </Tabs>

+### Recommended security options
+
+Frigate does not need elevated container privileges for most setups. The
+following hardens the container; add the `devices`/`group_add` entries your
+hardware requires (see the hardware acceleration docs):
+
+```yaml
+services:
+  frigate:
+    ...
+    security_opt:
+      - no-new-privileges:true
+    cap_drop:
+      - ALL
+```
+
+:::note
+
+`telemetry.stats.network_bandwidth` uses nethogs, which requires root with
+NET_ADMIN/NET_RAW capabilities. If you enable that stat, omit `cap_drop: [ALL]`
+or add `cap_add: [NET_ADMIN, NET_RAW]`.
+
+Platforms that genuinely require `privileged: true` (MemryX, some QNAP setups)
+are called out in their own sections and are unaffected by this guidance.
+
+:::
+
 **Docker CLI**

 If you can't use Docker Compose, you can run the container with something similar to this:
@@ -589,6 +639,8 @@ Home Assistant OS users can install via the App repository.
 5. Start the App
 6. Use the _Open Web UI_ button to access the Frigate UI, then click in the _cog icon_ > _Configuration editor_ and configure Frigate to your liking

+App users who can't set container environment variables can put `FRIGATE_` values in a `secrets.yaml` next to `config.yml` in `/addon_configs/<addon_directory>` instead. See [`secrets.yaml`](../configuration/advanced/system.md#secretsyaml).
+
 There are several variants of the App available:

 | App Variant                | Description                                                |
@@ -11,9 +11,9 @@ Frigate is designed to run locally and does not require a persistent internet co

 Frigate's internet usage falls into three categories:

-1. **One-time model downloads** — ML models are downloaded the first time a feature is enabled, then cached locally. No internet is needed on subsequent startups.
-2. **Optional cloud services** — Features like Frigate+ and Generative AI connect to external APIs only when explicitly configured.
-3. **Build-time dependencies** — Components bundled into the Docker image during the build process. These require no internet at runtime.
+1. **One-time model downloads**: ML models are downloaded the first time a feature is enabled, then cached locally. No internet is needed on subsequent startups.
+2. **Optional cloud services**: Features like Frigate+ and Generative AI connect to external APIs only when explicitly configured.
+3. **Build-time dependencies**: Components bundled into the Docker image during the build process. These require no internet at runtime.

 :::tip

@@ -32,7 +32,13 @@ The following models are downloaded automatically the first time their associate
 | [License plate recognition](/configuration/license_plate_recognition)                         | PaddleOCR (detection, classification, recognition) + YOLOv9 plate detector | GitHub               |
 | [Bird classification](/configuration/bird_classification)                                     | MobileNetV2 bird model + label map                                         | GitHub               |
 | [Custom classification](/configuration/custom_classification/state_classification) (training) | MobileNetV2 ImageNet base weights (via Keras)                              | Google storage       |
-| [Audio transcription](/configuration/advanced/system)                                                | Whisper or Sherpa-ONNX streaming model                                     | HuggingFace / OpenAI |
+| [Audio transcription](/configuration/advanced/system)                                         | Whisper or Sherpa-ONNX streaming model                                     | HuggingFace / OpenAI |
+
+:::note
+
+The MobileNetV2 base weights are the one exception to the `/config/model_cache/` rule. They are also the only entry that is not downloaded when the feature is enabled: Frigate fetches them when a training run actually starts.
+
+:::

 ### Hardware-Specific Detector Models

@@ -75,7 +81,7 @@ If your Frigate instance has restricted internet access, you can point model dow
 | `HF_ENDPOINT`                       | `https://huggingface.co`            | Semantic search, Sherpa-ONNX, AXEngine models |
 | `GITHUB_ENDPOINT`                   | `https://github.com`                | Face recognition, LPR, RKNN models            |
 | `GITHUB_RAW_ENDPOINT`               | `https://raw.githubusercontent.com` | Bird classification                           |
-| `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` | Google storage (Keras default)      | Custom classification training                |
+| `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` | Unset (Keras uses its own default)  | Custom classification training                |

 ## Optional Cloud Services

@@ -91,13 +97,13 @@ See [Frigate+](/integrations/plus) for details.

 When a Generative AI provider is configured, Frigate sends images and prompts to the configured provider for event descriptions, chat, and camera monitoring. Available providers:

-| Provider      | Internet Required                                                |
-| ------------- | ---------------------------------------------------------------- |
-| OpenAI        | Yes — connects to OpenAI API (or custom base URL)                |
-| Google Gemini | Yes — connects to Google Generative AI API                       |
-| Azure OpenAI  | Yes — connects to your Azure endpoint                            |
-| Ollama        | Depends — typically local (`localhost:11434`), but can be remote |
-| llama.cpp     | No — runs entirely locally                                       |
+| Provider      | Internet Required                                               |
+| ------------- | --------------------------------------------------------------- |
+| OpenAI        | Yes, connects to OpenAI API (or custom base URL)                |
+| Google Gemini | Yes, connects to Google Generative AI API                       |
+| Azure OpenAI  | Yes, connects to your Azure endpoint                            |
+| Ollama        | Depends: typically local (`localhost:11434`), but can be remote |
+| llama.cpp     | No, runs entirely locally                                       |

 Disable Generative AI by removing the `genai` configuration from your cameras. See [Generative AI](/configuration/genai/genai_config) for details.

@@ -126,30 +132,44 @@ When using the [DeepStack detector plugin](/configuration/object_detectors), Fri

 For [WebRTC live streaming](/configuration/live), Frigate uses STUN for NAT traversal:

- **go2rtc** defaults to a local STUN listener (`stun:8555`) — no internet required.
+- **go2rtc** defaults to a local STUN listener (`stun:8555`), no internet required.
 - **The web UI's WebRTC player** includes a fallback to Google's public STUN server (`stun:stun.l.google.com:19302`), which requires internet.

 ## Home Assistant Supervisor

-When running as a Home Assistant add-on, the go2rtc startup script queries the local Supervisor API (`http://supervisor/`) to discover the host IP address and WebRTC port. This is a local network call to the Home Assistant host, not an internet connection.
+When running as a Home Assistant App, the go2rtc startup script queries the local Supervisor API (`http://supervisor/`) to discover the host IP address and WebRTC port. This is a local network call to the Home Assistant host, not an internet connection.

 ## What Does NOT Require Internet

- **Object detection** — CPU, EdgeTPU, OpenVINO, and other bundled detector models are included in the Docker image.
- **Recording and playback** — All video is stored and served locally.
- **Live streaming** — Camera streams are pulled over your local network. MSE and HLS streaming work without any external connections.
- **The web interface** — Fully self-contained with no external fonts, scripts, analytics, or CDN dependencies. All translations are bundled locally.
- **Custom classification inference** — After training, custom models run entirely locally.
- **Audio detection** — The YAMNet audio classification model is bundled in the Docker image.
+- **Object detection**: CPU, EdgeTPU, OpenVINO, and other bundled detector models are included in the Docker image.
+- **Recording and playback**: All video is stored and served locally.
+- **Live streaming**: Camera streams are pulled over your local network. MSE and HLS streaming work without any external connections.
+- **The web interface**: Fully self-contained with no external fonts, scripts, analytics, or CDN dependencies. All translations are bundled locally.
+- **Custom classification inference**: After training, custom models run entirely locally.
+- **Audio detection**: The YAMNet audio classification model is bundled in the Docker image.

 ## Running Frigate Offline

 To run Frigate in an air-gapped or offline environment:

-1. **Pre-download models** — Start Frigate with internet access once with all desired features enabled. Models will be cached in `/config/model_cache/`.
-2. **Disable version check** — Set `telemetry.version_check: false` in your configuration.
-3. **Block outbound model requests** — Set the `HF_HUB_OFFLINE=1` and `TRANSFORMERS_OFFLINE=1` environment variables to prevent HuggingFace and Transformers from attempting any network requests.
-4. **Avoid cloud features** — Do not configure Frigate+, Generative AI providers that require internet, or cloud MQTT brokers.
-5. **Use local model mirrors** — If limited internet is available, set the `HF_ENDPOINT`, `GITHUB_ENDPOINT`, and `GITHUB_RAW_ENDPOINT` environment variables to point to local mirrors.
+1. **Pre-download models**: Start Frigate with internet access once with all desired features enabled. Models will be cached in `/config/model_cache/`.
+2. **Pre-download the training base weights**: If you plan to train custom classification models, set `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` before training, then run one training job while online. Without this variable the base weights are cached outside `/config/` and are lost whenever the container is recreated, so a later training run will fail offline. If the machine never has internet access, copy the weights in manually as described below.
+3. **Disable version check**: Set `telemetry.version_check: false` in your configuration.
+4. **Block outbound model requests**: Set the `HF_HUB_OFFLINE=1` and `TRANSFORMERS_OFFLINE=1` environment variables to prevent HuggingFace and Transformers from attempting any network requests.
+5. **Avoid cloud features**: Do not configure Frigate+, Generative AI providers that require internet, or cloud MQTT brokers.
+6. **Use local model mirrors**: If limited internet is available, set the `HF_ENDPOINT`, `GITHUB_ENDPOINT`, `GITHUB_RAW_ENDPOINT`, and `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` environment variables to point to local mirrors.

 After these steps, Frigate will operate with no outbound internet connections.
+
+### Manually Copying the Training Base Weights
+
+On a machine with internet access, download the weights:
+
+```bash
+curl -L -o mobilenet_v2_weights.h5 \
+  "https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v2/mobilenet_v2_weights_tf_dim_ordering_tf_kernels_0.35_224_no_top.h5"
+```
+
+Copy the file into your Frigate config volume as `/config/model_cache/MobileNet/mobilenet_v2_weights.h5`, keeping that exact filename, then set the environment variable `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` in your Docker compose file to the URL above and restart Frigate.
+
+The variable must be set even though the URL is never contacted. If it is unset, Frigate ignores the copied file and asks Keras to download the weights instead.
@@ -42,6 +42,8 @@ Frigate requires a CPU with AVX + AVX2 instructions. Most modern CPUs (post-2011

 Storage is an important consideration when planning a new installation. To get a more precise estimate of your storage requirements, you can use an IP camera storage calculator. Websites like [IPConfigure Storage Calculator](https://calculator.ipconfigure.com/) can help you determine the necessary disk space based on your camera settings.

+Once running, see [Understanding storage usage](/configuration/record#understanding-storage-usage) for how Frigate measures and reports disk usage, and why its numbers won't exactly match `df` or `du`.
+
 #### SSDs (Solid State Drives)

 SSDs are an excellent choice for Frigate, offering high speed and responsiveness. The older concern that SSDs would quickly "wear out" from constant video recording is largely no longer valid for modern consumer and enterprise-grade SSDs.
@@ -144,7 +144,7 @@ At this point you should be able to start Frigate and a basic config will be cre

 ### Step 2: Add a camera

-Click the **Add Camera** button in <NavPath path="Settings > Global configuration > Camera management" /> to use the camera setup wizard to get your first camera added into Frigate.
+Click the **Add Camera** button in <NavPath path="Settings > Global configuration > Camera management" /> to use the camera setup wizard to get your first camera added into Frigate. See [Adding a camera with the Add Camera Wizard](../configuration/cameras.md#adding-a-camera-with-the-add-camera-wizard) for a walkthrough of each step.

 ### Step 3: Configure hardware acceleration (recommended)

@@ -204,8 +204,8 @@ You need to refer to **Configure hardware acceleration** above to enable the con
 <ConfigTabs>
 <TabItem value="ui">

-1. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `OpenVINO` and **Device** `GPU`
-2. On the same page, in the **Custom Model** tab, configure the model settings for OpenVINO:
+1. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Intel GPU** from the **Hardware** dropdown
+2. On the same model, open the **Custom Model** tab and configure the model settings for OpenVINO:

 | Field                                    | Value                                      |
 | ---------------------------------------- | ------------------------------------------ |
@@ -222,15 +222,12 @@ You need to refer to **Configure hardware acceleration** above to enable the con
 ```yaml {3-6,9-15,20-21}
 mqtt: ...

-detectors: # <---- add detectors
-  ov:
-    type: openvino  # <---- use openvino detector
-    device: GPU
-
-# We will use the default MobileNet_v2 model from OpenVINO.
-model:
-  width: 300
-  height: 300
+models: # <---- add models
+  - devices:
+      - openvino:GPU # <---- use the openvino detector on the GPU
+    # We will use the default MobileNet_v2 model from OpenVINO.
+    width: 300
+    height: 300
  input_tensor: nhwc
  input_pixel_format: bgr
  path: /openvino-model/ssdlite_mobilenet_v2.xml
@@ -273,7 +270,7 @@ services:
 <ConfigTabs>
 <TabItem value="ui">

-Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`.
+Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown.

 </TabItem>
 <TabItem value="yaml">
@@ -281,10 +278,9 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a
 ```yaml {3-6,11-12}
 mqtt: ...

-detectors: # <---- add detectors
-  coral:
-    type: edgetpu
-    device: usb
+models: # <---- add models
+  - devices:
+      - edgetpu:usb

 cameras:
  name_of_your_camera:
@@ -305,7 +301,7 @@ Restart Frigate and you should start seeing detections for `person`. If you want

 ### Step 5: Setup motion masks

-Now that you have optimized your configuration for decoding the video stream, you will want to check to see where to implement motion masks. Click on the camera from the main dashboard, then select the gear icon in the top right, enable Debug View, and finally enable the switch for Motion Boxes. Watch for areas that continuously trigger unwanted motion to be detected. Common areas to mask include camera timestamps and trees that frequently blow in the wind. The goal is to avoid wasting object detection cycles looking at these areas.
+Now that you have optimized your configuration for decoding the video stream, you will want to check to see where to implement motion masks. Click on the camera from the main dashboard, then select the gear icon in the top right, enable the [Debug view](/usage/live#the-single-camera-view), and finally enable the switch for Motion Boxes. Watch for areas that continuously trigger unwanted motion to be detected. Common areas to mask include camera timestamps and trees that frequently blow in the wind. The goal is to avoid wasting object detection cycles looking at these areas.

 Use the mask editor to draw polygon masks directly on the camera feed. Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and set up a motion mask over the area. More information about masks can be found [here](../configuration/masks.md).

@@ -321,10 +317,9 @@ If you are using YAML to configure Frigate instead of the UI, your configuration
 mqtt:
  enabled: False

-detectors:
-  coral:
-    type: edgetpu
-    device: usb
+models:
+  - devices:
+      - edgetpu:usb

 cameras:
  name_of_your_camera:
@@ -357,7 +352,7 @@ In order to review activity in the Frigate UI, recordings need to be enabled.
 ```yaml {16-17}
 mqtt: ...

-detectors: ...
+models: ...

 cameras:
  name_of_your_camera:
@@ -35,7 +35,7 @@ Frigate relies on WebSockets for real-time communication between the browser and

 Your reverse proxy must be configured to forward the `Upgrade` and `Connection` headers so that WebSocket connections can be established. Each proxy example below already includes the directives needed to do this, but if you are adapting your own configuration, ensure these headers are passed through.

-Note that some proxies disable WebSocket support by default — for example, Nginx Proxy Manager has a "Websockets Support" toggle that must be enabled.
+Note that some proxies disable WebSocket support by default. For example, Nginx Proxy Manager has a "Websockets Support" toggle that must be enabled.

 ## Proxies

@@ -9,6 +9,8 @@ The best way to integrate with Home Assistant is to use the [official integratio

 ### Preparation

+Frigate itself must be installed and running before setting up the integration. See the [installation documentation](../frigate/installation.md) for details.
+
 The Frigate integration requires the `mqtt` integration to be installed and
 manually configured first.

@@ -122,7 +124,7 @@ Use `http://<frigate_device_ip>:8971` as the URL for the integration so that aut

 The above URL assumes you have [disabled TLS](../configuration/tls).
 By default, TLS is enabled and Frigate will be using a self-signed certificate. HomeAssistant will fail to connect HTTPS to port 8971 since it fails to verify the self-signed certificate.
-Either disable TLS and use HTTP from HomeAssistant, or configure Frigate to be acessible with a valid certificate.
+Either disable TLS and use HTTP from HomeAssistant, or configure Frigate to be accessible with a valid certificate.

 :::

@@ -279,7 +281,7 @@ For advanced usecases, this behavior can be changed with the [RTSP URL
 template](#options) option. When set, this string will override the default stream
 address that is derived from the default behavior described above. This option supports
 [jinja2 templates](https://jinja.palletsprojects.com/) and has the `camera` dict
-variables from [Frigate API](../integrations/api)
+variables from [Frigate API](/integrations/api/frigate-http-api)
 available for the template. Note that no Home Assistant state is available to the
 template, only the camera dict from Frigate.

@@ -3,35 +3,100 @@ id: homekit
 title: HomeKit
 ---

-Frigate cameras can be integrated with Apple HomeKit through go2rtc. This allows you to view your camera streams directly in the Apple Home app on your iOS, iPadOS, macOS, and tvOS devices.
+Frigate cameras can be exported to Apple HomeKit through go2rtc. Each exported camera appears as an accessory in the Apple Home app on your iOS, iPadOS, macOS, and tvOS devices.

 ## Overview

-HomeKit integration is handled entirely through go2rtc, which is embedded in Frigate. go2rtc provides the necessary HomeKit Accessory Protocol (HAP) server to expose your cameras to HomeKit.
+Exporting cameras is handled entirely through go2rtc, which is embedded in Frigate. go2rtc provides the necessary HomeKit Accessory Protocol (HAP) server, so your camera is published to HomeKit as an accessory in its own right.

-## Setup
+:::note

-All HomeKit configuration and pairing should be done through the **go2rtc WebUI**.
+This is the opposite of importing a HomeKit camera. go2rtc can also pair with an existing HomeKit camera (Aqara, Eve, Eufy, and similar) and use it as a stream source, which is what the `add` page of the go2rtc WebUI is for. That page discovers HomeKit accessories on your network and will not list your Frigate cameras. It is not used for exporting.

-### Accessing the go2rtc WebUI
-
-The go2rtc WebUI is available at:
-
-```
-http://<frigate_host>:1984
-```
-
-Replace `<frigate_host>` with the IP address or hostname of your Frigate server.
-
-### Pairing Cameras
-
-1. Navigate to the go2rtc WebUI at `http://<frigate_host>:1984`
-2. Use the `add` section to add a new camera to HomeKit
-3. Follow the on-screen instructions to generate pairing codes for your cameras
+:::

 ## Requirements

- Frigate must be accessible on your local network using host network_mode
- Your iOS device must be on the same network as Frigate
- Port 1984 must be accessible for the go2rtc WebUI
- For detailed go2rtc configuration options, refer to the [go2rtc documentation](https://github.com/AlexxIT/go2rtc)
+- Frigate must be running with `network_mode: host` so that HomeKit can discover your cameras over mDNS
+- Your Apple device must be on the same network as Frigate
+- Port 1984 must be accessible so you can reach the go2rtc WebUI
+
+HomeKit also places strict limits on the stream itself. go2rtc passes your stream through without resizing or re-encoding it, so the stream you export must already meet these requirements:
+
+- **Video:** H.264 at 1920x1080, 1280x720, or 320x240
+- **Audio:** Opus, mono, 16 kHz
+
+A camera's full resolution stream usually does not qualify. See [Exporting a compatible stream](#exporting-a-compatible-stream) below.
+
+## Configuration
+
+HomeKit settings are stored in `/config/go2rtc_homekit.yml`. This is a separate file from your Frigate config, because go2rtc needs to write your pairings back to it when you pair a device.
+
+Edit it using the go2rtc config editor, which writes to that file directly:
+
+```
+http://<frigate_host>:1984/editor.html
+```
+
+Replace `<frigate_host>` with the IP address or hostname of your Frigate server. The editor will be empty until you add a HomeKit section, since this file holds only your HomeKit settings and not the rest of your go2rtc config.
+
+:::warning
+
+Do not put the `homekit:` section in the `go2rtc:` section of your Frigate config.
+
+Frigate regenerates that config on every startup, so go2rtc cannot save your pairings to it. Pairing will appear to succeed and then fail after the next restart with `PairVerify with unknown client_id`. If the section exists in both places, your saved pairings are erased on every restart.
+
+:::
+
+Add an entry for each camera you want to export. The key must match the name of a go2rtc stream, and the pin must be 8 digits. This is the number the Home app calls the setup code:
+
+```yaml
+homekit:
+  front_door:
+    name: Front Door
+    pin: "12345678"
+```
+
+If the key does not match a go2rtc stream, go2rtc logs `[homekit] missing stream:` at startup and the camera will not appear in the Home app.
+
+:::note
+
+go2rtc derives each accessory's HomeKit identity from this key, so renaming it later means the camera appears as a new accessory and has to be paired again. Settle on the name before you pair.
+
+:::
+
+Frigate keeps only the `homekit:` section of this file when it starts, so do not store streams or other go2rtc settings in it.
+
+### Exporting a compatible stream
+
+If a camera's stream does not meet the requirements listed above, define a scaled restream in your Frigate config and point HomeKit at that stream instead of the original:
+
+```yaml
+go2rtc:
+  streams:
+    front_door:
+      - rtsp://user:password@192.168.1.50:554/stream
+    front_door_homekit:
+      - "ffmpeg:front_door#video=h264#width=1280#height=720#audio=opus/16000"
+```
+
+```yaml
+# /config/go2rtc_homekit.yml
+homekit:
+  front_door_homekit:
+    name: Front Door
+    pin: "12345678"
+```
+
+Add `#hardware=cuda`, `#hardware=vaapi`, or the appropriate value for your system to transcode using your GPU. Note that NVENC cannot encode H.264 wider than 4096 pixels, so very wide streams must be scaled down as shown above rather than only re-encoded.
+
+## Pairing Cameras
+
+1. Restart Frigate after adding the `homekit:` section
+2. In the Apple Home app, choose **Add Accessory**, then **More options** to enter a code manually
+3. Select your camera and enter the pin you configured as the setup code
+4. Confirm that a `pairings:` list now appears under the camera in `/config/go2rtc_homekit.yml`
+
+Pairings are saved back to that file automatically. If step 4 shows no `pairings:` list, check the Frigate log for `[homekit] can't save`, which means the `homekit:` section is missing from `/config/go2rtc_homekit.yml`.
+
+For detailed go2rtc configuration options, refer to the [go2rtc documentation](https://github.com/AlexxIT/go2rtc).
@@ -16,7 +16,7 @@ MQTT requires a network connection to your broker. This is typically local, but
 ### `frigate/available`

 Designed to be used as an availability topic with Home Assistant. Possible message are:
-"online": published when Frigate is running (on startup)
+"online": published once Frigate is running and has published its initial state. Note that this is published on every connection to the broker, so it is republished if the broker restarts or the connection drops and recovers, without Frigate itself restarting.
 "stopped": published when Frigate is stopped normally
 "offline": published automatically by the MQTT broker if Frigate disconnects unexpectedly (via MQTT Will Message)

@@ -280,7 +280,7 @@ Same data available at `/api/stats` published at a configurable interval.

 ### `frigate/camera_activity`

-Returns data about each camera, its current features, and if it is detecting motion, objects, etc. Can be triggered by publising to `frigate/onConnect`
+Returns data about each camera, its current features, and if it is detecting motion, objects, etc. Can be triggered by publishing to `frigate/onConnect`

 ### `frigate/profile/set`

@@ -292,7 +292,9 @@ Topic with the currently active profile name. Published value is the profile nam

 ### `frigate/notifications/set`

-Topic to turn notifications on and off. Expected values are `ON` and `OFF`.
+Topic to turn notifications on and off for all cameras. Expected values are `ON` and `OFF`.
+
+Only available when notifications are enabled in the config. Not persisted across Frigate restarts.

 ### `frigate/notifications/state`

@@ -302,12 +304,14 @@ Topic with current state of notifications. Published values are `ON` and `OFF`.

 ### `frigate/<camera_name>/status/<role>`

-Publishes the current health status of each role that is enabled (`audio`, `detect`, `record`). Possible values are:
+Publishes the current health status of each role that is enabled (`audio`, `detect`, `record`, `record_sub`). `record_sub` is only published for cameras with [sub stream recording](/configuration/record#sub-stream-recording) enabled, and is tracked separately from `record` so a healthy main stream can't hide a stalled sub stream. Possible values are:

 - `online`: Stream is running and being processed
 - `offline`: Stream is offline and is being restarted
 - `disabled`: Camera is currently turned off (either at runtime via the `enabled/set` topic, or persistently via the configuration file). See [Camera state](/configuration/live#camera-state) for the distinction.

+These reflect the state of Frigate's process for that role, not the camera's reachability, so an unreachable camera alternates between `offline` and `online` as the watchdog restarts ffmpeg. Wait for the status to hold steady (for example with Home Assistant's `for:`) rather than acting on a single message.
+
 ### `frigate/<camera_name>/<object_name>`

 Publishes the count of objects for the camera for use as a sensor in Home Assistant.
@@ -390,6 +394,18 @@ Topic to turn audio detection for a camera on and off. Expected values are `ON`

 Topic with current state of audio detection for a camera. Published values are `ON` and `OFF`.

+### `frigate/<camera_name>/audio_transcription/set`
+
+Topic to turn [live audio transcription](/configuration/audio_detectors#live-transcription) for a camera on and off. Expected values are `ON` and `OFF`. Transcribed text is published to `frigate/<camera_name>/audio/transcription`.
+
+`ON` is ignored unless audio transcription is enabled in the config for the camera. Unlike the other camera toggles, this one is not persisted across Frigate restarts.
+
+**NOTE:** Requires audio detection and transcription to be enabled
+
+### `frigate/<camera_name>/audio_transcription/state`
+
+Topic with current state of live audio transcription for a camera. Published values are `ON` and `OFF`.
+
 ### `frigate/<camera_name>/recordings/set`

 Topic to turn recordings for a camera on and off. Expected values are `ON` and `OFF`. The change is persisted across Frigate restarts (see [Runtime toggle persistence](/configuration/live#runtime-toggle-persistence)).
@@ -537,35 +553,42 @@ must be enabled in the configuration.

 Topic with current state of Birdseye for a camera. Published values are `ON` and `OFF`.

-### `frigate/<camera_name>/birdseye_mode/set`
+### `frigate/<camera_name>/birdseye_modes/set`

-Topic to set Birdseye mode for a camera. Birdseye offers different modes to customize under which circumstances the camera is shown.
+Topic to set the Birdseye activity types for a camera. Send one uppercase activity type or combine multiple types with commas, for example `MOTION,ALERTS`.

-_Note: Changing the value from `CONTINUOUS` -> `MOTION | OBJECTS` will take up to 30 seconds for
+_Note: Changing the value from `CONTINUOUS` to non-continuous activity types will take up to 30 seconds for
 the camera to be removed from the view._

-| Command      | Description                                                       |
-| ------------ | ----------------------------------------------------------------- |
-| `CONTINUOUS` | Always included                                                   |
-| `MOTION`     | Show when detected motion within the last 30 seconds are included |
-| `OBJECTS`    | Shown if an active object tracked within the last 30 seconds      |
+| Command       | Description                                                      |
+| ------------- | ---------------------------------------------------------------- |
+| `CONTINUOUS`  | Always included                                                  |
+| `MOTION`      | Shown if motion was detected within the last 30 seconds          |
+| `ALL_OBJECTS` | Shown if a tracked object was present within the last 30 seconds |
+| `ALERTS`      | Shown while an alert review item is in progress                  |
+| `DETECTIONS`  | Shown while a detection review item is in progress               |
+| `NONE`        | Never included                                                   |

-### `frigate/<camera_name>/birdseye_mode/state`
+### `frigate/<camera_name>/birdseye_modes/state`

-Topic with current state of the Birdseye mode for a camera. Published values are `CONTINUOUS`, `MOTION`, `OBJECTS`.
+Topic with the current Birdseye activity types for a camera. Multiple enabled types are published as a comma-separated value in the order `CONTINUOUS`, `MOTION`, `ALL_OBJECTS`, `ALERTS`, `DETECTIONS`. `NONE` is published when no activity types are enabled.

 ### `frigate/<camera_name>/notifications/set`

-Topic to turn notifications on and off. Expected values are `ON` and `OFF`.
+Topic to turn notifications for a camera on and off. Expected values are `ON` and `OFF`.
+
+`ON` is ignored unless notifications are enabled in the config for the camera. This is not persisted across Frigate restarts. It is the same control the UI labels **Suspend until restart**.

 ### `frigate/<camera_name>/notifications/state`

-Topic with current state of notifications. Published values are `ON` and `OFF`.
+Topic with current state of notifications. Published values are `ON` and `OFF`. This is the authoritative topic for whether a camera will notify.

 ### `frigate/<camera_name>/notifications/suspend`

-Topic to suspend notifications for a certain number of minutes. Expected value is an integer.
+Topic to suspend notifications for a certain number of minutes. Expected value is an integer. Separate from `notifications/set`: it does not change `notifications/state`, and is ignored while notifications are off.

 ### `frigate/<camera_name>/notifications/suspended`

-Topic with timestamp that notifications are suspended until. Published value is a UNIX timestamp, or 0 if notifications are not suspended.
+Topic with timestamp that notifications are suspended until. Published value is a UNIX timestamp, or 0 if there is no timed suspension.
+
+`0` does not mean notifications are enabled: `notifications/set` `OFF` clears the timed suspension, so this publishes `0` while `notifications/state` is `OFF`.
@@ -59,13 +59,12 @@ You can view all of your submitted images at [https://plus.frigate.video](https:

 Once you have [requested your first model](../plus/first_model.md) and gotten your own model ID, it can be used with a special model path. No other information needs to be configured for Frigate+ models because it fetches the remaining config from Frigate+ automatically.

-You can either choose the new model from the <NavPath path="Settings > System > Detectors and model" /> pane in the Frigate UI (the **Frigate+ Model** tab), or manually set the model at the root level in your config:
+You can either choose the new model from the <NavPath path="Settings > System > Detection models" /> pane in the Frigate UI (on the **Frigate+** tab of the model you want to change), or set it on that model in your config:

 ```yaml
-detectors: ...
-
-model:
-  path: plus://<your_model_id>
+models:
+  - devices: ...
+    path: plus://<your_model_id>
 ```

 :::note
@@ -79,10 +78,11 @@ Models are downloaded into the `/config/model_cache` folder and only downloaded
 If needed, you can override the labelmap for Frigate+ models. This is not recommended as renaming labels will break the Submit to Frigate+ feature if the labels are not available in Frigate+.

 ```yaml
-model:
-  path: plus://<your_model_id>
-  labelmap:
-    3: animal
-    4: animal
-    5: animal
+models:
+  - devices: ...
+    path: plus://<your_model_id>
+    labelmap:
+      3: animal
+      4: animal
+      5: animal
 ```
@@ -23,7 +23,7 @@ The [Advanced Camera Card](https://card.camera/#/README) is a Home Assistant das

 ## [Double Take](https://github.com/skrashevich/double-take)

-[Double Take](https://github.com/skrashevich/double-take) provides an unified UI and API for processing and training images for facial recognition.
+[Double Take](https://github.com/skrashevich/double-take) provides a unified UI and API for processing and training images for facial recognition.
 It supports automatically setting the sub labels in Frigate for person objects that are detected and recognized.
 This is a fork (with fixed errors and new features) of [original Double Take](https://github.com/jakowenko/double-take) project which, unfortunately, isn't being maintained by author.

@@ -31,6 +31,10 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht

 [Frigate Notify](https://github.com/0x2142/frigate-notify) is a simple app designed to send notifications from Frigate to your favorite platforms. Intended to be used with standalone Frigate installations - Home Assistant not required, MQTT is optional but recommended.

+## [Frigate Notify Alert](https://github.com/Sysoev86/frigate-notify-alert)
+
+[Frigate Notify Alert](https://github.com/Sysoev86/frigate-notify-alert) sends Frigate events to Telegram as a photo + video media group. It supports multiple camera groups (each notifying its own chat), optional zone filtering (notify only when an object enters a chosen zone), and in-chat buttons to pause notifications for a set time. Works with standalone Frigate over MQTT; Home Assistant not required.
+
 ## [Frigate Snap-Sync](https://github.com/thequantumphysicist/frigate-snap-sync/)

 [Frigate Snap-Sync](https://github.com/thequantumphysicist/frigate-snap-sync/) is a program that works in tandem with Frigate. It responds to Frigate when a snapshot or a review is made (and more can be added), and uploads them to one or more remote server(s) of your choice.
@@ -49,7 +53,7 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht

 ## [Scrypted - Frigate bridge plugin](https://github.com/apocaliss92/scrypted-frigate-bridge)

-[Scrypted - Frigate bridge](https://github.com/apocaliss92/scrypted-frigate-bridge) is an plugin that allows to ingest Frigate detections, motion, videoclips on Scrypted as well as provide templates to export rebroadcast configurations on Frigate.
+[Scrypted - Frigate bridge](https://github.com/apocaliss92/scrypted-frigate-bridge) is a plugin that allows you to ingest Frigate detections, motion, videoclips on Scrypted as well as provide templates to export rebroadcast configurations on Frigate.

 ## [Strix](https://github.com/eduard256/Strix)

@@ -19,7 +19,7 @@ For the best results, follow these guidelines. You may also want to review the d

 ## AI suggested labels

-If you have an active Frigate+ subscription, new uploads will be scanned for the objects configured for you camera and you will see suggested labels as light blue boxes when annotating in Frigate+. These suggestions are processed via a queue and typically complete within a minute after uploading, but processing times can be longer.
+If you have an active Frigate+ subscription, new uploads will be scanned for the objects configured for your camera and you will see suggested labels as light blue boxes when annotating in Frigate+. These suggestions are processed via a queue and typically complete within a minute after uploading, but processing times can be longer.

 ![Suggestions](/img/plus/suggestions.webp)

@@ -3,6 +3,10 @@ id: first_model
 title: Requesting your first model
 ---

+import ConfigTabs from "@site/src/components/ConfigTabs";
+import TabItem from "@theme/TabItem";
+import NavPath from "@site/src/components/NavPath";
+
 ## Step 1: Upload and annotate your images

 Before requesting your first model, you will need to upload and verify at least 10 images to Frigate+. The more images you upload, annotate, and verify the better your results will be. Most users start to see very good results once they have at least 100 verified images per camera. Keep in mind that varying conditions should be included. You will want images from cloudy days, sunny days, dawn, dusk, and night. Refer to the [integration docs](../integrations/plus.md#generate-an-api-key) for instructions on how to easily submit images to Frigate+ directly from Frigate.
@@ -16,36 +20,67 @@ For more detailed recommendations, you can refer to the docs on [annotating](./a
 Once you have an initial set of verified images, you can request a model on the Models page. For guidance on choosing a model type, refer to [this part of the documentation](./index.md#available-model-types). If you are unsure which type to request, you can test the base model for each version from the "Base Models" tab. Each model request requires 1 of the 12 trainings that you receive with your annual subscription. This model will support all [label types available](./index.md#available-label-types) even if you do not submit any examples for those labels. Model creation can take up to 36 hours.
 ![Plus Models Page](/img/plus/plus-models.jpg)

-## Step 3: Set your model id in the config
+## Step 3: Set your model

 You will receive an email notification when your Frigate+ model is ready.
 ![Model Ready Email](/img/plus/model-ready-email.jpg)

 Models available in Frigate+ can be used with a special model path. No other information needs to be configured because it fetches the remaining config from Frigate+ automatically.

+<ConfigTabs>
+<TabItem value="ui">
+
+Navigate to <NavPath path="Settings > System > Detection models" />. On the model you want to change, choose the **Frigate+** tab and select your new Frigate+ model from the **Available Frigate+ models** dropdown, then click **Save**. Restart Frigate to apply the change.
+
+</TabItem>
+<TabItem value="yaml">
+
 ```yaml
-detectors: ...
-
-model:
-  path: plus://<your_model_id>
+models:
+  - devices: ...
+    path: plus://<your_model_id>
 ```

-:::note
-
-Model IDs are not secret values and can be shared freely. Access to your model is protected by your API key.
-
-:::
-
 :::tip

 When setting the plus model id, all other fields should be removed as these are configured automatically with the Frigate+ model config

 :::

+</TabItem>
+</ConfigTabs>
+
+:::note
+
+Model IDs are not secret values and can be shared freely. Access to your model is protected by your API key.
+
+:::
+
 ## Step 4: Adjust your object filters for higher scores

 Frigate+ models generally have much higher scores than the default model provided in Frigate. You will likely need to increase your `threshold` and `min_score` values. Here is an example of how these values can be refined, but you should expect these to evolve as your model improves. For more information about how `threshold` and `min_score` are related, see the docs on [object filters](../configuration/object_filters.md#object-scores).

+<ConfigTabs>
+<TabItem value="ui">
+
+Navigate to <NavPath path="Settings > Global configuration > Objects" />. Under **Object filters**, set **Min Score** and **Threshold** for each object type, then click **Save**.
+
+| Object            | Min Score | Threshold |
+| ----------------- | --------- | --------- |
+| **dog**           | .7        | .9        |
+| **cat**           | .65       | .8        |
+| **face**          | .7        |           |
+| **package**       | .65       | .9        |
+| **license_plate** | .6        |           |
+| **amazon**        | .75       |           |
+| **ups**           | .75       |           |
+| **fedex**         | .75       |           |
+| **person**        | .65       | .85       |
+| **car**           | .65       | .85       |
+
+</TabItem>
+<TabItem value="yaml">
+
 ```yaml
 objects:
  filters:
@@ -75,3 +110,6 @@ objects:
      min_score: .65
      threshold: .85
 ```
+
+</TabItem>
+</ConfigTabs>
@@ -0,0 +1,238 @@
+---
+id: common_errors
+title: Common Error Messages
+---
+
+import FaqItem from "@site/src/components/FaqItem";
+
+This page is an index of error messages you might see in Frigate's logs, what each one means, and where to go next. It is organized by the kind of problem, not by which component logged the message.
+
+Two things to know before you start:
+
+- **Many of these messages come from FFmpeg, go2rtc, GPU drivers, or the operating system, not from Frigate itself.** Frigate captures and re-logs their output, so the log level shown in the Frigate UI does not always reflect the original severity.
+- **Wrapped errors put the real cause on the next line.** When Frigate logs a generic message like `Error occurred when attempting to maintain recording cache`, the actual exception is logged immediately after it. When a camera's FFmpeg process exits, Frigate logs `The following ffmpeg logs include the last 100 lines prior to exit` and dumps that camera's FFmpeg output. Always read those lines, they are where the answer usually is.
+
+## Camera connection and streams
+
+<FaqItem id="connection-refused-no-route-to-host-401-404" question="Connection refused / No route to host / 401 Unauthorized / 404 Not Found">
+
+These are FFmpeg errors about reaching the camera (or the go2rtc restream). `Connection refused` and `No route to host` mean nothing is listening at that address or the host is unreachable; `401 Unauthorized` is wrong credentials; `404 Not Found` is a wrong stream path (or a `restream` input pointing at a go2rtc stream name that does not exist). A camera that has hit its concurrent-connection limit can also return `refused` or `401` on a URL that works in VLC.
+
+See [go2rtc troubleshooting](/troubleshooting/go2rtc#1-read-the-go2rtc-logs) for how to isolate the stream.
+
+</FaqItem>
+
+<FaqItem id="no-frames-received-in-20-seconds" question="No frames received from <camera> in 20 seconds. Exiting ffmpeg...">
+
+FFmpeg is running but has stopped delivering video for 20 seconds, so Frigate's camera watchdog restarts it. The stream connected at least once, then went quiet: a camera reboot, a network drop, the camera evicting the connection, or a stalled decoder. If it repeats on a loop, the stream is unstable.
+
+</FaqItem>
+
+<FaqItem id="ffmpeg-process-crashed-unexpectedly" question="Ffmpeg process crashed unexpectedly for <camera>">
+
+The detect FFmpeg process exited on its own. This message is only the notification; the cause is in the 100 FFmpeg log lines Frigate dumps right after it (look for a `Failed to sync surface`, `Connection refused`, codec, or audio error in that block). Related watchdog messages include `<camera> exceeded fps limit`, which means the camera is delivering frames faster than `detect.fps` (usually a camera whose real frame rate differs from what is configured).
+
+</FaqItem>
+
+<FaqItem id="non-monotonically-increasing-dts" question="Non-monotonic DTS / non monotonically increasing dts to muxer / Queue input is backward in time">
+
+These are FFmpeg messages indicating the camera sent packets with out-of-order timestamps, either on the video or the audio stream. Timestamp jitter like this is common with WiFi cameras and restreamed or proxied sources; other causes are a camera "Smart Codec" / H.264+ / H.265+ mode or a camera clock that jumps. A sustained flood of these messages usually precedes the stream stalling and the watchdog restarting FFmpeg.
+
+In most cases, the fix is to improve the network, reduce system resource usage, or switch to non-WiFi cameras. In general, WiFi cameras are [not recommended](https://ipcamtalk.com/threads/multiple-cameras-high-bandwidth.77100/#post-861110).
+
+On the video stream, this can affect recordings: because they are copied without re-encoding, FFmpeg cannot fix the timestamps, and the segment muxer often splits early, producing one-second segments and a cache backlog. See [Recordings: segments are only 1 second long](/troubleshooting/recordings#segments-are-only-1-second-long).
+
+On the audio stream, the messages can come from the output's audio encoding. If the audio stream is the problem, it may help to have go2rtc transcode it by adding `#audio=aac` to the camera's go2rtc stream to produce clean timestamps for everything consuming the restream.
+
+</FaqItem>
+
+<FaqItem id="bad-cseq" question="RTP: PT=xx: bad cseq (packet loss / reordering)">
+
+An FFmpeg message meaning RTP packets arrived out of sequence, which almost always means the stream is using UDP transport. Frigate's RTSP presets force TCP, so seeing this points at a custom `input_args`, `preset-rtsp-udp`, or a go2rtc source that is not using TCP. Switch to TCP unless your camera is [UDP-only](/configuration/camera_specific#udp-only-cameras).
+
+</FaqItem>
+
+<FaqItem id="error-while-decoding-mb-non-existing-pps" question="error while decoding MB / non-existing PPS referenced (corrupt frames)">
+
+FFmpeg decoder messages meaning the received video bitstream was incomplete or damaged. A few of these at every stream start are normal (the decoder connected before the first keyframe) and Frigate discards them. A continuous stream of them means real packet loss, from Wi-Fi or a saturated link, an overloaded camera, or an FFmpeg restart loop caused by another problem. Fix the underlying instability rather than the message.
+
+</FaqItem>
+
+<FaqItem id="could-not-find-codec-parameters" question="Could not find codec parameters for stream ... unspecified size">
+
+An FFmpeg message meaning it probed the stream but never saw enough decodable video to determine the frame size, often because the probe window ended before the first keyframe on a long-GOP stream, or because the stream is not delivering usable video. If it is a Reolink HTTP stream, use `preset-http-reolink`, which raises the probe size for exactly this case.
+
+</FaqItem>
+
+## Recording
+
+<FaqItem id="no-new-recording-segments" question="No new recording segments were created for <camera> in the last 120s">
+
+Frigate's record watchdog is restarting the record FFmpeg process because no valid segment has reached the cache. This means the record stream is not connecting or the segments are being rejected (see the audio-codec entry below).
+
+See [Recordings: the record stream isn't connecting](/troubleshooting/recordings#the-record-stream-isnt-connecting).
+
+</FaqItem>
+
+<FaqItem id="invalid-or-missing-video-stream-in-segment" question="Invalid or missing video stream in segment. Discarding.">
+
+A cached recording segment failed validation (no readable video stream) and was deleted. The most common cause is a segment that was truncated because the record FFmpeg process was killed mid-write, so this often appears alongside, and as a consequence of, the record-stream restarts above. A segment containing only audio triggers it too.
+
+</FaqItem>
+
+<FaqItem id="incompatible-audio-codec" question="Recordings silently fail to save (incompatible audio codec)">
+
+Some camera audio codecs (G.711 variants such as `pcm_alaw` and `pcm_mulaw`) cannot be stored in an MP4 container, so segments never finalize even though live view works.
+
+See [Recordings: incompatible audio codec](/troubleshooting/recordings#incompatible-audio-codec-recordings-silently-fail-to-save) for the FFmpeg preset that transcodes the audio to AAC.
+
+</FaqItem>
+
+<FaqItem id="error-maintaining-recording-cache" question="Error occurred when attempting to maintain recording cache">
+
+A generic wrapper; the real exception is on the next log line. Frequently it is `[Errno 28] No space left on device` or `[Errno 17] File exists` on a network share.
+
+See [Recordings cache warnings and errors](/troubleshooting/recordings#i-see-the-message-error--error-occurred-when-attempting-to-maintain-recording-cache), which covers this message and the common `Errno` cases.
+
+</FaqItem>
+
+## Hardware acceleration
+
+<FaqItem id="failed-to-sync-surface" question="Failed to sync surface / Failed to download frame: -5 / Error while filtering">
+
+A VAAPI/QSV hardware frame-sync failure between FFmpeg and the GPU driver, not a Frigate bug. It usually appears when the detect stream is being scaled or decoded on the GPU.
+
+See [GPU: Failed to download frame: -5](/troubleshooting/gpu#failed-to-download-frame--5), which lists the fixes in order (switch VAAPI/QSV preset, change `LIBVA_DRIVER_NAME`, use an H.264 substream, match detect resolution and fps to the stream).
+
+</FaqItem>
+
+<FaqItem id="no-decoder-surfaces-left" question="No decoder surfaces left / Can't allocate a surface">
+
+Both mean the GPU ran out of decode surfaces: `No decoder surfaces left` is NVIDIA NVDEC, `Can't allocate a surface` is Intel QSV. This is surface-pool exhaustion, typically from too many concurrent hardware-decoded cameras on one GPU (consumer NVIDIA cards have a driver-enforced limit on simultaneous decode sessions). Reduce the number of cameras decoding on that GPU, decode some on the CPU, or move to hardware without the session cap.
+
+</FaqItem>
+
+<FaqItem id="nvidia-container-cli-nvml-error" question="nvidia-container-cli: nvml error: driver not loaded">
+
+This comes from the NVIDIA container runtime while starting the container, not from Frigate, and the container never starts. The NVIDIA driver is not loaded on the host. Confirm `nvidia-smi` works on the host itself (not inside the container) before troubleshooting Frigate. In a VM or LXC, the driver must be available inside the guest. See [Hardware: Nvidia GPU](/configuration/hardware_acceleration_video).
+
+</FaqItem>
+
+## Detectors and models
+
+<FaqItem id="illegal-instruction" question="Illegal instruction (core dumped)">
+
+The process was killed by the CPU for executing an unsupported instruction. There are two distinct causes in Frigate:
+
+- **A Coral EdgeTPU** on a newer kernel with an outdated gasket driver. See [EdgeTPU: Illegal instruction](/troubleshooting/edgetpu#attempting-to-load-tpu-as-pci--fatal-python-error-illegal-instruction).
+- **A CPU without AVX/AVX2**, when enabling semantic search, face recognition, license plate recognition, classification, or audio transcription. These features use libraries compiled with AVX and crash immediately on CPUs that lack it (commonly Intel Celeron/Pentium before the 2020 Tiger Lake generation). See the [CPU requirements](/frigate/planning_setup#cpu).
+
+</FaqItem>
+
+<FaqItem id="onnx-invalidprotobuf" question="ONNX Runtime InvalidProtobuf / failed to load model">
+
+ONNX Runtime could not parse the model file. The file exists but its contents are not a valid ONNX model, usually a corrupted or interrupted download in `model_cache`, or the wrong file pointed at by a model's `path`. Delete the cached model file so Frigate re-downloads it, and confirm the model's `path` points at an actual `.onnx` model. See [ONNX detector configuration](/configuration/object_detectors#onnx).
+
+</FaqItem>
+
+<FaqItem id="cuda-failure-999-901" question="CUDA failure 999 / CUDA failure 901">
+
+ONNX Runtime CUDA errors. `999` (`cudaErrorUnknown`) is a general, unrecoverable CUDA context failure, usually a driver/runtime version mismatch between the host and the container or a GPU in a bad state. `901` is a CUDA-graph capture error, which points at a custom model whose operations are not capture-safe. For `999`, align the host driver with the container's CUDA version and confirm the GPU is healthy.
+
+</FaqItem>
+
+<FaqItem id="openvino-no-supported-devices" question="Can't get OPTIMIZATION_CAPABILITIES property as no supported devices found">
+
+OpenVINO could not find the configured device (usually `GPU` or `NPU`). Most often the `/dev/dri` render node is not passed into the container, or the wrong render node is mapped when an iGPU and a discrete GPU coexist.
+
+See [GPU: no supported devices found](/troubleshooting/gpu#cant-get-optimization_capabilities-property-as-no-supported-devices-found).
+
+</FaqItem>
+
+## Memory and storage
+
+<FaqItem id="fatal-python-error-bus-error" question="Fatal Python error: Bus error">
+
+Frigate ran out of shared memory (`/dev/shm`). The container's `shm_size` is too small for the number and resolution of your detect streams, or you added cameras after startup without increasing it.
+
+See [Calculating required shm-size](/frigate/installation#calculating-required-shm-size). If you cannot increase `shm_size`, lowering the `SHM_MAX_FRAMES` environment variable reduces how many frames Frigate buffers per camera.
+
+</FaqItem>
+
+<FaqItem id="errno-28-no-space-left" question="[Errno 28] No space left on device">
+
+A filesystem is full: the recordings volume (`/media/frigate`), the cache tmpfs (`/tmp/cache`), or `/dev/shm`. Check which one, and note that inode exhaustion can produce this while `df -h` still shows free space.
+
+See [Recordings: No space left on device](/troubleshooting/recordings#i-see-the-message-error--error-occurred-when-attempting-to-maintain-recording-cache).
+
+</FaqItem>
+
+<FaqItem id="container-exits-with-no-logs" question="The container exits or restarts with no error in the logs">
+
+A silent exit is usually the host or container out-of-memory killer. Because `/dev/shm` and `/tmp/cache` are memory-backed, they count against the container's memory limit, so aggressive shm or cache sizing can trigger it. Give the container more memory, or reduce shm/cache sizing, and check the host's OOM messages (`dmesg`).
+
+</FaqItem>
+
+## Database
+
+<FaqItem id="database-is-locked" question="database is locked">
+
+SQLite could not acquire the write lock. Frigate's timeout already scales with camera count, so under normal local-disk operation this essentially only happens when the database is on a network share (SMB/NFS), where file locking is unreliable, or when two instances point at the same file.
+
+See [Database is locked](/troubleshooting/faqs#error-database-is-locked).
+
+</FaqItem>
+
+<FaqItem id="database-disk-image-is-malformed" question="database disk image is malformed">
+
+The SQLite database file is corrupted, typically after hard power loss, a network-share database, or a filesystem with unsafe write semantics. Frigate does not repair it automatically, but the database can usually be recovered by hand.
+
+**Stop Frigate first**, then work on the database file directly (by default `/config/frigate.db`). Start by checking what is actually wrong:
+
+```bash
+sqlite3 frigate.db "PRAGMA integrity_check;"
+```
+
+If the only problems reported are index-related (lines such as `row 14 missing from index recordings_path` or `non-unique entry in index ...`), rebuilding the indexes is usually enough and is the least destructive fix:
+
+```bash
+sqlite3 frigate.db "REINDEX;"
+```
+
+If the integrity check reports page or byte-level corruption instead (for example `Multiple uses for byte 2706 of page 142272`), dump the readable contents into a new database:
+
+```bash
+# dump what can still be read
+sqlite3 frigate.db .dump > frigate.dump
+
+# keep the corrupt file, then rebuild from the dump
+mv frigate.db frigate.db.bak
+cat frigate.dump | sqlite3 frigate.db
+
+# confirm the rebuilt database is clean, this should print "ok"
+sqlite3 frigate.db "PRAGMA integrity_check;"
+```
+
+Rows stored in the corrupted pages cannot be recovered, so expect to lose some tracked objects, review items, or thumbnails. Recordings themselves are files on disk and are not affected.
+
+As a last resort, stop Frigate, delete `frigate.db`, and restart. Frigate recreates it, but existing recordings lose all of their metadata. If a `backup.db` exists next to your database, Frigate wrote it before the last schema migration and restoring it recovers everything up to that point.
+
+Repeat corruption usually points at the underlying storage: move the database off a network share, and on Raspberry Pi check power delivery and the SD card or SSD.
+
+</FaqItem>
+
+## Startup and web access
+
+<FaqItem id="unable-to-start-frigate-in-safe-mode" question="Unable to start Frigate in safe mode / Starting Frigate in safe mode">
+
+When your config fails validation at startup, Frigate prints the validation errors (with line numbers), then starts in **safe mode**: a minimal configuration with no cameras and MQTT disabled, so the UI stays reachable. In safe mode the only available page is the Config Editor, which shows the validation errors so you can fix them, then save and restart. Note that recording retention and storage cleanup do **not** run while in safe mode, so do not leave a low-disk system sitting in it.
+
+`Unable to start Frigate in safe mode` means even the minimal config failed, which points at an error in your `auth`, `proxy`, or `database` section, or a config file that is not valid YAML at all. Safe mode is not sticky; fix the config and restart and Frigate returns to normal.
+
+</FaqItem>
+
+<FaqItem id="502-bad-gateway" question="502 Bad Gateway / connection refused to 127.0.0.1:5001">
+
+The web server is up but the Frigate backend (port 5001) is not answering yet. By far the most common reason is that the page was loaded during startup: the API binds last, after database migrations (which can take minutes on a large database), model downloads, and process startup, while the web server is already serving. Wait for startup to finish. If it persists, the backend has failed to start, and the reason is earlier in the logs. This also explains a `connection refused to 127.0.0.1:5001` seen while loading `/ws`, because every authenticated request first makes an auth subrequest to that port.
+
+</FaqItem>
@@ -3,7 +3,31 @@ id: cpu
 title: High CPU Usage
 ---

-High CPU usage can impact Frigate's performance and responsiveness. This guide outlines the most effective configuration changes to help reduce CPU consumption and optimize resource usage.
+High CPU usage can impact Frigate's performance and responsiveness. This guide explains how to interpret the CPU values Frigate reports and outlines the most effective configuration changes to help reduce CPU consumption and optimize resource usage.
+
+## Understanding Frigate's Reported CPU Usage
+
+Frigate's CPU percentages often look much higher than what the host reports. Usually both numbers are correct and are simply measured against different denominators, so confirm you actually have a problem before tuning anything.
+
+### Per-process values are relative to a single core
+
+The values Frigate reports for FFmpeg, capture, detect, detector, and other processes follow the same convention as `top`: 100% means one CPU core is fully saturated, not that the whole system is saturated. A multithreaded process such as FFmpeg can legitimately report well over 100%.
+
+Host and hypervisor tools instead report a percentage of the machine's total capacity across all cores. This includes `docker stats`, the `htop` summary, the Proxmox summary graph, the Unraid dashboard, Synology Resource Monitor, and Home Assistant's system monitor sensors. To reconcile the two:
+
+```
+host percentage ≈ (sum of Frigate's process percentages) / (number of cores)
+```
+
+On a 4 core system, an FFmpeg process reporting 100% is consuming one quarter of the machine, so the host will show roughly 25 to 30% once the remaining Frigate processes are included. That same 100% on a 16 core system is about 6%. Frigate's own warning thresholds use the per-core convention as well, so an FFmpeg process is flagged at 20% of a single core, not 20% of the system.
+
+### Instantaneous samples and averages measure different things
+
+Frigate collects stats every 15 seconds, and the `cpu` value covers only the interval since the previous collection. The `cpu_average` value in the stats API and MQTT payload is the average across the entire life of the process, and it is what the high CPU usage warnings are based on. Host dashboards generally plot data averaged over a longer window, so a single Frigate sample can show a peak that a host graph never displays. A process that has just started, such as FFmpeg after a camera reconnect, reports 0 until it has been sampled twice.
+
+### The system-wide value depends on what the container can see
+
+The system CPU value is read from `/proc/stat`. Under Docker that file belongs to the host, so the value covers the entire machine including workloads unrelated to Frigate, and it will not match `docker stats` for the Frigate container. Under an LXC container, lxcfs virtualizes `/proc/stat` and the value reflects only the cores assigned to the container. In a virtual machine, the guest sees only its assigned vCPUs while the hypervisor divides by every physical thread on the node, so guest and host percentages will not agree even when both are accurate.

 ## 1. Hardware Acceleration for Video Decoding

@@ -44,7 +68,7 @@ Choosing the right detector for your hardware is the single most important facto

 ### Understanding Detector Performance

-Frigate uses motion detection as a first-line check before running expensive object detection, as explained in the [motion detection documentation](../configuration/motion_detection). When motion is detected, Frigate creates a "region" (the green boxes in the debug viewer) and sends it to the detector. The detector's inference speed determines how many detections per second your system can handle.
+Frigate uses motion detection as a first-line check before running expensive object detection, as explained in the [motion detection documentation](../configuration/motion_detection). When motion is detected, Frigate creates a "region" (the green boxes in the [debug viewer](/usage/live#the-single-camera-view)) and sends it to the detector. The detector's inference speed determines how many detections per second your system can handle.

 **Calculating Detector Capacity:** Your detector has a finite capacity measured in detections per second. With an inference speed of 10ms, your detector can handle approximately 100 detections per second (1000ms / 10ms = 100).If your cameras collectively require more than this capacity, you'll experience delays, missed detections, or the system will fall behind.

@@ -58,7 +82,6 @@ When a single detector cannot keep up with your camera count, some detector type

 For detailed instructions on configuring multiple detectors, see the [Object Detectors documentation](../configuration/object_detectors).

-
 **When to add a second detector:**

 - Skipped FPS is consistently > 0 even during normal activity
@@ -70,4 +93,22 @@ The model you use significantly impacts detector performance. Frigate provides d
 **Model Size Trade-offs:**

 - Smaller models (320x320): Faster inference, Frigate is specifically optimized for a 320x320 size model.
- Larger models (640x640): Slower inference, can sometimes have higher accuracy on very large objects that take up a majority of the frame.
+- Larger models (640x640): Slower inference, can sometimes have higher accuracy on very large objects that take up a majority of the frame.
+
+For more detail on picking the right size, see [Choosing a model size](../configuration/object_detectors.md#choosing-a-model-size).
+
+## 3. Reducing Detector CPU Usage
+
+**Priority: High**
+
+The **Detector CPU Usage** metric measures the CPU spent converting frames into the tensor format the model expects and post-processing the model's output. It does not include inference, so this value can be high even when you've configured a GPU, NPU, or Coral for object detection.
+
+This metric scales with how many detections per second Frigate runs and how expensive each one is to prepare. Tuning [motion detection](../configuration/motion_detection) is usually the first recommendation to reduce the number of detections. Additionally, you can:
+
+- **Lower `detect -> fps`.** 5 is the recommended value for nearly all cameras. Running at 10 doubles the frames eligible for detection and is one of the largest contributors to this metric.
+- **Use a 320x320 model.** A 640x640 model has 4 times as many pixels to transpose, convert, and copy on every inference.
+- **Prefer a model that takes integer input.** Models configured with `input_dtype: float` require each frame to be converted to float32 and normalized on the CPU first. Models taking `int` input, such as the tflite models used by the Edge TPU, skip that step.
+- **Do not match the detect resolution to the model resolution.** The detect stream should match your camera's aspect ratio, for example `1280x720`, not the model's input size. Frigate crops and scales regions of motion itself, so an oversized detect stream only adds work.
+- **Tune stationary object behavior.** Objects that never settle into a stationary state are re-detected continuously. Raising `detect -> stationary -> interval` reduces how often detection runs on objects that are already parked. See [stationary objects](../configuration/stationary_objects).
+
+Adding [more detector instances](#multiple-detector-instances) spreads this work across more CPU cores, but does not reduce the total CPU used.