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d8d9452179
Add the schema backing per-monitor object detection and the AI dataset/ model/class management UI: - Monitors gains AnalysisImageOpacity and ObjectDetection, ObjectDetectionModel, ObjectDetectionObjectThreshold, ObjectDetectionNMSThreshold columns. - New tables AI_Datasets, AI_Models, AI_Object_Classes, AI_Detection_Settings and AI_Detections. - Seed the COCO 2017 dataset (80 classes) and default per-class detection settings via db/coco_dataset.sql. Existing installs get zm_update-1.39.17.sql, which is idempotent and adds the columns with their final VARCHAR(16) ObjectDetection shape directly (no enum-churn intermediates). Fresh installs create the same objects from zm_create.sql.in sourcing AI_Models.sql and coco_dataset.sql. Both paths were verified to produce identical schema. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
111 lines
3.5 KiB
SQL
111 lines
3.5 KiB
SQL
--
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-- Pre-populate COCO 2017 Dataset with 80 object classes
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--
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-- Insert COCO 2017 Dataset
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INSERT IGNORE INTO AI_Datasets (Id, Name, Description, Version, NumClasses) VALUES
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(1, 'COCO', 'Microsoft Common Objects in Context', '2017', 80);
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-- Insert all 80 COCO object classes with correct indices (0-79)
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INSERT IGNORE INTO AI_Object_Classes (DatasetId, ClassName, ClassIndex, Description) VALUES
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(1, 'person', 0, 'Person'),
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(1, 'bicycle', 1, 'Bicycle'),
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(1, 'car', 2, 'Car'),
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(1, 'motorcycle', 3, 'Motorcycle'),
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(1, 'airplane', 4, 'Airplane'),
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(1, 'bus', 5, 'Bus'),
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(1, 'train', 6, 'Train'),
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(1, 'truck', 7, 'Truck'),
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(1, 'boat', 8, 'Boat'),
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(1, 'traffic light', 9, 'Traffic light'),
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(1, 'fire hydrant', 10, 'Fire hydrant'),
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(1, 'stop sign', 11, 'Stop sign'),
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(1, 'parking meter', 12, 'Parking meter'),
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(1, 'bench', 13, 'Bench'),
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(1, 'bird', 14, 'Bird'),
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(1, 'cat', 15, 'Cat'),
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(1, 'dog', 16, 'Dog'),
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(1, 'horse', 17, 'Horse'),
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(1, 'sheep', 18, 'Sheep'),
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(1, 'cow', 19, 'Cow'),
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(1, 'elephant', 20, 'Elephant'),
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(1, 'bear', 21, 'Bear'),
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(1, 'zebra', 22, 'Zebra'),
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(1, 'giraffe', 23, 'Giraffe'),
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(1, 'backpack', 24, 'Backpack'),
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(1, 'umbrella', 25, 'Umbrella'),
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(1, 'handbag', 26, 'Handbag'),
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(1, 'tie', 27, 'Tie'),
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(1, 'suitcase', 28, 'Suitcase'),
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(1, 'frisbee', 29, 'Frisbee'),
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(1, 'skis', 30, 'Skis'),
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(1, 'snowboard', 31, 'Snowboard'),
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(1, 'sports ball', 32, 'Sports ball'),
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(1, 'kite', 33, 'Kite'),
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(1, 'baseball bat', 34, 'Baseball bat'),
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(1, 'baseball glove', 35, 'Baseball glove'),
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(1, 'skateboard', 36, 'Skateboard'),
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(1, 'surfboard', 37, 'Surfboard'),
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(1, 'tennis racket', 38, 'Tennis racket'),
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(1, 'bottle', 39, 'Bottle'),
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(1, 'wine glass', 40, 'Wine glass'),
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(1, 'cup', 41, 'Cup'),
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(1, 'fork', 42, 'Fork'),
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(1, 'knife', 43, 'Knife'),
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(1, 'spoon', 44, 'Spoon'),
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(1, 'bowl', 45, 'Bowl'),
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(1, 'banana', 46, 'Banana'),
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(1, 'apple', 47, 'Apple'),
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(1, 'sandwich', 48, 'Sandwich'),
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(1, 'orange', 49, 'Orange'),
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(1, 'broccoli', 50, 'Broccoli'),
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(1, 'carrot', 51, 'Carrot'),
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(1, 'hot dog', 52, 'Hot dog'),
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(1, 'pizza', 53, 'Pizza'),
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(1, 'donut', 54, 'Donut'),
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(1, 'cake', 55, 'Cake'),
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(1, 'chair', 56, 'Chair'),
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(1, 'couch', 57, 'Couch'),
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(1, 'potted plant', 58, 'Potted plant'),
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(1, 'bed', 59, 'Bed'),
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(1, 'dining table', 60, 'Dining table'),
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(1, 'toilet', 61, 'Toilet'),
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(1, 'tv', 62, 'TV'),
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(1, 'laptop', 63, 'Laptop'),
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(1, 'mouse', 64, 'Mouse'),
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(1, 'remote', 65, 'Remote'),
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(1, 'keyboard', 66, 'Keyboard'),
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(1, 'cell phone', 67, 'Cell phone'),
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(1, 'microwave', 68, 'Microwave'),
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(1, 'oven', 69, 'Oven'),
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(1, 'toaster', 70, 'Toaster'),
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(1, 'sink', 71, 'Sink'),
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(1, 'refrigerator', 72, 'Refrigerator'),
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(1, 'book', 73, 'Book'),
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(1, 'clock', 74, 'Clock'),
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(1, 'vase', 75, 'Vase'),
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(1, 'scissors', 76, 'Scissors'),
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(1, 'teddy bear', 77, 'Teddy bear'),
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(1, 'hair drier', 78, 'Hair drier'),
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(1, 'toothbrush', 79, 'Toothbrush');
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-- Create default detection settings for common security monitoring objects
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-- Only enable person and vehicles by default
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INSERT IGNORE INTO AI_Detection_Settings (MonitorId, ObjectClassId, Enabled, ReportDetection, ConfidenceThreshold, BoxColor)
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SELECT NULL, Id, 1, 1,
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CASE
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WHEN ClassName = 'person' THEN 60
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ELSE 50
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END,
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CASE
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WHEN ClassName = 'person' THEN '#FF0000'
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WHEN ClassName = 'car' THEN '#0000FF'
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WHEN ClassName = 'truck' THEN '#0066FF'
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WHEN ClassName = 'bus' THEN '#0099FF'
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WHEN ClassName = 'motorcycle' THEN '#00CCFF'
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ELSE '#808080'
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END
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FROM AI_Object_Classes
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WHERE DatasetId = (SELECT Id FROM AI_Datasets WHERE Name = 'COCO' LIMIT 1)
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AND ClassName IN ('person', 'car', 'truck', 'bus', 'motorcycle');
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