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bbd263ff48
- Add hOCR test fixtures for Latin, Arabic, CJK, Devanagari scripts - Add tests for fpdf2 renderer, multi-font manager, system font provider - Add multilingual rendering tests - Update existing tests to use fpdf2 renderer
125 lines
3.5 KiB
Python
125 lines
3.5 KiB
Python
# SPDX-FileCopyrightText: 2022 James R. Barlow
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# SPDX-License-Identifier: MPL-2.0
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from __future__ import annotations
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import re
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from io import StringIO
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from pathlib import Path
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import pytest
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from pdfminer.converter import TextConverter
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from pdfminer.layout import LAParams
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from pdfminer.pdfdocument import PDFDocument
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from pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager
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from pdfminer.pdfpage import PDFPage
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from pdfminer.pdfparser import PDFParser
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from PIL import Image
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from ocrmypdf._exec.tesseract import generate_hocr
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from ocrmypdf.font import MultiFontManager
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from ocrmypdf.fpdf_renderer import Fpdf2PdfRenderer
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from ocrmypdf.helpers import check_pdf
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from ocrmypdf.hocrtransform import HocrParser
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from .conftest import check_ocrmypdf
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def text_from_pdf(filename):
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output_string = StringIO()
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with open(filename, 'rb') as in_file:
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parser = PDFParser(in_file)
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doc = PDFDocument(parser)
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rsrcmgr = PDFResourceManager()
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device = TextConverter(rsrcmgr, output_string, laparams=LAParams())
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interpreter = PDFPageInterpreter(rsrcmgr, device)
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for page in PDFPage.create_pages(doc):
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interpreter.process_page(page)
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return output_string.getvalue()
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# pylint: disable=redefined-outer-name
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@pytest.fixture
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def font_dir():
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"""Get the font directory."""
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return Path(__file__).parent.parent / "src" / "ocrmypdf" / "data"
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@pytest.fixture
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def multi_font_manager(font_dir):
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"""Create a MultiFontManager for tests."""
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return MultiFontManager(font_dir)
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@pytest.fixture
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def blank_hocr(tmp_path):
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im = Image.new('1', (8, 8), 0)
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im.save(tmp_path / 'blank.tif', format='TIFF')
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generate_hocr(
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input_file=tmp_path / 'blank.tif',
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output_hocr=tmp_path / 'blank.hocr',
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output_text=tmp_path / 'blank.txt',
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languages=['eng'],
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engine_mode=1,
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tessconfig=[],
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pagesegmode=3,
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thresholding=0,
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user_words=None,
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user_patterns=None,
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timeout=None,
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)
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return tmp_path / 'blank.hocr'
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def test_mono_image(blank_hocr, outdir, multi_font_manager):
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im = Image.new('1', (8, 8), 0)
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for n in range(8):
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im.putpixel((n, n), 1)
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im.save(outdir / 'mono.tif', format='TIFF')
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# Parse hOCR file
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parser = HocrParser(str(blank_hocr))
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ocr_page = parser.parse()
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# Use DPI from hOCR or default
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dpi = ocr_page.dpi or 8
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# Render to PDF using fpdf2
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renderer = Fpdf2PdfRenderer(
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page=ocr_page,
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dpi=dpi,
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multi_font_manager=multi_font_manager,
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invisible_text=True,
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)
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renderer.render(outdir / 'mono.pdf')
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check_pdf(outdir / 'mono.pdf')
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@pytest.mark.slow
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def test_fpdf2_matches_sandwich(resources, outdir):
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"""Test that fpdf2 renderer produces similar output to sandwich renderer."""
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# Note: hocr renderer now redirects to fpdf2
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check_ocrmypdf(
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resources / 'ccitt.pdf', outdir / 'fpdf2.pdf', '--pdf-renderer=fpdf2'
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)
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check_ocrmypdf(
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resources / 'ccitt.pdf', outdir / 'tess.pdf', '--pdf-renderer=sandwich'
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)
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# Slight differences in spacing and word order can appear, so at least ensure
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# that we get all of the same words...
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def clean(s):
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s = re.sub(r'\s+', ' ', s)
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words = s.split(' ')
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return set(words)
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fpdf2_words = clean(text_from_pdf(outdir / 'fpdf2.pdf'))
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tess_words = clean(text_from_pdf(outdir / 'tess.pdf'))
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similarity = len(fpdf2_words & tess_words) / len(fpdf2_words | tess_words)
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assert similarity > 0.99
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