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https://github.com/ocrmypdf/OCRmyPDF.git
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32322a9fe9
Expect word similarity rather than exact match. Difference appears to be due to quote styles. Thanks @QuLogic for reporting.
103 lines
3.1 KiB
Python
103 lines
3.1 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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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 import hocrtransform
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from ocrmypdf._exec.tesseract import generate_hocr
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from ocrmypdf.helpers import check_pdf
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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 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):
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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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hocr = hocrtransform.HocrTransform(hocr_filename=str(blank_hocr), dpi=8)
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hocr.to_pdf(
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out_filename=str(outdir / 'mono.pdf'), image_filename=str(outdir / 'mono.tif')
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)
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# shutil.copy(outdir / 'mono.pdf', 'mono.pdf')
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check_pdf(str(outdir / 'mono.pdf'))
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@pytest.mark.slow
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def test_hocrtransform_matches_sandwich(resources, outdir):
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check_ocrmypdf(resources / 'ccitt.pdf', outdir / 'hocr.pdf', '--pdf-renderer=hocr')
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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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hocr_words = clean(text_from_pdf(outdir / 'hocr.pdf'))
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tess_words = clean(text_from_pdf(outdir / 'tess.pdf'))
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similarity = len(hocr_words & tess_words) / len(hocr_words | tess_words)
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# from pathlib import Path
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# Path('hocr.txt').write_text(sorted('\n'.join(hocr_words)))
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# Path('tess.txt').write_text(sorted('\n'.join(tess_words)))
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# Path('mismatch.txt').write_text(
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# '\n'.join(sorted(hocr_words ^ tess_words)), encoding='utf8'
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# )
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assert similarity > 0.99
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