mirror of
https://github.com/mikegerber/ocrd_calamari.git
synced 2025-07-18 22:49:54 +02:00
98 lines
3.3 KiB
Python
98 lines
3.3 KiB
Python
import os
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import shutil
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import subprocess
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import urllib.request
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from lxml import etree
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import pytest
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from ocrd.resolver import Resolver
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from ocrd_calamari import CalamariRecognize
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from .base import assets
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METS_KANT = assets.url_of('kant_aufklaerung_1784-page-block-line-word_glyph/data/mets.xml')
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WORKSPACE_DIR = '/tmp/test-ocrd-calamari'
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CHECKPOINT = os.path.join(os.getcwd(), 'gt4histocr-calamari/*.ckpt.json')
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@pytest.fixture
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def workspace():
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if os.path.exists(WORKSPACE_DIR):
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shutil.rmtree(WORKSPACE_DIR)
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os.makedirs(WORKSPACE_DIR)
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resolver = Resolver()
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workspace = resolver.workspace_from_url(METS_KANT, dst_dir=WORKSPACE_DIR)
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# XXX Work around data bug(?):
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# PAGE-XML links to OCR-D-IMG/INPUT_0017.tif, but this is nothing core can download
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os.makedirs(os.path.join(WORKSPACE_DIR, 'OCR-D-IMG'))
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for f in ['INPUT_0017.tif', 'INPUT_0020.tif']:
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urllib.request.urlretrieve(
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"https://github.com/OCR-D/assets/raw/master/data/kant_aufklaerung_1784/data/OCR-D-IMG/" + f,
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os.path.join(WORKSPACE_DIR, 'OCR-D-IMG', f))
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# The binarization options I have are:
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#
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# a. ocrd_kraken which tries to install cltsm, whose installation is borken on my machine (protobuf)
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# b. ocrd_olena which 1. I cannot fully install via pip and 2. whose dependency olena doesn't compile on my
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# machine
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# c. just fumble with the original files
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#
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# So I'm going for option c.
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for f in ['INPUT_0017.tif', 'INPUT_0020.tif']:
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ff = os.path.join(WORKSPACE_DIR, 'OCR-D-IMG', f)
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subprocess.call(['convert', ff, '-threshold', '50%', ff])
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return workspace
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def test_recognize(workspace):
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# XXX Should remove GT text to really test this
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CalamariRecognize(
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workspace,
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input_file_grp="OCR-D-GT-SEG-LINE",
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output_file_grp="OCR-D-OCR-CALAMARI",
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parameter={
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"checkpoint": CHECKPOINT,
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}
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).process()
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workspace.save_mets()
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page1 = os.path.join(workspace.directory, "OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_0001.xml")
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assert os.path.exists(page1)
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with open(page1, "r", encoding="utf-8") as f:
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assert "verſchuldeten" in f.read()
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def test_word_segmentation(workspace):
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CalamariRecognize(
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workspace,
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input_file_grp="OCR-D-GT-SEG-LINE",
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output_file_grp="OCR-D-OCR-CALAMARI",
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parameter={
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"checkpoint": CHECKPOINT,
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}
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).process()
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workspace.save_mets()
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page1 = os.path.join(workspace.directory, "OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_0001.xml")
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assert os.path.exists(page1)
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tree = etree.parse(page1)
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NSMAP = { "pc": "http://schema.primaresearch.org/PAGE/gts/pagecontent/2019-07-15" }
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# The result should contain a TextLine that contains the text "December"
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line = tree.xpath(".//pc:TextLine[pc:TextEquiv/pc:Unicode[contains(text(),'December')]]", namespaces=NSMAP)[0]
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assert line
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# The textline should a. contain multiple words and b. these should concatenate fine to produce the same line text
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words = line.xpath(".//pc:Word", namespaces=NSMAP)
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assert len(words) >= 2
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words_text = " ".join(word.xpath("pc:TextEquiv/pc:Unicode", namespaces=NSMAP)[0].text for word in words)
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line_text = line.xpath("pc:TextEquiv/pc:Unicode", namespaces=NSMAP)[0].text
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assert words_text == line_text
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# vim:tw=120:
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