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https://github.com/mikegerber/ocrd_calamari.git
synced 2025-06-09 11:49:53 +02:00
✨ Include proper word + glyph segmentation
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parent
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commit
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2 changed files with 47 additions and 20 deletions
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@ -4,6 +4,7 @@ import os
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from glob import glob
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import numpy as np
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import uniseg.wordbreak
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from calamari_ocr.ocr import MultiPredictor
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from calamari_ocr.ocr.voting import voter_from_proto
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from calamari_ocr.proto import VoterParams
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@ -13,7 +14,7 @@ from ocrd_models.ocrd_page import (
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LabelType, LabelsType,
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MetadataItemType,
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TextEquivType,
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WordType, CoordsType,
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WordType, GlyphType, CoordsType,
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to_xml
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)
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from ocrd_utils import getLogger, concat_padded, coordinates_for_segment, points_from_polygon, MIMETYPE_PAGE
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@ -95,28 +96,53 @@ class CalamariRecognize(Processor):
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line.set_TextEquiv([TextEquivType(Unicode=line_text, conf=line_conf)])
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# Save word results
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# XXX For early development just put every char = glyph into its own word
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for word_no, p in enumerate(prediction.positions):
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start = p.global_start
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end = p.global_end
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def unwanted(c):
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return c == " "
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word_no = 0
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i = 0
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for word_text in uniseg.wordbreak.words(prediction.sentence):
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print(word_text)
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word_length = len(word_text)
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do_not_include = all(unwanted(c) for c in word_text)
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if not do_not_include:
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word_positions = prediction.positions[i:i+word_length]
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word_start = word_positions[0].global_start
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word_end = word_positions[-1].global_end
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# XXX Maybe use version in ocrd_tesserocr
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h = line_image.height
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polygon = [(word_start, 0), (word_end, 0), (word_end, h), (word_start, h)]
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points = points_from_polygon(coordinates_for_segment(polygon, None, line_coords))
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word = WordType(id='%s_word%04d' % (line.id, word_no), Coords=CoordsType(points))
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word.add_TextEquiv(TextEquivType(Unicode=word_text))
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for glyph_no, p in enumerate(word_positions):
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glyph_start = p.global_start
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glyph_end = p.global_end
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# XXX Maybe use version in ocrd_tesserocr
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h = line_image.height
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polygon = [(glyph_start, 0), (glyph_end, 0), (glyph_end, h), (glyph_start, h)]
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points = points_from_polygon(coordinates_for_segment(polygon, None, line_coords))
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glyph = GlyphType(id='%s_glyph%04d' % (word.id, glyph_no), Coords=CoordsType(points))
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chars = sorted(p.chars, key=lambda k: k.probability, reverse=True)
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for index, char in enumerate(chars):
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if char.char:
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glyph.add_TextEquiv(TextEquivType(Unicode=char.char, index=index, conf=char.probability))
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# XXX Note that omission probabilities are not normalized?!
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word.add_Glyph(glyph)
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line.add_Word(word)
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# XXX Maybe use version in ocrd_tesserocr
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h = line_image.height
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polygon = [(start, 0), (end, 0), (end, h), (start, h)]
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points = points_from_polygon(coordinates_for_segment(polygon, None, line_coords))
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i += word_length
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word_no += 1
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word = WordType(
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id='%s_word%04d' % (line.id, word_no),
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Coords=CoordsType(points))
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chars = sorted(p.chars, key=lambda k: k.probability, reverse=True)
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for index, char in enumerate(chars):
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if char.char:
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word.add_TextEquiv(TextEquivType(Unicode=char.char, index=index, conf=char.probability))
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# XXX Note that omission probabilities are not normalized?!
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line.add_Word(word)
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_page_update_higher_textequiv_levels('line', pcgts)
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@ -4,3 +4,4 @@ calamari-ocr == 0.3.5
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setuptools >= 41.0.0 # tensorboard depends on this, but why do we get an error at runtime?
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click
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ocrd >= 2.2.1
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uniseg
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