Konstantin Baierer
5 years ago
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GitHub
commit
58f2adcd1c
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# ocrd_calamari
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Recognize text using [Calamari OCR](https://github.com/Calamari-OCR/calamari).
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Introduction
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-------------
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This offers a OCR-D compliant workspace processor for some of the functionality of Calamari OCR.
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This processor only operates on the text line level and so needs a line segmentation (and by extension a binarized
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image) as its input.
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Example Usage
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-------------
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~~~
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ocrd-calamari-recognize -p test-parameters.json -m mets.xml -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI
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~~~
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With `test-parameters.json`:
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~~~
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{
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"checkpoint": "/path/to/some/trained/models/*.ckpt.json"
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}
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~~~
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TODO
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----
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* Support Calamari's "extended prediction data" output
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* Currently, the processor only supports a prediction using confidence voting of multiple models. While this is
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superior, it makes sense to support single model prediction, too.
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import click
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from ocrd.decorators import ocrd_cli_options, ocrd_cli_wrap_processor
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from ocrd_calamari.recognize import CalamariRecognize
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@click.command()
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@ocrd_cli_options
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def ocrd_calamari_recognize(*args, **kwargs):
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return ocrd_cli_wrap_processor(CalamariRecognize, *args, **kwargs)
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import json
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from pkg_resources import resource_string
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OCRD_TOOL = json.loads(resource_string(__name__, 'ocrd-tool.json').decode('utf8'))
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TF_CPP_MIN_LOG_LEVEL = '3' # '3' == ERROR
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@ -1,39 +0,0 @@
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from __future__ import absolute_import
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from calamari_ocr.scripts.predict import run
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log = getLogger('processor.KrakenOcr')
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class KrakenOcr(Processor):
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def __init__(self, *args, **kwargs):
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kwargs['ocrd_tool'] = OCRD_TOOL['tools']['ocrd-calamari-ocr']
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super(KrakenOcr, self).__init__(*args, **kwargs)
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def process(self):
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"""
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Performs the binarization.
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"""
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for (n, input_file) in enumerate(self.input_files):
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log.info("INPUT FILE %i / %s", n, input_file)
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pcgts = ocrd_page.from_file(self.workspace.download_file(input_file))
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image_url = pcgts.get_Page().imageFilename
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log.info("pcgts %s", pcgts)
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for region in pcgts.get_Page().get_TextRegion():
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textlines = region.get_TextLine()
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log.info("About to binarize %i lines of region '%s'", len(textlines), region.id)
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for (line_no, line) in enumerate(textlines):
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log.debug("Binarizing line '%s' in region '%s'", line_no, region.id)
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image = self.workspace.resolve_image_as_pil(image_url, polygon_from_points(line.get_Coords().points))
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print(dir(kraken.binarization))
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bin_image = kraken.binarization.nlbin(image)
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bin_image_bytes = io.BytesIO()
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bin_image.save(bin_image_bytes, format='PNG')
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ID = concat_padded(self.output_file_grp, n)
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self.add_output_file(
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ID=ID,
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file_grp=self.output_file_grp,
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basename="%s.bin.png" % ID,
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mimetype='image/png',
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content=bin_image_bytes.getvalue()
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)
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from __future__ import absolute_import
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import os
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from glob import glob
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import numpy as np
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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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from ocrd import Processor
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from ocrd_modelfactory import page_from_file
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from ocrd_models.ocrd_page import to_xml
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from ocrd_models.ocrd_page_generateds import TextEquivType
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from ocrd_utils import getLogger, concat_padded, polygon_from_points, MIMETYPE_PAGE
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from ocrd_calamari.config import OCRD_TOOL, TF_CPP_MIN_LOG_LEVEL
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log = getLogger('processor.CalamariRecognize')
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class CalamariRecognize(Processor):
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def __init__(self, *args, **kwargs):
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kwargs['ocrd_tool'] = OCRD_TOOL['tools']['ocrd-calamari-recognize']
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super(CalamariRecognize, self).__init__(*args, **kwargs)
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def _init_calamari(self):
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = TF_CPP_MIN_LOG_LEVEL
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checkpoints = glob(self.parameter['checkpoint'])
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self.predictor = MultiPredictor(checkpoints=checkpoints)
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voter_params = VoterParams()
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voter_params.type = VoterParams.Type.Value(self.parameter['voter'].upper())
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self.voter = voter_from_proto(voter_params)
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def resolve_image_as_np(self, image_url, coords):
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return np.array(self.workspace.resolve_image_as_pil(image_url, coords), dtype=np.uint8)
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def _make_file_id(self, input_file, n):
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file_id = input_file.ID.replace(self.input_file_grp, self.output_file_grp)
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if file_id == input_file.ID:
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file_id = concat_padded(self.output_file_grp, n)
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return file_id
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def process(self):
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"""
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Performs the recognition.
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"""
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self._init_calamari()
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for (n, input_file) in enumerate(self.input_files):
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log.info("INPUT FILE %i / %s", n, input_file)
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pcgts = page_from_file(self.workspace.download_file(input_file))
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image_url = pcgts.get_Page().imageFilename
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log.info("pcgts %s", pcgts)
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for region in pcgts.get_Page().get_TextRegion():
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textlines = region.get_TextLine()
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log.info("About to recognize %i lines of region '%s'", len(textlines), region.id)
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for (line_no, line) in enumerate(textlines):
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log.debug("Recognizing line '%s' in region '%s'", line_no, region.id)
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image = self.resolve_image_as_np(image_url, polygon_from_points(line.get_Coords().points))
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raw_results = list(self.predictor.predict_raw([image], progress_bar=False))[0]
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for i, p in enumerate(raw_results):
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p.prediction.id = "fold_{}".format(i)
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prediction = self.voter.vote_prediction_result(raw_results)
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prediction.id = "voted"
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line_text = prediction.sentence
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line_conf = prediction.avg_char_probability
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line.add_TextEquiv(TextEquivType(Unicode=line_text, conf=line_conf))
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_page_update_higher_textequiv_levels('line', pcgts)
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file_id = self._make_file_id(input_file, n)
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self.workspace.add_file(
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ID=file_id,
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file_grp=self.output_file_grp,
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pageId=input_file.pageId,
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mimetype=MIMETYPE_PAGE,
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local_filename=os.path.join(self.output_file_grp, file_id + '.xml'),
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content=to_xml(pcgts))
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# TODO: This is a copy of ocrd_tesserocr's function, and should probably be moved to a ocrd lib
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def _page_update_higher_textequiv_levels(level, pcgts):
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"""Update the TextEquivs of all PAGE-XML hierarchy levels above `level` for consistency.
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Starting with the hierarchy level chosen for processing,
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join all first TextEquiv (by the rules governing the respective level)
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into TextEquiv of the next higher level, replacing them.
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"""
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regions = pcgts.get_Page().get_TextRegion()
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if level != 'region':
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for region in regions:
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lines = region.get_TextLine()
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if level != 'line':
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for line in lines:
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words = line.get_Word()
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if level != 'word':
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for word in words:
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glyphs = word.get_Glyph()
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word_unicode = u''.join(glyph.get_TextEquiv()[0].Unicode
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if glyph.get_TextEquiv()
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else u'' for glyph in glyphs)
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word.set_TextEquiv(
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[TextEquivType(Unicode=word_unicode)]) # remove old
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line_unicode = u' '.join(word.get_TextEquiv()[0].Unicode
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if word.get_TextEquiv()
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else u'' for word in words)
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line.set_TextEquiv(
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[TextEquivType(Unicode=line_unicode)]) # remove old
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region_unicode = u'\n'.join(line.get_TextEquiv()[0].Unicode
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if line.get_TextEquiv()
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else u'' for line in lines)
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region.set_TextEquiv(
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[TextEquivType(Unicode=region_unicode)]) # remove old
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@ -0,0 +1,5 @@
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numpy
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calamari-ocr
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tensorflow-gpu
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click
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ocrd >= 1.0.0b11
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# -*- coding: utf-8 -*-
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import codecs
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from setuptools import setup, find_packages
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setup(
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name='ocrd_calamari',
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version='0.0.1',
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description='Calamari bindings',
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long_description=codecs.open('README.md', encoding='utf-8').read(),
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author='Konstantin Baierer, Mike Gerber',
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author_email='unixprog@gmail.com, mike.gerber@sbb.spk-berlin.de',
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url='https://github.com/kba/ocrd_calamari',
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license='Apache License 2.0',
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packages=find_packages(exclude=('tests', 'docs')),
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install_requires=open('requirements.txt').read().split('\n'),
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package_data={
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'': ['*.json', '*.yml', '*.yaml'],
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},
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entry_points={
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'console_scripts': [
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'ocrd-calamari-recognize=ocrd_calamari.cli:ocrd_calamari_recognize',
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]
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},
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)
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