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https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp.git
synced 2024-12-25 20:34:18 +00:00
Update file handling. Now md5 is correct
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parent
bd5d8ddedb
commit
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4
nlp
4
nlp
@ -148,9 +148,11 @@ def parse_args():
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required=True)
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parser.add_argument('-l', '--language',
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choices=SPACY_MODELS.keys(),
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help='Language of the input (2-character ISO 639-1 language codes)', # noqa
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required=True)
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parser.add_argument('--check-encoding',
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action='store_true')
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action='store_true',
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help='Check encoding of the input file, UTF-8 is used instead') # noqa
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parser.add_argument('--log-dir',
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help='Logging directory')
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parser.add_argument('--mem-mb',
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23
spacy-nlp
23
spacy-nlp
@ -16,29 +16,32 @@ spacy_models = {spacy.info(pipeline)['lang']: pipeline
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# Parse the given arguments
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parser = ArgumentParser(description='Create annotations for a given txt file')
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parser.add_argument('input', metavar='Path to txt input file')
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parser.add_argument('output', metavar='Path to JSON output file')
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parser.add_argument('input', help='Path to txt input file')
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parser.add_argument('output', help='Path to JSON output file')
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parser.add_argument('-l', '--language',
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choices=spacy_models.keys(),
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help='Language of the input (2-character ISO 639-1 language codes)', # noqa
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required=True)
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parser.add_argument('-c', '--check-encoding', action='store_true')
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parser.add_argument('-c', '--check-encoding',
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action='store_true',
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help='Check encoding of the input file, UTF-8 is used instead') # noqa
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args = parser.parse_args()
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if args.check_encoding:
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with open(args.input, "rb") as text_file:
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if args.check_encoding:
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encoding = chardet.detect(text_file.read())['encoding']
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else:
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encoding = 'utf-8'
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# If requested: Check the encoding of the text contents from the input file
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# Else: Use utf-8
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with open(args.input, "rb") as text_file:
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if args.check_encoding:
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encoding = chardet.detect(text_file.read())['encoding']
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else:
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encoding = 'utf-8'
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text_md5 = hashlib.md5()
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for chunk in iter(lambda: text_file.read(128 * text_md5.block_size), b''):
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text_md5.update(chunk)
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# Load the text contents from the input file
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with open(args.input, encoding=encoding) as text_file:
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# spaCy NLP is limited to strings with maximum 1 million characters at
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# spaCy NLP is limited to strings with a maximum of 1 million characters at
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# once. So we split it into suitable chunks.
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text_chunks = textwrap.wrap(
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text_file.read(),
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@ -94,9 +94,9 @@ def main():
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# Parse the given arguments
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parser = ArgumentParser(description='Create a vrt from JSON and txt')
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parser.add_argument('text', metavar='Path to txt file')
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parser.add_argument('stand_off_data', metavar='Path to JSON file')
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parser.add_argument('output', metavar='Path to vrt output file')
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parser.add_argument('text', help='Path to txt file')
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parser.add_argument('stand_off_data', help='Path to JSON file')
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parser.add_argument('output', help='Path to vrt output file')
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args = parser.parse_args()
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with open(args.stand_off_data) as stand_of_data_file:
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@ -6,7 +6,7 @@ import os
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import subprocess
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import sys
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CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/nlp:1.0.0'
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CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/nlp:1.0.0b'
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CONTAINER_INPUT_DIR = '/input'
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CONTAINER_OUTPUT_DIR = '/output'
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CONTAINER_LOG_DIR = '/logs'
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