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https://github.com/tesseract-ocr/tesseract.git
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82 lines
3.2 KiB
Bash
Executable File
82 lines
3.2 KiB
Bash
Executable File
#!/bin/bash
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# (C) Copyright 2014, Google Inc.
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# This script provides an easy way to execute various phases of training
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# Tesseract. For a detailed description of the phases, see
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# https://github.com/tesseract-ocr/tesseract/wiki/TrainingTesseract
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#
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# USAGE:
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#
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# tesstrain.sh
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# --fontlist FONTS # A list of fontnames to train on.
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# --fonts_dir FONTS_PATH # Path to font files.
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# --lang LANG_CODE # ISO 639 code.
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# --langdata_dir DATADIR # Path to tesseract/training/langdata directory.
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# --output_dir OUTPUTDIR # Location of output traineddata file.
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# --overwrite # Safe to overwrite files in output_dir.
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# --linedata_only # Only generate training data for lstmtraining.
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# --run_shape_clustering # Run shape clustering (use for Indic langs).
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# --exposures EXPOSURES # A list of exposure levels to use (e.g. "-1 0 1").
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#
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# OPTIONAL flags for input data. If unspecified we will look for them in
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# the langdata_dir directory.
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# --training_text TEXTFILE # Text to render and use for training.
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# --wordlist WORDFILE # Word list for the language ordered by
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# # decreasing frequency.
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#
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# OPTIONAL flag to specify location of existing traineddata files, required
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# during feature extraction. If unspecified will use TESSDATA_PREFIX defined in
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# the current environment.
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# --tessdata_dir TESSDATADIR # Path to tesseract/tessdata directory.
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#
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# NOTE:
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# The font names specified in --fontlist need to be recognizable by Pango using
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# fontconfig. An easy way to list the canonical names of all fonts available on
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# your system is to run text2image with --list_available_fonts and the
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# appropriate --fonts_dir path.
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source "$(dirname $0)/tesstrain_utils.sh"
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ARGV=("$@")
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parse_flags
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mkdir -p ${TRAINING_DIR}
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tlog "\n=== Starting training for language '${LANG_CODE}'"
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source "$(dirname $0)/language-specific.sh"
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set_lang_specific_parameters ${LANG_CODE}
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initialize_fontconfig
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phase_I_generate_image 8
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phase_UP_generate_unicharset
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if ((LINEDATA)); then
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phase_E_extract_features "lstm.train" 8 "lstmf"
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make__lstmdata
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tlog "\nCreated starter traineddata for language '${LANG_CODE}'\n"
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tlog "\nRun lstmtraining to do the LSTM training for language '${LANG_CODE}'\n"
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else
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phase_D_generate_dawg
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phase_E_extract_features "box.train" 8 "tr"
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phase_C_cluster_prototypes "${TRAINING_DIR}/${LANG_CODE}.normproto"
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if [[ "${ENABLE_SHAPE_CLUSTERING}" == "y" ]]; then
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phase_S_cluster_shapes
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fi
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phase_M_cluster_microfeatures
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phase_B_generate_ambiguities
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make__traineddata
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tlog "\nCompleted training for language '${LANG_CODE}'\n"
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fi
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