1 files changed, 112 insertions, 0 deletions
diff --git a/tesseract/src/training/tesstrain.py b/tesseract/src/training/tesstrain.py
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+++ b/tesseract/src/training/tesstrain.py
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+#!/usr/bin/env python3
+
+# (C) Copyright 2014, Google Inc.
+# (C) Copyright 2018, James R Barlow
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# This script provides an easy way to execute various phases of training
+# Tesseract.  For a detailed description of the phases, see
+# https://tesseract-ocr.github.io/tessdoc/Training-Tesseract.html.
+
+import logging
+import os
+import sys
+
+if (sys.version_info.major < 3) or (sys.version_info.major == 3 and sys.version_info.minor < 6):
+    raise Exception("Must be using Python minimum version 3.6!")
+
+sys.path.insert(0, os.path.dirname(__file__))
+from tesstrain_utils import (
+    parse_flags,
+    initialize_fontconfig,
+    phase_I_generate_image,
+    phase_UP_generate_unicharset,
+    phase_E_extract_features,
+    make_lstmdata,
+    cleanup,
+)
+import language_specific
+
+log = logging.getLogger()
+
+
+def setup_logging_console():
+    log.setLevel(logging.DEBUG)
+    console = logging.StreamHandler()
+    console.setLevel(logging.INFO)
+    console_formatter = logging.Formatter(
+        "[%(asctime)s] %(levelname)s - %(message)s", datefmt="%H:%M:%S"
+    )
+    console.setFormatter(console_formatter)
+    log.addHandler(console)
+
+
+def setup_logging_logfile(logfile):
+    logfile = logging.FileHandler(logfile, encoding='utf-8')
+    logfile.setLevel(logging.DEBUG)
+    logfile_formatter = logging.Formatter(
+        "[%(asctime)s] - %(levelname)s - %(name)s - %(message)s"
+    )
+    logfile.setFormatter(logfile_formatter)
+    log.addHandler(logfile)
+    return logfile
+
+
+def main():
+    setup_logging_console()
+    ctx = parse_flags()
+    logfile = setup_logging_logfile(ctx.log_file)
+    if not ctx.linedata:
+        log.error("--linedata_only is required since only LSTM is supported")
+        sys.exit(1)
+
+    log.info(f"=== Starting training for language {ctx.lang_code}")
+    ctx = language_specific.set_lang_specific_parameters(ctx, ctx.lang_code)
+
+    initialize_fontconfig(ctx)
+    phase_I_generate_image(ctx, par_factor=8)
+    phase_UP_generate_unicharset(ctx)
+
+    if ctx.linedata:
+        phase_E_extract_features(ctx, ["lstm.train"], "lstmf")
+        make_lstmdata(ctx)
+
+    log.removeHandler(logfile)
+    logfile.close()
+    cleanup(ctx)
+    log.info("All done!")
+    return 0
+
+
+if __name__ == "__main__":
+    main()
+
+# _rc0 = subprocess.call(["tlog","\n=== Starting training for language '"+str(LANG_CODE.val)+"'"],shell=True)
+# _rc0 = subprocess.call(["source",os.popen("dirname "+__file__).read().rstrip("\n")+"/language-specific.sh"],shell=True)
+# _rc0 = subprocess.call(["set_lang_specific_parameters",str(LANG_CODE.val)],shell=True)
+# _rc0 = subprocess.call(["initialize_fontconfig"],shell=True)
+# _rc0 = subprocess.call(["phase_I_generate_image","8"],shell=True)
+# _rc0 = subprocess.call(["phase_UP_generate_unicharset"],shell=True)
+# if (LINEDATA ):
+# subprocess.call(["phase_E_extract_features"," --psm 6  lstm.train ","8","lstmf"],shell=True)
+#     subprocess.call(["make__lstmdata"],shell=True)
+#     subprocess.call(["tlog","\nCreated starter traineddata for language '"+str(LANG_CODE.val)+"'\n"],shell=True)
+#     subprocess.call(["tlog","\nRun lstmtraining to do the LSTM training for language '"+str(LANG_CODE.val)+"'\n"],shell=True)
+# else:
+#     subprocess.call(["phase_D_generate_dawg"],shell=True)
+#     subprocess.call(["phase_E_extract_features","box.train","8","tr"],shell=True)
+#     subprocess.call(["phase_C_cluster_prototypes",str(TRAINING_DIR.val)+"/"+str(LANG_CODE.val)+".normproto"],shell=True)
+#     if (str(ENABLE_SHAPE_CLUSTERING.val) == "y" ):
+#         subprocess.call(["phase_S_cluster_shapes"],shell=True)
+#     subprocess.call(["phase_M_cluster_microfeatures"],shell=True)
+#     subprocess.call(["phase_B_generate_ambiguities"],shell=True)
+#     subprocess.call(["make__traineddata"],shell=True)
+#     subprocess.call(["tlog","\nCompleted training for language '"+str(LANG_CODE.val)+"'\n"],shell=True)