tesseract/training/lstmeval.cpp

59 lines
2.2 KiB
C++

///////////////////////////////////////////////////////////////////////
// File: lstmeval.cpp
// Description: Evaluation program for LSTM-based networks.
// Author: Ray Smith
// Created: Wed Nov 23 12:20:06 PST 2016
//
// (C) Copyright 2016, Google Inc.
// 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.
///////////////////////////////////////////////////////////////////////
#ifndef USE_STD_NAMESPACE
#include "base/commandlineflags.h"
#endif
#include "commontraining.h"
#include "genericvector.h"
#include "lstmtester.h"
#include "strngs.h"
#include "tprintf.h"
STRING_PARAM_FLAG(model, "", "Name of model file (training or recognition)");
STRING_PARAM_FLAG(eval_listfile, "",
"File listing sample files in lstmf training format.");
INT_PARAM_FLAG(max_image_MB, 2000, "Max memory to use for images.");
int main(int argc, char **argv) {
ParseArguments(&argc, &argv);
if (FLAGS_model.empty()) {
tprintf("Must provide a --model!\n");
return 1;
}
if (FLAGS_eval_listfile.empty()) {
tprintf("Must provide a --eval_listfile!\n");
return 1;
}
GenericVector<char> model_data;
if (!tesseract::LoadDataFromFile(FLAGS_model.c_str(), &model_data)) {
tprintf("Failed to load model from: %s\n", FLAGS_eval_listfile.c_str());
return 1;
}
tesseract::LSTMTester tester(static_cast<inT64>(FLAGS_max_image_MB) *
1048576);
if (!tester.LoadAllEvalData(FLAGS_eval_listfile.c_str())) {
tprintf("Failed to load eval data from: %s\n", FLAGS_eval_listfile.c_str());
return 1;
}
double errs = 0.0;
STRING result = tester.RunEvalSync(0, &errs, model_data, 0);
tprintf("%s\n", result.string());
return 0;
} /* main */