/
classifier_tester.cpp
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/
classifier_tester.cpp
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// Copyright 2011 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
// 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.
// Filename: classifier_tester.cpp
// Purpose: Tests a character classifier on data as formatted for training,
// but doesn't have to be the same as the training data.
// Author: Ray Smith
#include <stdio.h>
#ifdef GOOGLE_TESSERACT
#include "base/commandlineflags.h"
#endif // GOOGLE_TESSERACT
#include "baseapi.h"
#include "commontraining.h"
#include "mastertrainer.h"
#include "params.h"
#include "strngs.h"
#include "tessclassifier.h"
#include "tesseractclass.h"
STRING_PARAM_FLAG(classifier, "", "Classifier to test");
STRING_PARAM_FLAG(lang, "eng", "Language to test");
STRING_PARAM_FLAG(tessdata_dir, "", "Directory of traineddata files");
DECLARE_INT_PARAM_FLAG(debug_level);
enum ClassifierName {
CN_PRUNER,
CN_FULL,
CN_COUNT
};
static const char* names[] = {"pruner", "full"};
static tesseract::ShapeClassifier* InitializeClassifier(
const char* classifer_name, const UNICHARSET& unicharset,
int argc, char **argv,
tesseract::TessBaseAPI** api) {
// Decode the classifier string.
ClassifierName classifier = CN_COUNT;
for (int c = 0; c < CN_COUNT; ++c) {
if (strcmp(classifer_name, names[c]) == 0) {
classifier = static_cast<ClassifierName>(c);
break;
}
}
if (classifier == CN_COUNT) {
fprintf(stderr, "Invalid classifier name:%s\n", FLAGS_classifier.c_str());
return nullptr;
}
// We need to initialize tesseract to test.
*api = new tesseract::TessBaseAPI;
tesseract::OcrEngineMode engine_mode = tesseract::OEM_TESSERACT_ONLY;
tesseract::Tesseract* tesseract = nullptr;
tesseract::Classify* classify = nullptr;
if (
classifier == CN_PRUNER || classifier == CN_FULL) {
if ((*api)->Init(FLAGS_tessdata_dir.c_str(), FLAGS_lang.c_str(),
engine_mode) < 0) {
fprintf(stderr, "Tesseract initialization failed!\n");
return nullptr;
}
tesseract = const_cast<tesseract::Tesseract*>((*api)->tesseract());
classify = static_cast<tesseract::Classify*>(tesseract);
if (classify->shape_table() == nullptr) {
fprintf(stderr, "Tesseract must contain a ShapeTable!\n");
return nullptr;
}
}
tesseract::ShapeClassifier* shape_classifier = nullptr;
if (classifier == CN_PRUNER) {
shape_classifier = new tesseract::TessClassifier(true, classify);
} else if (classifier == CN_FULL) {
shape_classifier = new tesseract::TessClassifier(false, classify);
}
tprintf("Testing classifier %s:\n", classifer_name);
return shape_classifier;
}
// This program has complex setup requirements, so here is some help:
// Two different modes, tr files and serialized mastertrainer.
// From tr files:
// classifier_tester -U unicharset -F font_properties -X xheights
// -classifier x -lang lang [-output_trainer trainer] *.tr
// From a serialized trainer:
// classifier_tester -input_trainer trainer [-lang lang] -classifier x
//
// In the first case, the unicharset must be the unicharset from within
// the classifier under test, and the font_properties and xheights files must
// match the files used during training.
// In the second case, the trainer file must have been prepared from
// some previous run of shapeclustering, mftraining, or classifier_tester
// using the same conditions as above, ie matching unicharset/font_properties.
//
// Available values of classifier (x above) are:
// pruner : Tesseract class pruner only.
// full : Tesseract full classifier.
// with an input trainer.)
int main(int argc, char **argv) {
tesseract::CheckSharedLibraryVersion();
ParseArguments(&argc, &argv);
STRING file_prefix;
tesseract::MasterTrainer* trainer =
tesseract::LoadTrainingData(argc, argv, false, nullptr, &file_prefix);
tesseract::TessBaseAPI* api;
// Decode the classifier string.
tesseract::ShapeClassifier* shape_classifier = InitializeClassifier(
FLAGS_classifier.c_str(), trainer->unicharset(), argc, argv, &api);
if (shape_classifier == nullptr) {
fprintf(stderr, "Classifier init failed!:%s\n", FLAGS_classifier.c_str());
return 1;
}
// We want to test junk as well if it is available.
// trainer->IncludeJunk();
// We want to test with replicated samples too.
trainer->ReplicateAndRandomizeSamplesIfRequired();
trainer->TestClassifierOnSamples(tesseract::CT_UNICHAR_TOP1_ERR,
MAX(3, FLAGS_debug_level), false,
shape_classifier, nullptr);
delete shape_classifier;
delete api;
delete trainer;
return 0;
} /* main */