tesseract/cube/classifier_factory.cpp

98 lines
3.4 KiB
C++

/**********************************************************************
* File: classifier_factory.cpp
* Description: Implementation of the Base Character Classifier
* Author: Ahmad Abdulkader
* Created: 2007
*
* (C) Copyright 2008, 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.
*
**********************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <string>
#include "classifier_factory.h"
#include "conv_net_classifier.h"
#include "feature_base.h"
#include "feature_bmp.h"
#include "feature_chebyshev.h"
#include "feature_hybrid.h"
#include "hybrid_neural_net_classifier.h"
namespace tesseract {
// Creates a CharClassifier object of the appropriate type depending on the
// classifier type in the settings file
CharClassifier *CharClassifierFactory::Create(const string &data_file_path,
const string &lang,
LangModel *lang_mod,
CharSet *char_set,
TuningParams *params) {
// create the feature extraction object
FeatureBase *feat_extract;
switch (params->TypeFeature()) {
case TuningParams::BMP:
feat_extract = new FeatureBmp(params);
break;
case TuningParams::CHEBYSHEV:
feat_extract = new FeatureChebyshev(params);
break;
case TuningParams::HYBRID:
feat_extract = new FeatureHybrid(params);
break;
default:
fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): invalid "
"feature type.\n");
return NULL;
}
if (feat_extract == NULL) {
fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): unable "
"to instantiate feature extraction object.\n");
return NULL;
}
// create the classifier object
CharClassifier *classifier_obj;
switch (params->TypeClassifier()) {
case TuningParams::NN:
classifier_obj = new ConvNetCharClassifier(char_set, params,
feat_extract);
break;
case TuningParams::HYBRID_NN:
classifier_obj = new HybridNeuralNetCharClassifier(char_set, params,
feat_extract);
break;
default:
fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): invalid "
"classifier type.\n");
return NULL;
}
if (classifier_obj == NULL) {
fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): error "
"allocating memory for character classifier object.\n");
return NULL;
}
// Init the classifier
if (!classifier_obj->Init(data_file_path, lang, lang_mod)) {
delete classifier_obj;
fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): unable "
"to Init() character classifier object.\n");
return NULL;
}
return classifier_obj;
}
}