mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-12-23 06:57:50 +08:00
4523ce9f7d
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@526 d0cd1f9f-072b-0410-8dd7-cf729c803f20
98 lines
3.4 KiB
C++
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;
|
|
}
|
|
}
|