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https://github.com/tesseract-ocr/tesseract.git
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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++
/**********************************************************************
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* File: classifier_factory.cpp
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* Description: Implementation of the Base Character Classifier
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* Author: Ahmad Abdulkader
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* Created: 2007
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*
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* (C) Copyright 2008, Google Inc.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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**********************************************************************/
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#include <stdio.h>
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#include <stdlib.h>
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#include <string>
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#include "classifier_factory.h"
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#include "conv_net_classifier.h"
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#include "feature_base.h"
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#include "feature_bmp.h"
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#include "feature_chebyshev.h"
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#include "feature_hybrid.h"
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#include "hybrid_neural_net_classifier.h"
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namespace tesseract {
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// Creates a CharClassifier object of the appropriate type depending on the
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// classifier type in the settings file
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CharClassifier *CharClassifierFactory::Create(const string &data_file_path,
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const string &lang,
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LangModel *lang_mod,
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CharSet *char_set,
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TuningParams *params) {
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// create the feature extraction object
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FeatureBase *feat_extract;
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switch (params->TypeFeature()) {
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case TuningParams::BMP:
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feat_extract = new FeatureBmp(params);
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break;
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case TuningParams::CHEBYSHEV:
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feat_extract = new FeatureChebyshev(params);
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break;
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case TuningParams::HYBRID:
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feat_extract = new FeatureHybrid(params);
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break;
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default:
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fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): invalid "
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"feature type.\n");
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return NULL;
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}
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if (feat_extract == NULL) {
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fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): unable "
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"to instantiate feature extraction object.\n");
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return NULL;
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}
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// create the classifier object
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CharClassifier *classifier_obj;
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switch (params->TypeClassifier()) {
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case TuningParams::NN:
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classifier_obj = new ConvNetCharClassifier(char_set, params,
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feat_extract);
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break;
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case TuningParams::HYBRID_NN:
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classifier_obj = new HybridNeuralNetCharClassifier(char_set, params,
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feat_extract);
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break;
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default:
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fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): invalid "
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"classifier type.\n");
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return NULL;
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}
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if (classifier_obj == NULL) {
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fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): error "
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"allocating memory for character classifier object.\n");
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return NULL;
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}
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// Init the classifier
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if (!classifier_obj->Init(data_file_path, lang, lang_mod)) {
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delete classifier_obj;
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fprintf(stderr, "Cube ERROR (CharClassifierFactory::Create): unable "
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"to Init() character classifier object.\n");
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return NULL;
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}
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return classifier_obj;
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}
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}
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