Tesseract
3.02
|
00001 /********************************************************************** 00002 * File: tface.c (Formerly tface.c) 00003 * Description: C side of the Tess/tessedit C/C++ interface. 00004 * Author: Ray Smith 00005 * Created: Mon Apr 27 11:57:06 BST 1992 00006 * 00007 * (C) Copyright 1992, Hewlett-Packard Ltd. 00008 ** Licensed under the Apache License, Version 2.0 (the "License"); 00009 ** you may not use this file except in compliance with the License. 00010 ** You may obtain a copy of the License at 00011 ** http://www.apache.org/licenses/LICENSE-2.0 00012 ** Unless required by applicable law or agreed to in writing, software 00013 ** distributed under the License is distributed on an "AS IS" BASIS, 00014 ** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 00015 ** See the License for the specific language governing permissions and 00016 ** limitations under the License. 00017 * 00018 **********************************************************************/ 00019 00020 #include "bestfirst.h" 00021 #include "callcpp.h" 00022 #include "chop.h" 00023 #include "chopper.h" 00024 #include "danerror.h" 00025 #include "fxdefs.h" 00026 #include "globals.h" 00027 #include "gradechop.h" 00028 #include "matchtab.h" 00029 #include "pageres.h" 00030 #include "permute.h" 00031 #include "wordclass.h" 00032 #include "wordrec.h" 00033 #include "featdefs.h" 00034 00035 #include <math.h> 00036 #ifdef __UNIX__ 00037 #include <unistd.h> 00038 #endif 00039 00040 00041 namespace tesseract { 00042 00050 void Wordrec::program_editup(const char *textbase, 00051 bool init_classifier, 00052 bool init_dict) { 00053 if (textbase != NULL) imagefile = textbase; 00054 InitFeatureDefs(&feature_defs_); 00055 SetupExtractors(&feature_defs_); 00056 InitAdaptiveClassifier(init_classifier); 00057 if (init_dict) getDict().Load(); 00058 pass2_ok_split = chop_ok_split; 00059 pass2_seg_states = wordrec_num_seg_states; 00060 } 00061 00067 int Wordrec::end_recog() { 00068 program_editdown (0); 00069 00070 return (0); 00071 } 00072 00073 00080 void Wordrec::program_editdown(inT32 elasped_time) { 00081 EndAdaptiveClassifier(); 00082 blob_match_table.end_match_table(); 00083 getDict().InitChoiceAccum(); 00084 getDict().End(); 00085 } 00086 00087 00093 void Wordrec::set_pass1() { 00094 chop_ok_split.set_value(70.0); 00095 wordrec_num_seg_states.set_value(15); 00096 SettupPass1(); 00097 } 00098 00099 00105 void Wordrec::set_pass2() { 00106 chop_ok_split.set_value(pass2_ok_split); 00107 wordrec_num_seg_states.set_value(pass2_seg_states); 00108 SettupPass2(); 00109 } 00110 00111 00117 BLOB_CHOICE_LIST_VECTOR *Wordrec::cc_recog(WERD_RES *word) { 00118 getDict().InitChoiceAccum(); 00119 getDict().reset_hyphen_vars(word->word->flag(W_EOL)); 00120 blob_match_table.init_match_table(); 00121 BLOB_CHOICE_LIST_VECTOR *results = chop_word_main(word); 00122 getDict().DebugWordChoices(); 00123 return results; 00124 } 00125 00126 00133 int Wordrec::dict_word(const WERD_CHOICE &word) { 00134 return getDict().valid_word(word); 00135 } 00136 00143 BLOB_CHOICE_LIST *Wordrec::call_matcher(const DENORM* denorm, TBLOB *tessblob) { 00144 // Rotate the blob for classification if necessary. 00145 TBLOB* rotated_blob = tessblob->ClassifyNormalizeIfNeeded(&denorm); 00146 if (rotated_blob == NULL) { 00147 rotated_blob = tessblob; 00148 } 00149 BLOB_CHOICE_LIST *ratings = new BLOB_CHOICE_LIST(); // matcher result 00150 AdaptiveClassifier(rotated_blob, *denorm, ratings, NULL); 00151 if (rotated_blob != tessblob) { 00152 delete rotated_blob; 00153 delete denorm; 00154 } 00155 return ratings; 00156 } 00157 00158 00159 } // namespace tesseract