Mercurial > hgrepos > Python2 > PyMuPDF
annotate mupdf-source/thirdparty/tesseract/src/ccstruct/blamer.h @ 46:7ee69f120f19 default tip
>>>>> tag v1.26.5+1 for changeset b74429b0f5c4
| author | Franz Glasner <fzglas.hg@dom66.de> |
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| date | Sat, 11 Oct 2025 17:17:30 +0200 |
| parents | b50eed0cc0ef |
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| rev | line source |
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1 /////////////////////////////////////////////////////////////////////// |
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2 // File: blamer.h |
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3 // Description: Module allowing precise error causes to be allocated. |
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4 // Author: Rike Antonova |
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5 // Refactored: Ray Smith |
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6 // |
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7 // (C) Copyright 2013, Google Inc. |
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8 // Licensed under the Apache License, Version 2.0 (the "License"); |
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9 // you may not use this file except in compliance with the License. |
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10 // You may obtain a copy of the License at |
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11 // http://www.apache.org/licenses/LICENSE-2.0 |
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12 // Unless required by applicable law or agreed to in writing, software |
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13 // distributed under the License is distributed on an "AS IS" BASIS, |
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14 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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15 // See the License for the specific language governing permissions and |
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16 // limitations under the License. |
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17 // |
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18 /////////////////////////////////////////////////////////////////////// |
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19 |
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20 #ifndef TESSERACT_CCSTRUCT_BLAMER_H_ |
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21 #define TESSERACT_CCSTRUCT_BLAMER_H_ |
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22 |
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23 #ifdef HAVE_CONFIG_H |
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24 # include "config_auto.h" // DISABLED_LEGACY_ENGINE |
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25 #endif |
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26 #include "boxword.h" // for BoxWord |
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27 #ifndef DISABLED_LEGACY_ENGINE |
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28 # include "params_training_featdef.h" // for ParamsTrainingBundle, ParamsTra... |
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29 #endif // ndef DISABLED_LEGACY_ENGINE |
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30 #include "ratngs.h" // for BLOB_CHOICE_LIST (ptr only) |
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31 #include "rect.h" // for TBOX |
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32 #include "tprintf.h" // for tprintf |
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33 |
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34 #include <tesseract/unichar.h> // for UNICHAR_ID |
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35 |
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36 #include <cstdint> // for int16_t |
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37 #include <cstring> // for memcpy |
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38 #include <vector> // for std::vector |
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39 |
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40 namespace tesseract { |
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41 |
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42 class DENORM; |
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43 class MATRIX; |
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44 class UNICHARSET; |
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45 class WERD_RES; |
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46 |
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47 struct MATRIX_COORD; |
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48 struct TWERD; |
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49 |
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50 class LMPainPoints; |
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51 |
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52 static const int16_t kBlamerBoxTolerance = 5; |
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53 |
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54 // Enum for expressing the source of error. |
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55 // Note: Please update kIncorrectResultReasonNames when modifying this enum. |
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56 enum IncorrectResultReason { |
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57 // The text recorded in best choice == truth text |
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58 IRR_CORRECT, |
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59 // Either: Top choice is incorrect and is a dictionary word (language model |
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60 // is unlikely to help correct such errors, so blame the classifier). |
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61 // Or: the correct unichar was not included in shortlist produced by the |
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62 // classifier at all. |
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63 IRR_CLASSIFIER, |
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64 // Chopper have not found one or more splits that correspond to the correct |
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65 // character bounding boxes recorded in BlamerBundle::truth_word. |
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66 IRR_CHOPPER, |
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67 // Classifier did include correct unichars for each blob in the correct |
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68 // segmentation, however its rating could have been too bad to allow the |
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69 // language model to pull out the correct choice. On the other hand the |
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70 // strength of the language model might have been too weak to favor the |
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71 // correct answer, this we call this case a classifier-language model |
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72 // tradeoff error. |
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73 IRR_CLASS_LM_TRADEOFF, |
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74 // Page layout failed to produce the correct bounding box. Blame page layout |
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75 // if the truth was not found for the word, which implies that the bounding |
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76 // box of the word was incorrect (no truth word had a similar bounding box). |
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77 IRR_PAGE_LAYOUT, |
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78 // SegSearch heuristic prevented one or more blobs from the correct |
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79 // segmentation state to be classified (e.g. the blob was too wide). |
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80 IRR_SEGSEARCH_HEUR, |
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81 // The correct segmentaiton state was not explored because of poor SegSearch |
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82 // pain point prioritization. We blame SegSearch pain point prioritization |
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83 // if the best rating of a choice constructed from correct segmentation is |
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84 // better than that of the best choice (i.e. if we got to explore the correct |
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85 // segmentation state, language model would have picked the correct choice). |
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86 IRR_SEGSEARCH_PP, |
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87 // Same as IRR_CLASS_LM_TRADEOFF, but used when we only run chopper on a word, |
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88 // and thus use the old language model (permuters). |
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89 // TODO(antonova): integrate the new language mode with chopper |
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90 IRR_CLASS_OLD_LM_TRADEOFF, |
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91 // If there is an incorrect adaptive template match with a better score than |
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92 // a correct one (either pre-trained or adapted), mark this as adaption error. |
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93 IRR_ADAPTION, |
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94 // split_and_recog_word() failed to find a suitable split in truth. |
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95 IRR_NO_TRUTH_SPLIT, |
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96 // Truth is not available for this word (e.g. when words in corrected content |
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97 // file are turned into ~~~~ because an appropriate alignment was not found. |
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98 IRR_NO_TRUTH, |
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99 // The text recorded in best choice != truth text, but none of the above |
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100 // reasons are set. |
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101 IRR_UNKNOWN, |
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102 |
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103 IRR_NUM_REASONS |
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104 }; |
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105 |
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106 // Blamer-related information to determine the source of errors. |
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107 struct BlamerBundle { |
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108 static const char *IncorrectReasonName(IncorrectResultReason irr); |
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109 BlamerBundle() |
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110 : truth_has_char_boxes_(false) |
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111 , incorrect_result_reason_(IRR_CORRECT) |
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112 , lattice_data_(nullptr) { |
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113 ClearResults(); |
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114 } |
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115 BlamerBundle(const BlamerBundle &other) { |
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116 this->CopyTruth(other); |
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117 this->CopyResults(other); |
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118 } |
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119 ~BlamerBundle() { |
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120 delete[] lattice_data_; |
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121 } |
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122 |
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123 // Accessors. |
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124 std::string TruthString() const { |
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125 std::string truth_str; |
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126 for (auto &text : truth_text_) { |
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127 truth_str += text; |
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128 } |
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129 return truth_str; |
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130 } |
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131 IncorrectResultReason incorrect_result_reason() const { |
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132 return incorrect_result_reason_; |
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133 } |
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134 bool NoTruth() const { |
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135 return incorrect_result_reason_ == IRR_NO_TRUTH || incorrect_result_reason_ == IRR_PAGE_LAYOUT; |
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136 } |
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137 bool HasDebugInfo() const { |
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138 return debug_.length() > 0 || misadaption_debug_.length() > 0; |
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139 } |
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140 const std::string &debug() const { |
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141 return debug_; |
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142 } |
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143 const std::string &misadaption_debug() const { |
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144 return misadaption_debug_; |
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145 } |
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146 void UpdateBestRating(float rating) { |
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147 if (rating < best_correctly_segmented_rating_) { |
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148 best_correctly_segmented_rating_ = rating; |
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149 } |
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150 } |
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151 int correct_segmentation_length() const { |
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152 return correct_segmentation_cols_.size(); |
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153 } |
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154 // Returns true if the given ratings matrix col,row position is included |
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155 // in the correct segmentation path at the given index. |
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156 bool MatrixPositionCorrect(int index, const MATRIX_COORD &coord) { |
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157 return correct_segmentation_cols_[index] == coord.col && |
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158 correct_segmentation_rows_[index] == coord.row; |
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159 } |
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160 void set_best_choice_is_dict_and_top_choice(bool value) { |
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161 best_choice_is_dict_and_top_choice_ = value; |
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162 } |
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163 const char *lattice_data() const { |
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164 return lattice_data_; |
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165 } |
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166 int lattice_size() const { |
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167 return lattice_size_; // size of lattice_data in bytes |
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168 } |
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169 void set_lattice_data(const char *data, int size) { |
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170 lattice_size_ = size; |
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171 delete[] lattice_data_; |
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172 lattice_data_ = new char[lattice_size_]; |
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173 memcpy(lattice_data_, data, lattice_size_); |
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174 } |
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175 #ifndef DISABLED_LEGACY_ENGINE |
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176 const tesseract::ParamsTrainingBundle ¶ms_training_bundle() const { |
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177 return params_training_bundle_; |
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178 } |
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179 // Adds a new ParamsTrainingHypothesis to the current hypothesis list. |
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180 void AddHypothesis(const tesseract::ParamsTrainingHypothesis &hypo) { |
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181 params_training_bundle_.AddHypothesis(hypo); |
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182 } |
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183 #endif // ndef DISABLED_LEGACY_ENGINE |
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184 |
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185 // Functions to setup the blamer. |
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186 // Whole word string, whole word bounding box. |
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187 void SetWordTruth(const UNICHARSET &unicharset, const char *truth_str, const TBOX &word_box); |
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188 // Single "character" string, "character" bounding box. |
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189 // May be called multiple times to indicate the characters in a word. |
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190 void SetSymbolTruth(const UNICHARSET &unicharset, const char *char_str, const TBOX &char_box); |
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191 // Marks that there is something wrong with the truth text, like it contains |
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192 // reject characters. |
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193 void SetRejectedTruth(); |
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194 |
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195 // Returns true if the provided word_choice is correct. |
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196 bool ChoiceIsCorrect(const WERD_CHOICE *word_choice) const; |
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197 |
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198 void ClearResults() { |
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199 norm_truth_word_.DeleteAllBoxes(); |
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200 norm_box_tolerance_ = 0; |
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201 if (!NoTruth()) { |
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202 incorrect_result_reason_ = IRR_CORRECT; |
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203 } |
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204 debug_ = ""; |
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205 segsearch_is_looking_for_blame_ = false; |
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206 best_correctly_segmented_rating_ = WERD_CHOICE::kBadRating; |
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207 correct_segmentation_cols_.clear(); |
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208 correct_segmentation_rows_.clear(); |
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209 best_choice_is_dict_and_top_choice_ = false; |
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210 delete[] lattice_data_; |
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211 lattice_data_ = nullptr; |
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212 lattice_size_ = 0; |
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213 } |
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214 void CopyTruth(const BlamerBundle &other) { |
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215 truth_has_char_boxes_ = other.truth_has_char_boxes_; |
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216 truth_word_ = other.truth_word_; |
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217 truth_text_ = other.truth_text_; |
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218 incorrect_result_reason_ = (other.NoTruth() ? other.incorrect_result_reason_ : IRR_CORRECT); |
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219 } |
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220 void CopyResults(const BlamerBundle &other) { |
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221 norm_truth_word_ = other.norm_truth_word_; |
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222 norm_box_tolerance_ = other.norm_box_tolerance_; |
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223 incorrect_result_reason_ = other.incorrect_result_reason_; |
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224 segsearch_is_looking_for_blame_ = other.segsearch_is_looking_for_blame_; |
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225 best_correctly_segmented_rating_ = other.best_correctly_segmented_rating_; |
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226 correct_segmentation_cols_ = other.correct_segmentation_cols_; |
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227 correct_segmentation_rows_ = other.correct_segmentation_rows_; |
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228 best_choice_is_dict_and_top_choice_ = other.best_choice_is_dict_and_top_choice_; |
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229 if (other.lattice_data_ != nullptr) { |
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230 lattice_data_ = new char[other.lattice_size_]; |
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231 memcpy(lattice_data_, other.lattice_data_, other.lattice_size_); |
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232 lattice_size_ = other.lattice_size_; |
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233 } else { |
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234 lattice_data_ = nullptr; |
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235 } |
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236 } |
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237 const char *IncorrectReason() const; |
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238 |
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239 // Appends choice and truth details to the given debug string. |
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240 void FillDebugString(const std::string &msg, const WERD_CHOICE *choice, std::string &debug); |
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241 |
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242 // Sets up the norm_truth_word from truth_word using the given DENORM. |
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243 void SetupNormTruthWord(const DENORM &denorm); |
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244 |
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245 // Splits *this into two pieces in bundle1 and bundle2 (preallocated, empty |
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246 // bundles) where the right edge/ of the left-hand word is word1_right, |
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247 // and the left edge of the right-hand word is word2_left. |
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248 void SplitBundle(int word1_right, int word2_left, bool debug, BlamerBundle *bundle1, |
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249 BlamerBundle *bundle2) const; |
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250 // "Joins" the blames from bundle1 and bundle2 into *this. |
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251 void JoinBlames(const BlamerBundle &bundle1, const BlamerBundle &bundle2, bool debug); |
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252 |
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253 // If a blob with the same bounding box as one of the truth character |
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254 // bounding boxes is not classified as the corresponding truth character |
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255 // blames character classifier for incorrect answer. |
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256 void BlameClassifier(const UNICHARSET &unicharset, const TBOX &blob_box, |
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257 const BLOB_CHOICE_LIST &choices, bool debug); |
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258 |
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259 // Checks whether chops were made at all the character bounding box |
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260 // boundaries in word->truth_word. If not - blames the chopper for an |
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261 // incorrect answer. |
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262 void SetChopperBlame(const WERD_RES *word, bool debug); |
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263 // Blames the classifier or the language model if, after running only the |
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264 // chopper, best_choice is incorrect and no blame has been yet set. |
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265 // Blames the classifier if best_choice is classifier's top choice and is a |
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266 // dictionary word (i.e. language model could not have helped). |
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267 // Otherwise, blames the language model (formerly permuter word adjustment). |
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268 void BlameClassifierOrLangModel(const WERD_RES *word, const UNICHARSET &unicharset, |
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269 bool valid_permuter, bool debug); |
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270 // Sets up the correct_segmentation_* to mark the correct bounding boxes. |
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271 void SetupCorrectSegmentation(const TWERD *word, bool debug); |
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272 |
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273 // Returns true if a guided segmentation search is needed. |
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274 bool GuidedSegsearchNeeded(const WERD_CHOICE *best_choice) const; |
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275 // Setup ready to guide the segmentation search to the correct segmentation. |
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276 void InitForSegSearch(const WERD_CHOICE *best_choice, MATRIX *ratings, UNICHAR_ID wildcard_id, |
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277 bool debug, std::string &debug_str, tesseract::LMPainPoints *pain_points, |
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278 double max_char_wh_ratio, WERD_RES *word_res); |
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279 // Returns true if the guided segsearch is in progress. |
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280 bool GuidedSegsearchStillGoing() const; |
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281 // The segmentation search has ended. Sets the blame appropriately. |
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282 void FinishSegSearch(const WERD_CHOICE *best_choice, bool debug, std::string &debug_str); |
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283 |
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284 // If the bundle is null or still does not indicate the correct result, |
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285 // fix it and use some backup reason for the blame. |
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286 static void LastChanceBlame(bool debug, WERD_RES *word); |
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287 |
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288 // Sets the misadaption debug if this word is incorrect, as this word is |
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289 // being adapted to. |
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290 void SetMisAdaptionDebug(const WERD_CHOICE *best_choice, bool debug); |
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291 |
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292 private: |
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293 // Copy assignment operator (currently unused, therefore private). |
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294 BlamerBundle &operator=(const BlamerBundle &other) = delete; |
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295 void SetBlame(IncorrectResultReason irr, const std::string &msg, const WERD_CHOICE *choice, |
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296 bool debug) { |
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297 incorrect_result_reason_ = irr; |
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298 debug_ = IncorrectReason(); |
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299 debug_ += " to blame: "; |
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300 FillDebugString(msg, choice, debug_); |
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301 if (debug) { |
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302 tprintf("SetBlame(): %s", debug_.c_str()); |
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303 } |
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304 } |
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305 |
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306 private: |
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307 // Set to true when bounding boxes for individual unichars are recorded. |
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308 bool truth_has_char_boxes_; |
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309 // Variables used by the segmentation search when looking for the blame. |
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310 // Set to true while segmentation search is continued after the usual |
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311 // termination condition in order to look for the blame. |
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312 bool segsearch_is_looking_for_blame_; |
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313 // Set to true if best choice is a dictionary word and |
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314 // classifier's top choice. |
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315 bool best_choice_is_dict_and_top_choice_; |
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316 // Tolerance for bounding box comparisons in normalized space. |
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317 int norm_box_tolerance_; |
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318 // The true_word (in the original image coordinate space) contains ground |
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319 // truth bounding boxes for this WERD_RES. |
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320 tesseract::BoxWord truth_word_; |
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321 // Same as above, but in normalized coordinates |
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322 // (filled in by WERD_RES::SetupForRecognition()). |
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323 tesseract::BoxWord norm_truth_word_; |
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324 // Contains ground truth unichar for each of the bounding boxes in truth_word. |
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325 std::vector<std::string> truth_text_; |
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326 // The reason for incorrect OCR result. |
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327 IncorrectResultReason incorrect_result_reason_; |
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328 // Debug text associated with the blame. |
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329 std::string debug_; |
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330 // Misadaption debug information (filled in if this word was misadapted to). |
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331 std::string misadaption_debug_; |
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332 // Vectors populated by SegSearch to indicate column and row indices that |
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333 // correspond to blobs with correct bounding boxes. |
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334 std::vector<int> correct_segmentation_cols_; |
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335 std::vector<int> correct_segmentation_rows_; |
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336 // Best rating for correctly segmented path |
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337 // (set and used by SegSearch when looking for blame). |
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338 float best_correctly_segmented_rating_; |
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339 int lattice_size_; // size of lattice_data in bytes |
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340 // Serialized segmentation search lattice. |
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341 char *lattice_data_; |
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342 // Information about hypotheses (paths) explored by the segmentation search. |
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343 #ifndef DISABLED_LEGACY_ENGINE |
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344 tesseract::ParamsTrainingBundle params_training_bundle_; |
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345 #endif // ndef DISABLED_LEGACY_ENGINE |
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346 }; |
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ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
changeset
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347 |
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b50eed0cc0ef
ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
changeset
|
348 } // namespace tesseract |
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b50eed0cc0ef
ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
changeset
|
349 |
|
b50eed0cc0ef
ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
changeset
|
350 #endif // TESSERACT_CCSTRUCT_BLAMER_H_ |
