Mercurial > hgrepos > Python2 > PyMuPDF

annotate mupdf-source/thirdparty/tesseract/src/classify/trainingsample.h @ 46:7ee69f120f19 default tip

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>>>>> tag v1.26.5+1 for changeset b74429b0f5c4
author Franz Glasner <fzglas.hg@dom66.de>
date Sat, 11 Oct 2025 17:17:30 +0200
parents b50eed0cc0ef
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
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1 // Copyright 2010 Google Inc. All Rights Reserved.
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2 // Author: rays@google.com (Ray Smith)
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3 //
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4 // Licensed under the Apache License, Version 2.0 (the "License");
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5 // you may not use this file except in compliance with the License.
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6 // You may obtain a copy of the License at
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7 // http://www.apache.org/licenses/LICENSE-2.0
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8 // Unless required by applicable law or agreed to in writing, software
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9 // distributed under the License is distributed on an "AS IS" BASIS,
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10 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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11 // See the License for the specific language governing permissions and
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12 // limitations under the License.
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13 //
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14 ///////////////////////////////////////////////////////////////////////
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15
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16 #ifndef TESSERACT_TRAINING_TRAININGSAMPLE_H_
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17 #define TESSERACT_TRAINING_TRAININGSAMPLE_H_
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18
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19 #include "elst.h"
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20 #include "featdefs.h"
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21 #include "intfx.h"
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22 #include "intmatcher.h"
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23 #include "matrix.h"
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24 #include "mf.h"
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25 #include "mfdefs.h"
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26 #include "picofeat.h"
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27 #include "shapetable.h"
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28 #include "unicharset.h"
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30 struct Pix;
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32 namespace tesseract {
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33
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34 class IntFeatureMap;
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35 class IntFeatureSpace;
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36 class ShapeTable;
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37
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38 // Number of elements of cn_feature_.
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39 static const int kNumCNParams = 4;
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40 // Number of ways to shift the features when randomizing.
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41 static const int kSampleYShiftSize = 5;
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42 // Number of ways to scale the features when randomizing.
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43 static const int kSampleScaleSize = 3;
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44 // Total number of different ways to manipulate the features when randomizing.
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45 // The first and last combinations are removed to avoid an excessive
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46 // top movement (first) and an identity transformation (last).
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47 // WARNING: To avoid patterned duplication of samples, be sure to keep
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48 // kSampleRandomSize prime!
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49 // Eg with current values (kSampleYShiftSize = 5 and TkSampleScaleSize = 3)
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50 // kSampleRandomSize is 13, which is prime.
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51 static const int kSampleRandomSize = kSampleYShiftSize * kSampleScaleSize - 2;
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52 // ASSERT_IS_PRIME(kSampleRandomSize) !!
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53
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54 class TESS_API TrainingSample : public ELIST_LINK {
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55 public:
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56 TrainingSample()
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57 : class_id_(INVALID_UNICHAR_ID)
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58 , font_id_(0)
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59 , page_num_(0)
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60 , num_features_(0)
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61 , num_micro_features_(0)
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62 , outline_length_(0)
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63 , features_(nullptr)
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64 , micro_features_(nullptr)
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65 , weight_(1.0)
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66 , max_dist_(0.0)
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67 , sample_index_(0)
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68 , features_are_indexed_(false)
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69 , features_are_mapped_(false)
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70 , is_error_(false) {}
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71 ~TrainingSample();
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72
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73 // Saves the given features into a TrainingSample. The features are copied,
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74 // so may be deleted afterwards. Delete the return value after use.
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75 static TrainingSample *CopyFromFeatures(const INT_FX_RESULT_STRUCT &fx_info,
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76 const TBOX &bounding_box,
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77 const INT_FEATURE_STRUCT *features, int num_features);
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78 // Returns the cn_feature as a FEATURE_STRUCT* needed by cntraining.
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79 FEATURE_STRUCT *GetCNFeature() const;
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80 // Constructs and returns a copy "randomized" by the method given by
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81 // the randomizer index. If index is out of [0, kSampleRandomSize) then
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82 // an exact copy is returned.
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83 TrainingSample *RandomizedCopy(int index) const;
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84 // Constructs and returns an exact copy.
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85 TrainingSample *Copy() const;
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86
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87 // WARNING! Serialize/DeSerialize do not save/restore the "cache" data
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88 // members, which is mostly the mapped features, and the weight.
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89 // It is assumed these can all be reconstructed from what is saved.
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90 // Writes to the given file. Returns false in case of error.
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91 bool Serialize(FILE *fp) const;
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92 // Creates from the given file. Returns nullptr in case of error.
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93 // If swap is true, assumes a big/little-endian swap is needed.
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94 static TrainingSample *DeSerializeCreate(bool swap, FILE *fp);
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95 // Reads from the given file. Returns false in case of error.
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96 // If swap is true, assumes a big/little-endian swap is needed.
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97 bool DeSerialize(bool swap, FILE *fp);
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98
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99 // Extracts the needed information from the CHAR_DESC_STRUCT.
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diff changeset
100 void ExtractCharDesc(int feature_type, int micro_type, int cn_type, int geo_type,
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diff changeset
101 CHAR_DESC_STRUCT *char_desc);
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102
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103 // Sets the mapped_features_ from the features_ using the provided
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104 // feature_space to the indexed versions of the features.
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105 void IndexFeatures(const IntFeatureSpace &feature_space);
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106
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107 // Returns a pix representing the sample. (Int features only.)
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108 Image RenderToPix(const UNICHARSET *unicharset) const;
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109 // Displays the features in the given window with the given color.
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110 void DisplayFeatures(ScrollView::Color color, ScrollView *window) const;
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111
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112 // Returns a pix of the original sample image. The pix is padded all round
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113 // by padding wherever possible.
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114 // The returned Pix must be pixDestroyed after use.
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115 // If the input page_pix is nullptr, nullptr is returned.
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116 Image GetSamplePix(int padding, Image page_pix) const;
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117
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118 // Accessors.
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119 UNICHAR_ID class_id() const {
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120 return class_id_;
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121 }
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122 void set_class_id(int id) {
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123 class_id_ = id;
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124 }
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parents:
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125 int font_id() const {
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126 return font_id_;
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127 }
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128 void set_font_id(int id) {
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129 font_id_ = id;
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130 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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131 int page_num() const {
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parents:
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132 return page_num_;
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133 }
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parents:
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134 void set_page_num(int page) {
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135 page_num_ = page;
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136 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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137 const TBOX &bounding_box() const {
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parents:
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138 return bounding_box_;
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139 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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140 void set_bounding_box(const TBOX &box) {
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141 bounding_box_ = box;
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142 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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143 uint32_t num_features() const {
b50eed0cc0ef ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
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parents:
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144 return num_features_;
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145 }
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parents:
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146 const INT_FEATURE_STRUCT *features() const {
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147 return features_;
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148 }
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149 uint32_t num_micro_features() const {
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150 return num_micro_features_;
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151 }
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parents:
diff changeset
152 const MicroFeature *micro_features() const {
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153 return micro_features_;
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154 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
155 int outline_length() const {
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156 return outline_length_;
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parents:
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157 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
158 float cn_feature(int index) const {
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parents:
diff changeset
159 return cn_feature_[index];
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160 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
161 int geo_feature(int index) const {
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parents:
diff changeset
162 return geo_feature_[index];
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163 }
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parents:
diff changeset
164 double weight() const {
b50eed0cc0ef ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
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parents:
diff changeset
165 return weight_;
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166 }
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parents:
diff changeset
167 void set_weight(double value) {
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parents:
diff changeset
168 weight_ = value;
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169 }
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parents:
diff changeset
170 double max_dist() const {
b50eed0cc0ef ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
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parents:
diff changeset
171 return max_dist_;
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172 }
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parents:
diff changeset
173 void set_max_dist(double value) {
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parents:
diff changeset
174 max_dist_ = value;
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175 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
176 int sample_index() const {
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diff changeset
177 return sample_index_;
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178 }
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parents:
diff changeset
179 void set_sample_index(int value) {
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diff changeset
180 sample_index_ = value;
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181 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
182 bool features_are_mapped() const {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
183 return features_are_mapped_;
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184 }
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parents:
diff changeset
185 const std::vector<int> &mapped_features() const {
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parents:
diff changeset
186 ASSERT_HOST(features_are_mapped_);
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parents:
diff changeset
187 return mapped_features_;
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188 }
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parents:
diff changeset
189 const std::vector<int> &indexed_features() const {
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parents:
diff changeset
190 ASSERT_HOST(features_are_indexed_);
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parents:
diff changeset
191 return mapped_features_;
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192 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
193 bool is_error() const {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
194 return is_error_;
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diff changeset
195 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
196 void set_is_error(bool value) {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
197 is_error_ = value;
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diff changeset
198 }
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parents:
diff changeset
199
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parents:
diff changeset
200 private:
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>
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201 // Unichar id that this sample represents. There obviously must be a
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202 // reference UNICHARSET somewhere. Usually in TrainingSampleSet.
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203 UNICHAR_ID class_id_;
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204 // Font id in which this sample was printed. Refers to a fontinfo_table_ in
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205 // MasterTrainer.
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206 int font_id_;
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207 // Number of page that the sample came from.
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208 int page_num_;
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209 // Bounding box of sample in original image.
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210 TBOX bounding_box_;
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211 // Number of INT_FEATURE_STRUCT in features_ array.
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212 uint32_t num_features_;
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213 // Number of MicroFeature in micro_features_ array.
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214 uint32_t num_micro_features_;
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215 // Total length of outline in the baseline normalized coordinate space.
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216 // See comment in WERD_RES class definition for a discussion of coordinate
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217 // spaces.
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218 int outline_length_;
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219 // Array of features.
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220 INT_FEATURE_STRUCT *features_;
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221 // Array of features.
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222 MicroFeature *micro_features_;
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223 // The one and only CN feature. Indexed by NORM_PARAM_NAME enum.
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224 float cn_feature_[kNumCNParams];
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225 // The one and only geometric feature. (Aims at replacing cn_feature_).
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226 // Indexed by GeoParams enum in picofeat.h
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227 int geo_feature_[GeoCount];
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228
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229 // Non-serialized cache data.
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230 // Weight used for boosting training.
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231 double weight_;
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232 // Maximum distance to other samples of same class/font used in computing
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233 // the canonical sample.
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234 double max_dist_;
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235 // Global index of this sample.
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236 int sample_index_;
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237
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238 public:
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239 // both are used in training tools
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240 // hide after refactoring
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241
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242 // Indexed/mapped features, as indicated by the bools below.
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243 std::vector<int> mapped_features_;
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244 bool features_are_indexed_;
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245 bool features_are_mapped_;
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246
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247 private:
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248 // True if the last classification was an error by the current definition.
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249 bool is_error_;
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250
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251 // Randomizing factors.
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252 static const int kYShiftValues[kSampleYShiftSize];
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253 static const double kScaleValues[kSampleScaleSize];
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254 };
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255
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256 ELISTIZEH(TrainingSample)
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257
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258 } // namespace tesseract
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259
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260 #endif // TESSERACT_TRAINING_TRAININGSAMPLE_H_