Mercurial > hgrepos > Python2 > PyMuPDF
annotate mupdf-source/thirdparty/tesseract/src/ccmain/linerec.cpp @ 21:2f43e400f144
Provide an "all" target to build both the sdist and the wheel
| author | Franz Glasner <fzglas.hg@dom66.de> |
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| date | Fri, 19 Sep 2025 10:28:53 +0200 |
| parents | b50eed0cc0ef |
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| rev | line source |
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2
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1 /////////////////////////////////////////////////////////////////////// |
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2 // File: linerec.cpp |
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3 // Description: Top-level line-based recognition module for Tesseract. |
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4 // Author: Ray Smith |
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5 // |
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6 // (C) Copyright 2013, Google Inc. |
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7 // Licensed under the Apache License, Version 2.0 (the "License"); |
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8 // you may not use this file except in compliance with the License. |
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9 // You may obtain a copy of the License at |
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10 // http://www.apache.org/licenses/LICENSE-2.0 |
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11 // Unless required by applicable law or agreed to in writing, software |
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12 // distributed under the License is distributed on an "AS IS" BASIS, |
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13 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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14 // See the License for the specific language governing permissions and |
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15 // limitations under the License. |
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16 /////////////////////////////////////////////////////////////////////// |
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17 |
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18 #include "tesseractclass.h" |
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19 |
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20 #include <allheaders.h> |
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21 #include "boxread.h" |
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22 #include "imagedata.h" // for ImageData |
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23 #include "lstmrecognizer.h" |
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24 #include "pageres.h" |
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25 #include "recodebeam.h" |
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26 #include "tprintf.h" |
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27 |
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28 #include <algorithm> |
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29 |
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30 namespace tesseract { |
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31 |
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32 // Scale factor to make certainty more comparable to Tesseract. |
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33 const float kCertaintyScale = 7.0f; |
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34 // Worst acceptable certainty for a dictionary word. |
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35 const float kWorstDictCertainty = -25.0f; |
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36 |
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37 // Generates training data for training a line recognizer, eg LSTM. |
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38 // Breaks the page into lines, according to the boxes, and writes them to a |
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39 // serialized DocumentData based on output_basename. |
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40 // Return true if successful, false if an error occurred. |
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41 bool Tesseract::TrainLineRecognizer(const char *input_imagename, const std::string &output_basename, |
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42 BLOCK_LIST *block_list) { |
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43 std::string lstmf_name = output_basename + ".lstmf"; |
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44 DocumentData images(lstmf_name); |
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45 if (applybox_page > 0) { |
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46 // Load existing document for the previous pages. |
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47 if (!images.LoadDocument(lstmf_name.c_str(), 0, 0, nullptr)) { |
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48 tprintf("Failed to read training data from %s!\n", lstmf_name.c_str()); |
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49 return false; |
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50 } |
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51 } |
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52 std::vector<TBOX> boxes; |
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53 std::vector<std::string> texts; |
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54 // Get the boxes for this page, if there are any. |
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55 if (!ReadAllBoxes(applybox_page, false, input_imagename, &boxes, &texts, nullptr, nullptr) || |
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56 boxes.empty()) { |
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57 tprintf("Failed to read boxes from %s\n", input_imagename); |
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58 return false; |
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59 } |
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60 TrainFromBoxes(boxes, texts, block_list, &images); |
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61 if (images.PagesSize() == 0) { |
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62 tprintf("Failed to read pages from %s\n", input_imagename); |
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63 return false; |
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64 } |
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65 images.Shuffle(); |
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66 if (!images.SaveDocument(lstmf_name.c_str(), nullptr)) { |
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67 tprintf("Failed to write training data to %s!\n", lstmf_name.c_str()); |
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68 return false; |
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69 } |
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70 return true; |
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71 } |
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72 |
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73 // Generates training data for training a line recognizer, eg LSTM. |
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74 // Breaks the boxes into lines, normalizes them, converts to ImageData and |
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75 // appends them to the given training_data. |
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76 void Tesseract::TrainFromBoxes(const std::vector<TBOX> &boxes, const std::vector<std::string> &texts, |
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77 BLOCK_LIST *block_list, DocumentData *training_data) { |
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78 auto box_count = boxes.size(); |
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79 // Process all the text lines in this page, as defined by the boxes. |
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80 unsigned end_box = 0; |
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81 // Don't let \t, which marks newlines in the box file, get into the line |
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82 // content, as that makes the line unusable in training. |
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83 while (end_box < texts.size() && texts[end_box] == "\t") { |
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84 ++end_box; |
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85 } |
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86 for (auto start_box = end_box; start_box < box_count; start_box = end_box) { |
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87 // Find the textline of boxes starting at start and their bounding box. |
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88 TBOX line_box = boxes[start_box]; |
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89 std::string line_str = texts[start_box]; |
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90 for (end_box = start_box + 1; end_box < box_count && texts[end_box] != "\t"; ++end_box) { |
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91 line_box += boxes[end_box]; |
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92 line_str += texts[end_box]; |
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93 } |
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94 // Find the most overlapping block. |
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95 BLOCK *best_block = nullptr; |
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96 int best_overlap = 0; |
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|
97 BLOCK_IT b_it(block_list); |
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98 for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) { |
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99 BLOCK *block = b_it.data(); |
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100 if (block->pdblk.poly_block() != nullptr && !block->pdblk.poly_block()->IsText()) { |
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101 continue; // Not a text block. |
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102 } |
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103 TBOX block_box = block->pdblk.bounding_box(); |
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104 block_box.rotate(block->re_rotation()); |
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105 if (block_box.major_overlap(line_box)) { |
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106 TBOX overlap_box = line_box.intersection(block_box); |
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107 if (overlap_box.area() > best_overlap) { |
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108 best_overlap = overlap_box.area(); |
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109 best_block = block; |
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110 } |
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111 } |
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112 } |
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113 ImageData *imagedata = nullptr; |
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114 if (best_block == nullptr) { |
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115 tprintf("No block overlapping textline: %s\n", line_str.c_str()); |
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116 } else { |
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117 imagedata = GetLineData(line_box, boxes, texts, start_box, end_box, *best_block); |
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118 } |
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119 if (imagedata != nullptr) { |
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120 training_data->AddPageToDocument(imagedata); |
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121 } |
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122 // Don't let \t, which marks newlines in the box file, get into the line |
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123 // content, as that makes the line unusable in training. |
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124 while (end_box < texts.size() && texts[end_box] == "\t") { |
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125 ++end_box; |
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126 } |
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127 } |
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128 } |
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129 |
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130 // Returns an Imagedata containing the image of the given box, |
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131 // and ground truth boxes/truth text if available in the input. |
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132 // The image is not normalized in any way. |
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133 ImageData *Tesseract::GetLineData(const TBOX &line_box, const std::vector<TBOX> &boxes, |
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134 const std::vector<std::string> &texts, int start_box, int end_box, |
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135 const BLOCK &block) { |
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136 TBOX revised_box; |
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137 ImageData *image_data = GetRectImage(line_box, block, kImagePadding, &revised_box); |
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138 if (image_data == nullptr) { |
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139 return nullptr; |
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140 } |
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141 image_data->set_page_number(applybox_page); |
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142 // Copy the boxes and shift them so they are relative to the image. |
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143 FCOORD block_rotation(block.re_rotation().x(), -block.re_rotation().y()); |
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144 ICOORD shift = -revised_box.botleft(); |
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145 std::vector<TBOX> line_boxes; |
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146 std::vector<std::string> line_texts; |
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147 for (int b = start_box; b < end_box; ++b) { |
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148 TBOX box = boxes[b]; |
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149 box.rotate(block_rotation); |
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150 box.move(shift); |
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|
151 line_boxes.push_back(box); |
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152 line_texts.push_back(texts[b]); |
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153 } |
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|
154 std::vector<int> page_numbers(line_boxes.size(), applybox_page); |
|
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|
155 image_data->AddBoxes(line_boxes, line_texts, page_numbers); |
|
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156 return image_data; |
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157 } |
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158 |
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159 // Helper gets the image of a rectangle, using the block.re_rotation() if |
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160 // needed to get to the image, and rotating the result back to horizontal |
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161 // layout. (CJK characters will be on their left sides) The vertical text flag |
|
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162 // is set in the returned ImageData if the text was originally vertical, which |
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163 // can be used to invoke a different CJK recognition engine. The revised_box |
|
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164 // is also returned to enable calculation of output bounding boxes. |
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|
165 ImageData *Tesseract::GetRectImage(const TBOX &box, const BLOCK &block, int padding, |
|
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|
166 TBOX *revised_box) const { |
|
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167 TBOX wbox = box; |
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|
168 wbox.pad(padding, padding); |
|
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|
169 *revised_box = wbox; |
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170 // Number of clockwise 90 degree rotations needed to get back to tesseract |
|
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171 // coords from the clipped image. |
|
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|
172 int num_rotations = 0; |
|
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|
173 if (block.re_rotation().y() > 0.0f) { |
|
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parents:
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|
174 num_rotations = 1; |
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parents:
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|
175 } else if (block.re_rotation().x() < 0.0f) { |
|
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parents:
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176 num_rotations = 2; |
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parents:
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|
177 } else if (block.re_rotation().y() < 0.0f) { |
|
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ADD: MuPDF v1.26.7: the MuPDF source as downloaded by a default build of PyMuPDF 1.26.4.
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178 num_rotations = 3; |
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parents:
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179 } |
|
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parents:
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180 // Handle two cases automatically: 1 the box came from the block, 2 the box |
|
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parents:
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181 // came from a box file, and refers to the image, which the block may not. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
182 if (block.pdblk.bounding_box().major_overlap(*revised_box)) { |
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
183 revised_box->rotate(block.re_rotation()); |
|
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parents:
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184 } |
|
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parents:
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|
185 // Now revised_box always refers to the image. |
|
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parents:
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186 // BestPix is never colormapped, but may be of any depth. |
|
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parents:
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187 Image pix = BestPix(); |
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parents:
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188 int width = pixGetWidth(pix); |
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parents:
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189 int height = pixGetHeight(pix); |
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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:
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190 TBOX image_box(0, 0, width, height); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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191 // Clip to image bounds; |
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
192 *revised_box &= image_box; |
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parents:
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193 if (revised_box->null_box()) { |
|
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parents:
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194 return nullptr; |
|
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parents:
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195 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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196 Box *clip_box = boxCreate(revised_box->left(), height - revised_box->top(), revised_box->width(), |
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
197 revised_box->height()); |
|
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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:
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|
198 Image box_pix = pixClipRectangle(pix, clip_box, nullptr); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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199 boxDestroy(&clip_box); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
200 if (box_pix == nullptr) { |
|
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parents:
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201 return nullptr; |
|
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parents:
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|
202 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
203 if (num_rotations > 0) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
204 Image rot_pix = pixRotateOrth(box_pix, num_rotations); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
205 box_pix.destroy(); |
|
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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:
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|
206 box_pix = rot_pix; |
|
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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:
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|
207 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
208 // Convert sub-8-bit images to 8 bit. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
209 int depth = pixGetDepth(box_pix); |
|
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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:
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|
210 if (depth < 8) { |
|
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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:
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|
211 Image grey; |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
212 grey = pixConvertTo8(box_pix, false); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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213 box_pix.destroy(); |
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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
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|
214 box_pix = grey; |
|
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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:
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|
215 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
216 bool vertical_text = false; |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
217 if (num_rotations > 0) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
218 // Rotated the clipped revised box back to internal coordinates. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
219 FCOORD rotation(block.re_rotation().x(), -block.re_rotation().y()); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
220 revised_box->rotate(rotation); |
|
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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:
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|
221 if (num_rotations != 2) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
222 vertical_text = true; |
|
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parents:
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223 } |
|
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parents:
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224 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
225 return new ImageData(vertical_text, box_pix); |
|
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parents:
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|
226 } |
|
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parents:
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|
227 |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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228 // Recognizes a word or group of words, converting to WERD_RES in *words. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
229 // Analogous to classify_word_pass1, but can handle a group of words as well. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
230 void Tesseract::LSTMRecognizeWord(const BLOCK &block, ROW *row, WERD_RES *word, |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
231 PointerVector<WERD_RES> *words) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
232 TBOX word_box = word->word->bounding_box(); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
233 // Get the word image - no frills. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
234 if (tessedit_pageseg_mode == PSM_SINGLE_WORD || tessedit_pageseg_mode == PSM_RAW_LINE) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
235 // In single word mode, use the whole image without any other row/word |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
236 // interpretation. |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
237 word_box = TBOX(0, 0, ImageWidth(), ImageHeight()); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
238 } else { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
239 float baseline = row->base_line((word_box.left() + word_box.right()) / 2); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
240 if (baseline + row->descenders() < word_box.bottom()) { |
|
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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:
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|
241 word_box.set_bottom(baseline + row->descenders()); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
242 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
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|
243 if (baseline + row->x_height() + row->ascenders() > word_box.top()) { |
|
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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:
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|
244 word_box.set_top(baseline + row->x_height() + row->ascenders()); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
245 } |
|
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parents:
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246 } |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
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|
247 ImageData *im_data = GetRectImage(word_box, block, kImagePadding, &word_box); |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
248 if (im_data == nullptr) { |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
249 return; |
|
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parents:
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|
250 } |
|
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parents:
diff
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|
251 |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
252 bool do_invert = tessedit_do_invert; |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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|
253 float threshold = do_invert ? double(invert_threshold) : 0.0f; |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
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|
254 lstm_recognizer_->RecognizeLine(*im_data, threshold, classify_debug_level > 0, |
|
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff
changeset
|
255 kWorstDictCertainty / kCertaintyScale, word_box, words, |
|
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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
|
256 lstm_choice_mode, lstm_choice_iterations); |
|
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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
|
257 delete im_data; |
|
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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
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|
258 SearchWords(words); |
|
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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
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259 } |
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260 |
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261 // Apply segmentation search to the given set of words, within the constraints |
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262 // of the existing ratings matrix. If there is already a best_choice on a word |
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263 // leaves it untouched and just sets the done/accepted etc flags. |
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264 void Tesseract::SearchWords(PointerVector<WERD_RES> *words) { |
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265 // Run the segmentation search on the network outputs and make a BoxWord |
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266 // for each of the output words. |
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267 // If we drop a word as junk, then there is always a space in front of the |
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268 // next. |
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269 const Dict *stopper_dict = lstm_recognizer_->GetDict(); |
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270 if (stopper_dict == nullptr) { |
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271 stopper_dict = &getDict(); |
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272 } |
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273 for (unsigned w = 0; w < words->size(); ++w) { |
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274 WERD_RES *word = (*words)[w]; |
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275 if (word->best_choice == nullptr) { |
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276 // It is a dud. |
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277 word->SetupFake(lstm_recognizer_->GetUnicharset()); |
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278 } else { |
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279 // Set the best state. |
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280 for (unsigned i = 0; i < word->best_choice->length(); ++i) { |
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281 int length = word->best_choice->state(i); |
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282 word->best_state.push_back(length); |
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283 } |
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284 word->reject_map.initialise(word->best_choice->length()); |
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285 word->tess_failed = false; |
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286 word->tess_accepted = true; |
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287 word->tess_would_adapt = false; |
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288 word->done = true; |
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289 word->tesseract = this; |
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290 float word_certainty = std::min(word->space_certainty, word->best_choice->certainty()); |
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291 word_certainty *= kCertaintyScale; |
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292 if (getDict().stopper_debug_level >= 1) { |
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293 tprintf("Best choice certainty=%g, space=%g, scaled=%g, final=%g\n", |
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294 word->best_choice->certainty(), word->space_certainty, |
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295 std::min(word->space_certainty, word->best_choice->certainty()) * kCertaintyScale, |
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296 word_certainty); |
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297 word->best_choice->print(); |
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298 } |
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299 word->best_choice->set_certainty(word_certainty); |
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300 |
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301 word->tess_accepted = stopper_dict->AcceptableResult(word); |
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302 } |
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303 } |
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304 } |
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305 |
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306 } // namespace tesseract. |
