annotate mupdf-source/thirdparty/tesseract/src/lstm/lstmrecognizer.h @ 21:2f43e400f144

Provide an "all" target to build both the sdist and the wheel
author Franz Glasner <fzglas.hg@dom66.de>
date Fri, 19 Sep 2025 10:28:53 +0200
parents b50eed0cc0ef
children
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rev   line source
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1 ///////////////////////////////////////////////////////////////////////
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2 // File: lstmrecognizer.h
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3 // Description: Top-level line recognizer class for LSTM-based networks.
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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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18 #ifndef TESSERACT_LSTM_LSTMRECOGNIZER_H_
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19 #define TESSERACT_LSTM_LSTMRECOGNIZER_H_
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21 #include "ccutil.h"
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22 #include "helpers.h"
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23 #include "matrix.h"
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24 #include "network.h"
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25 #include "networkscratch.h"
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26 #include "params.h"
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27 #include "recodebeam.h"
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28 #include "series.h"
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29 #include "unicharcompress.h"
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31 class BLOB_CHOICE_IT;
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32 struct Pix;
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33 class ROW_RES;
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34 class ScrollView;
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35 class TBOX;
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36 class WERD_RES;
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38 namespace tesseract {
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40 class Dict;
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41 class ImageData;
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43 // Enum indicating training mode control flags.
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44 enum TrainingFlags {
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45 TF_INT_MODE = 1,
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46 TF_COMPRESS_UNICHARSET = 64,
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47 };
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49 // Top-level line recognizer class for LSTM-based networks.
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50 // Note that a sub-class, LSTMTrainer is used for training.
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51 class TESS_API LSTMRecognizer {
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52 public:
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53 LSTMRecognizer();
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54 LSTMRecognizer(const std::string &language_data_path_prefix);
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55 ~LSTMRecognizer();
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56
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57 int NumOutputs() const {
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58 return network_->NumOutputs();
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59 }
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60
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61 // Return the training iterations.
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62 int training_iteration() const {
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63 return training_iteration_;
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64 }
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65
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66 // Return the sample iterations.
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67 int sample_iteration() const {
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68 return sample_iteration_;
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69 }
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70
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71 // Return the learning rate.
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72 float learning_rate() const {
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73 return learning_rate_;
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74 }
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75
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76 LossType OutputLossType() const {
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77 if (network_ == nullptr) {
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78 return LT_NONE;
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79 }
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80 StaticShape shape;
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81 shape = network_->OutputShape(shape);
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82 return shape.loss_type();
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83 }
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84 bool SimpleTextOutput() const {
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85 return OutputLossType() == LT_SOFTMAX;
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86 }
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87 bool IsIntMode() const {
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88 return (training_flags_ & TF_INT_MODE) != 0;
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89 }
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90 // True if recoder_ is active to re-encode text to a smaller space.
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91 bool IsRecoding() const {
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92 return (training_flags_ & TF_COMPRESS_UNICHARSET) != 0;
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93 }
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94 // Returns true if the network is a TensorFlow network.
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95 bool IsTensorFlow() const {
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96 return network_->type() == NT_TENSORFLOW;
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97 }
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98 // Returns a vector of layer ids that can be passed to other layer functions
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99 // to access a specific layer.
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100 std::vector<std::string> EnumerateLayers() const {
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101 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
102 auto *series = static_cast<Series *>(network_);
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
103 std::vector<std::string> layers;
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
104 series->EnumerateLayers(nullptr, layers);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
105 return layers;
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parents:
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106 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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107 // Returns a specific layer from its id (from EnumerateLayers).
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parents:
diff changeset
108 Network *GetLayer(const std::string &id) 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
109 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
110 ASSERT_HOST(id.length() > 1 && id[0] == ':');
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
111 auto *series = static_cast<Series *>(network_);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
112 return series->GetLayer(&id[1]);
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113 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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114 // Returns the learning rate of the layer from its id.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
115 float GetLayerLearningRate(const std::string &id) 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
116 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
117 if (network_->TestFlag(NF_LAYER_SPECIFIC_LR)) {
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:
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118 ASSERT_HOST(id.length() > 1 && id[0] == ':');
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
119 auto *series = static_cast<Series *>(network_);
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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120 return series->LayerLearningRate(&id[1]);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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121 } else {
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Franz Glasner <fzglas.hg@dom66.de>
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122 return learning_rate_;
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123 }
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124 }
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125
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126 // Return the network string.
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127 const char *GetNetwork() const {
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128 return network_str_.c_str();
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129 }
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130
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131 // Return the adam beta.
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parents:
diff changeset
132 float GetAdamBeta() const {
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133 return adam_beta_;
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134 }
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parents:
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135
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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136 // Return the momentum.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
137 float GetMomentum() const {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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138 return momentum_;
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139 }
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parents:
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140
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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141 // Multiplies the all the learning rate(s) by the given factor.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
142 void ScaleLearningRate(double factor) {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
143 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
144 learning_rate_ *= factor;
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parents:
diff changeset
145 if (network_->TestFlag(NF_LAYER_SPECIFIC_LR)) {
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
146 std::vector<std::string> layers = EnumerateLayers();
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
147 for (auto &layer : layers) {
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parents:
diff changeset
148 ScaleLayerLearningRate(layer, factor);
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parents:
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149 }
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parents:
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150 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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151 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
152 // Multiplies the learning rate of the layer with id, by the given factor.
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
153 void ScaleLayerLearningRate(const std::string &id, double factor) {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
154 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
155 ASSERT_HOST(id.length() > 1 && id[0] == ':');
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
156 auto *series = static_cast<Series *>(network_);
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
157 series->ScaleLayerLearningRate(&id[1], factor);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
158 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
159
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
160 // Set the all the learning rate(s) to the given value.
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
161 void SetLearningRate(float learning_rate)
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
162 {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
163 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
164 learning_rate_ = learning_rate;
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
165 if (network_->TestFlag(NF_LAYER_SPECIFIC_LR)) {
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
166 for (auto &id : EnumerateLayers()) {
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
167 SetLayerLearningRate(id, learning_rate);
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
168 }
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
169 }
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
170 }
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
171 // Set the learning rate of the layer with id, by the given value.
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
172 void SetLayerLearningRate(const std::string &id, float learning_rate)
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
173 {
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
174 ASSERT_HOST(network_ != nullptr && network_->type() == NT_SERIES);
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
175 ASSERT_HOST(id.length() > 1 && id[0] == ':');
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
176 auto *series = static_cast<Series *>(network_);
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
177 series->SetLayerLearningRate(&id[1], learning_rate);
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
178 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
179
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
180 // Converts the network to int if not already.
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
181 void ConvertToInt() {
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
182 if ((training_flags_ & TF_INT_MODE) == 0) {
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
183 network_->ConvertToInt();
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
184 training_flags_ |= TF_INT_MODE;
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
185 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
186 }
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
187
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
188 // Provides access to the UNICHARSET that this classifier works with.
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
189 const UNICHARSET &GetUnicharset() const {
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
190 return ccutil_.unicharset;
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
191 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
192 UNICHARSET &GetUnicharset() {
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
193 return ccutil_.unicharset;
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
194 }
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
195 // Provides access to the UnicharCompress that this classifier works with.
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
196 const UnicharCompress &GetRecoder() const {
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
197 return recoder_;
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
198 }
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
199 // Provides access to the Dict that this classifier works with.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
200 const Dict *GetDict() const {
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
201 return dict_;
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
202 }
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203 Dict *GetDict() {
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204 return dict_;
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205 }
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206 // Sets the sample iteration to the given value. The sample_iteration_
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parents:
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207 // determines the seed for the random number generator. The training
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208 // iteration is incremented only by a successful training iteration.
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209 void SetIteration(int iteration) {
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210 sample_iteration_ = iteration;
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211 }
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212 // Accessors for textline image normalization.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
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213 int NumInputs() const {
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214 return network_->NumInputs();
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215 }
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216
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217 // Return the null char index.
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218 int null_char() const {
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219 return null_char_;
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220 }
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221
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222 // Loads a model from mgr, including the dictionary only if lang is not null.
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223 bool Load(const ParamsVectors *params, const std::string &lang, TessdataManager *mgr);
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224
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225 // Writes to the given file. Returns false in case of error.
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226 // If mgr contains a unicharset and recoder, then they are not encoded to fp.
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227 bool Serialize(const TessdataManager *mgr, TFile *fp) const;
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228 // Reads from the given file. Returns false in case of error.
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229 // If mgr contains a unicharset and recoder, then they are taken from there,
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230 // otherwise, they are part of the serialization in fp.
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231 bool DeSerialize(const TessdataManager *mgr, TFile *fp);
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232 // Loads the charsets from mgr.
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233 bool LoadCharsets(const TessdataManager *mgr);
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234 // Loads the Recoder.
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parents:
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235 bool LoadRecoder(TFile *fp);
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236 // Loads the dictionary if possible from the traineddata file.
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237 // Prints a warning message, and returns false but otherwise fails silently
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238 // and continues to work without it if loading fails.
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239 // Note that dictionary load is independent from DeSerialize, but dependent
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240 // on the unicharset matching. This enables training to deserialize a model
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241 // from checkpoint or restore without having to go back and reload the
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242 // dictionary.
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parents:
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243 bool LoadDictionary(const ParamsVectors *params, const std::string &lang, TessdataManager *mgr);
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244
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245 // Recognizes the line image, contained within image_data, returning the
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246 // recognized tesseract WERD_RES for the words.
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247 // If invert_threshold > 0, tries inverted as well if the normal
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248 // interpretation doesn't produce a result which at least reaches
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249 // that threshold. The line_box is used for computing the
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250 // box_word in the output words. worst_dict_cert is the worst certainty that
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parents:
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251 // will be used in a dictionary word.
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252 void RecognizeLine(const ImageData &image_data, float invert_threshold, bool debug, double worst_dict_cert,
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253 const TBOX &line_box, PointerVector<WERD_RES> *words, int lstm_choice_mode = 0,
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254 int lstm_choice_amount = 5);
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255
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256 // Helper computes min and mean best results in the output.
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257 void OutputStats(const NetworkIO &outputs, float *min_output, float *mean_output, float *sd);
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258 // Recognizes the image_data, returning the labels,
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259 // scores, and corresponding pairs of start, end x-coords in coords.
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260 // Returned in scale_factor is the reduction factor
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parents:
diff changeset
261 // between the image and the output coords, for computing bounding boxes.
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parents:
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262 // If re_invert is true, the input is inverted back to its original
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parents:
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263 // photometric interpretation if inversion is attempted but fails to
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parents:
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264 // improve the results. This ensures that outputs contains the correct
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parents:
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265 // forward outputs for the best photometric interpretation.
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parents:
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266 // inputs is filled with the used inputs to the network.
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Franz Glasner <fzglas.hg@dom66.de>
parents:
diff changeset
267 bool RecognizeLine(const ImageData &image_data, float invert_threshold, bool debug, bool re_invert,
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
268 bool upside_down, float *scale_factor, NetworkIO *inputs, NetworkIO *outputs);
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269
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270 // Converts an array of labels to utf-8, whether or not the labels are
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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271 // augmented with character boundaries.
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parents:
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272 std::string DecodeLabels(const std::vector<int> &labels);
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273
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parents:
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274 // Displays the forward results in a window with the characters and
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parents:
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275 // boundaries as determined by the labels and label_coords.
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parents:
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276 void DisplayForward(const NetworkIO &inputs, const std::vector<int> &labels,
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277 const std::vector<int> &label_coords, const char *window_name,
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parents:
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278 ScrollView **window);
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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279 // Converts the network output to a sequence of labels. Outputs labels, scores
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parents:
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280 // and start xcoords of each char, and each null_char_, with an additional
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parents:
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281 // final xcoord for the end of the output.
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parents:
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282 // The conversion method is determined by internal state.
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parents:
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283 void LabelsFromOutputs(const NetworkIO &outputs, std::vector<int> *labels,
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parents:
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284 std::vector<int> *xcoords);
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parents:
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285
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parents:
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286 protected:
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parents:
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287 // Sets the random seed from the sample_iteration_;
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parents:
diff changeset
288 void SetRandomSeed() {
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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289 int64_t seed = static_cast<int64_t>(sample_iteration_) * 0x10000001;
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parents:
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290 randomizer_.set_seed(seed);
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parents:
diff changeset
291 randomizer_.IntRand();
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parents:
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292 }
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parents:
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293
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parents:
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294 // Displays the labels and cuts at the corresponding xcoords.
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parents:
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295 // Size of labels should match xcoords.
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parents:
diff changeset
296 void DisplayLSTMOutput(const std::vector<int> &labels, const std::vector<int> &xcoords,
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
297 int height, ScrollView *window);
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parents:
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298
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parents:
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299 // Prints debug output detailing the activation path that is implied by the
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300 // xcoords.
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301 void DebugActivationPath(const NetworkIO &outputs, const std::vector<int> &labels,
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302 const std::vector<int> &xcoords);
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303
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304 // Prints debug output detailing activations and 2nd choice over a range
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305 // of positions.
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306 void DebugActivationRange(const NetworkIO &outputs, const char *label, int best_choice,
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307 int x_start, int x_end);
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308
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309 // As LabelsViaCTC except that this function constructs the best path that
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310 // contains only legal sequences of subcodes for recoder_.
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311 void LabelsViaReEncode(const NetworkIO &output, std::vector<int> *labels,
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312 std::vector<int> *xcoords);
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313 // Converts the network output to a sequence of labels, with scores, using
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314 // the simple character model (each position is a char, and the null_char_ is
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315 // mainly intended for tail padding.)
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316 void LabelsViaSimpleText(const NetworkIO &output, std::vector<int> *labels,
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317 std::vector<int> *xcoords);
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318
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319 // Returns a string corresponding to the label starting at start. Sets *end
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320 // to the next start and if non-null, *decoded to the unichar id.
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321 const char *DecodeLabel(const std::vector<int> &labels, unsigned start, unsigned *end, int *decoded);
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322
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323 // Returns a string corresponding to a given single label id, falling back to
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324 // a default of ".." for part of a multi-label unichar-id.
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325 const char *DecodeSingleLabel(int label);
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326
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327 protected:
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328 // The network hierarchy.
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329 Network *network_;
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330 // The unicharset. Only the unicharset element is serialized.
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331 // Has to be a CCUtil, so Dict can point to it.
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332 CCUtil ccutil_;
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333 // For backward compatibility, recoder_ is serialized iff
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334 // training_flags_ & TF_COMPRESS_UNICHARSET.
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335 // Further encode/decode ccutil_.unicharset's ids to simplify the unicharset.
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336 UnicharCompress recoder_;
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337
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338 // ==Training parameters that are serialized to provide a record of them.==
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339 std::string network_str_;
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340 // Flags used to determine the training method of the network.
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341 // See enum TrainingFlags above.
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342 int32_t training_flags_;
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343 // Number of actual backward training steps used.
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344 int32_t training_iteration_;
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345 // Index into training sample set. sample_iteration >= training_iteration_.
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346 int32_t sample_iteration_;
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347 // Index in softmax of null character. May take the value UNICHAR_BROKEN or
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348 // ccutil_.unicharset.size().
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349 int32_t null_char_;
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350 // Learning rate and momentum multipliers of deltas in backprop.
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351 float learning_rate_;
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352 float momentum_;
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353 // Smoothing factor for 2nd moment of gradients.
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354 float adam_beta_;
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355
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356 // === NOT SERIALIZED.
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357 TRand randomizer_;
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358 NetworkScratch scratch_space_;
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359 // Language model (optional) to use with the beam search.
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360 Dict *dict_;
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361 // Beam search held between uses to optimize memory allocation/use.
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362 RecodeBeamSearch *search_;
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363
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364 // == Debugging parameters.==
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365 // Recognition debug display window.
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366 ScrollView *debug_win_;
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367 };
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368
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369 } // namespace tesseract.
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370
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371 #endif // TESSERACT_LSTM_LSTMRECOGNIZER_H_