Mercurial > hgrepos > Python2 > PyMuPDF

annotate mupdf-source/thirdparty/tesseract/src/training/common/ctc.h @ 17:dd9cdb856310

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Remove PKG-INFO from the because it is regenerated automatically for the sdist
author Franz Glasner <fzglas.hg@dom66.de>
date Thu, 18 Sep 2025 17:40:40 +0200
parents b50eed0cc0ef
children
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1 ///////////////////////////////////////////////////////////////////////
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2 // File: ctc.h
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3 // Description: Slightly improved standard CTC to compute the targets.
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4 // Author: Ray Smith
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5 // Created: Wed Jul 13 15:17:06 PDT 2016
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6 //
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7 // (C) Copyright 2016, Google Inc.
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8 // Licensed under the Apache License, Version 2.0 (the "License");
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9 // you may not use this file except in compliance with the License.
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10 // You may obtain a copy of the License at
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11 // http://www.apache.org/licenses/LICENSE-2.0
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12 // Unless required by applicable law or agreed to in writing, software
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13 // distributed under the License is distributed on an "AS IS" BASIS,
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14 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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15 // See the License for the specific language governing permissions and
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16 // limitations under the License.
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17 ///////////////////////////////////////////////////////////////////////
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19 #ifndef TESSERACT_LSTM_CTC_H_
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20 #define TESSERACT_LSTM_CTC_H_
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22 #include "export.h"
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23 #include "network.h"
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24 #include "networkio.h"
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25 #include "scrollview.h"
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27 namespace tesseract {
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29 // Class to encapsulate CTC and simple target generation.
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30 class TESS_COMMON_TRAINING_API CTC {
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31 public:
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32 // Normalizes the probabilities such that no target has a prob below min_prob,
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33 // and, provided that the initial total is at least min_total_prob, then all
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34 // probs will sum to 1, otherwise to sum/min_total_prob. The maximum output
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35 // probability is thus 1 - (num_classes-1)*min_prob.
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36 static void NormalizeProbs(NetworkIO *probs) {
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37 NormalizeProbs(probs->mutable_float_array());
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38 }
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40 // Builds a target using CTC. Slightly improved as follows:
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41 // Includes normalizations and clipping for stability.
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42 // labels should be pre-padded with nulls wherever desired, but they don't
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43 // have to be between all labels. Allows for multi-label codes with no
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44 // nulls between.
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45 // labels can be longer than the time sequence, but the total number of
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46 // essential labels (non-null plus nulls between equal labels) must not exceed
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47 // the number of timesteps in outputs.
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48 // outputs is the output of the network, and should have already been
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49 // normalized with NormalizeProbs.
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50 // On return targets is filled with the computed targets.
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51 // Returns false if there is insufficient time for the labels.
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52 static bool ComputeCTCTargets(const std::vector<int> &truth_labels, int null_char,
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53 const GENERIC_2D_ARRAY<float> &outputs, NetworkIO *targets);
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54
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55 private:
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56 // Constructor is private as the instance only holds information specific to
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57 // the current labels, outputs etc, and is built by the static function.
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58 CTC(const std::vector<int> &labels, int null_char, const GENERIC_2D_ARRAY<float> &outputs);
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59
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60 // Computes vectors of min and max label index for each timestep, based on
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61 // whether skippability of nulls makes it possible to complete a valid path.
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62 bool ComputeLabelLimits();
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63 // Computes targets based purely on the labels by spreading the labels evenly
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64 // over the available timesteps.
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65 void ComputeSimpleTargets(GENERIC_2D_ARRAY<float> *targets) const;
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66 // Computes mean positions and half widths of the simple targets by spreading
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67 // the labels even over the available timesteps.
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68 void ComputeWidthsAndMeans(std::vector<float> *half_widths, std::vector<int> *means) const;
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69 // Calculates and returns a suitable fraction of the simple targets to add
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70 // to the network outputs.
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71 float CalculateBiasFraction();
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72 // Runs the forward CTC pass, filling in log_probs.
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73 void Forward(GENERIC_2D_ARRAY<double> *log_probs) const;
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74 // Runs the backward CTC pass, filling in log_probs.
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75 void Backward(GENERIC_2D_ARRAY<double> *log_probs) const;
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76 // Normalizes and brings probs out of log space with a softmax over time.
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77 void NormalizeSequence(GENERIC_2D_ARRAY<double> *probs) const;
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78 // For each timestep computes the max prob for each class over all
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79 // instances of the class in the labels_, and sets the targets to
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80 // the max observed prob.
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81 void LabelsToClasses(const GENERIC_2D_ARRAY<double> &probs, NetworkIO *targets) const;
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82 // Normalizes the probabilities such that no target has a prob below min_prob,
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83 // and, provided that the initial total is at least min_total_prob, then all
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84 // probs will sum to 1, otherwise to sum/min_total_prob. The maximum output
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85 // probability is thus 1 - (num_classes-1)*min_prob.
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86 static void NormalizeProbs(GENERIC_2D_ARRAY<float> *probs);
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87 // Returns true if the label at index is a needed null.
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88 bool NeededNull(int index) const;
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89 // Returns exp(clipped(x)), clipping x to a reasonable range to prevent over/
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90 // underflow.
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91 static double ClippedExp(double x) {
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92 if (x < -kMaxExpArg_) {
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93 return exp(-kMaxExpArg_);
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94 }
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95 if (x > kMaxExpArg_) {
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96 return exp(kMaxExpArg_);
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97 }
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98 return exp(x);
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99 }
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100
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101 // Minimum probability limit for softmax input to ctc_loss.
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102 static const float kMinProb_;
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103 // Maximum absolute argument to exp().
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104 static const double kMaxExpArg_;
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105 // Minimum probability for total prob in time normalization.
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106 static const double kMinTotalTimeProb_;
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107 // Minimum probability for total prob in final normalization.
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108 static const double kMinTotalFinalProb_;
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109
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110 // The truth label indices that are to be matched to outputs_.
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111 const std::vector<int> &labels_;
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112 // The network outputs.
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113 GENERIC_2D_ARRAY<float> outputs_;
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114 // The null or "blank" label.
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115 int null_char_;
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116 // Number of timesteps in outputs_.
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117 int num_timesteps_;
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118 // Number of classes in outputs_.
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119 int num_classes_;
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120 // Number of labels in labels_.
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121 int num_labels_;
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122 // Min and max valid label indices for each timestep.
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123 std::vector<int> min_labels_;
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124 std::vector<int> max_labels_;
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125 };
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126
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127 } // namespace tesseract
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128
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129 #endif // TESSERACT_LSTM_CTC_H_