Mercurial > hgrepos > Python2 > PyMuPDF

annotate mupdf-source/thirdparty/tesseract/src/ccmain/paragraphs_internal.h @ 21:2f43e400f144

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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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1 /**********************************************************************
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2 * File: paragraphs_internal.h
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3 * Description: Paragraph Detection internal data structures.
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4 * Author: David Eger
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5 *
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6 * (C) Copyright 2011, 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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19 #ifndef TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_
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20 #define TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_
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22 #include <tesseract/publictypes.h> // for ParagraphJustification
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23 #include "paragraphs.h"
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25 // NO CODE OUTSIDE OF paragraphs.cpp AND TESTS SHOULD NEED TO ACCESS
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26 // DATA STRUCTURES OR FUNCTIONS IN THIS FILE.
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28 namespace tesseract {
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30 class UNICHARSET;
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31 class WERD_CHOICE;
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33 // Return whether the given word is likely to be a list item start word.
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34 TESS_API
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35 bool AsciiLikelyListItem(const std::string &word);
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37 // Set right word attributes given either a unicharset and werd or a utf8
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38 // string.
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39 TESS_API
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40 void RightWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd, const std::string &utf8,
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41 bool *is_list, bool *starts_idea, bool *ends_idea);
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43 // Set left word attributes given either a unicharset and werd or a utf8 string.
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44 TESS_API
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45 void LeftWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd, const std::string &utf8,
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46 bool *is_list, bool *starts_idea, bool *ends_idea);
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48 enum LineType {
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49 LT_START = 'S', // First line of a paragraph.
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50 LT_BODY = 'C', // Continuation line of a paragraph.
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51 LT_UNKNOWN = 'U', // No clues.
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52 LT_MULTIPLE = 'M', // Matches for both LT_START and LT_BODY.
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53 };
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55 // The first paragraph in a page of body text is often un-indented.
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56 // This is a typographic convention which is common to indicate either that:
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57 // (1) The paragraph is the continuation of a previous paragraph, or
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58 // (2) The paragraph is the first paragraph in a chapter.
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59 //
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60 // I refer to such paragraphs as "crown"s, and the output of the paragraph
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61 // detection algorithm attempts to give them the same paragraph model as
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62 // the rest of the body text.
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63 //
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64 // Nonetheless, while building hypotheses, it is useful to mark the lines
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65 // of crown paragraphs temporarily as crowns, either aligned left or right.
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66 extern const ParagraphModel *kCrownLeft;
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67 extern const ParagraphModel *kCrownRight;
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68
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69 inline bool StrongModel(const ParagraphModel *model) {
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70 return model != nullptr && model != kCrownLeft && model != kCrownRight;
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71 }
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73 struct LineHypothesis {
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74 LineHypothesis() : ty(LT_UNKNOWN), model(nullptr) {}
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75 LineHypothesis(LineType line_type, const ParagraphModel *m) : ty(line_type), model(m) {}
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76 LineHypothesis(const LineHypothesis &other) = default;
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78 // Copy assignment operator.
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79 LineHypothesis &operator=(const LineHypothesis &other) = default;
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81 bool operator==(const LineHypothesis &other) const {
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82 return ty == other.ty && model == other.model;
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83 }
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85 LineType ty;
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86 const ParagraphModel *model;
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87 };
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89 class ParagraphTheory; // Forward Declaration
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91 using SetOfModels = std::vector<const ParagraphModel *>;
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93 // Row Scratch Registers are data generated by the paragraph detection
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94 // algorithm based on a RowInfo input.
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95 class RowScratchRegisters {
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96 public:
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97 // We presume row will outlive us.
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98 void Init(const RowInfo &row);
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99
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100 LineType GetLineType() const;
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101
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102 LineType GetLineType(const ParagraphModel *model) const;
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103
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104 // Mark this as a start line type, sans model. This is useful for the
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parents:
diff changeset
105 // initial marking of probable body lines or paragraph start lines.
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106 void SetStartLine();
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107
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108 // Mark this as a body line type, sans model. This is useful for the
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109 // initial marking of probably body lines or paragraph start lines.
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110 void SetBodyLine();
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111
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112 // Record that this row fits as a paragraph start line in the given model,
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113 void AddStartLine(const ParagraphModel *model);
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114 // Record that this row fits as a paragraph body line in the given model,
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115 void AddBodyLine(const ParagraphModel *model);
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116
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117 // Clear all hypotheses about this line.
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118 void SetUnknown() {
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119 hypotheses_.clear();
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120 }
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121
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122 // Append all hypotheses of strong models that match this row as a start.
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123 void StartHypotheses(SetOfModels *models) const;
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124
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125 // Append all hypotheses of strong models matching this row.
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126 void StrongHypotheses(SetOfModels *models) const;
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127
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128 // Append all hypotheses for this row.
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129 void NonNullHypotheses(SetOfModels *models) const;
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130
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131 // Discard any hypotheses whose model is not in the given list.
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132 void DiscardNonMatchingHypotheses(const SetOfModels &models);
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133
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134 // If we have only one hypothesis and that is that this line is a paragraph
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135 // start line of a certain model, return that model. Else return nullptr.
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136 const ParagraphModel *UniqueStartHypothesis() const;
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137
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138 // If we have only one hypothesis and that is that this line is a paragraph
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139 // body line of a certain model, return that model. Else return nullptr.
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140 const ParagraphModel *UniqueBodyHypothesis() const;
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141
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142 // Return the indentation for the side opposite of the aligned side.
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143 int OffsideIndent(tesseract::ParagraphJustification just) const {
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144 switch (just) {
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145 case tesseract::JUSTIFICATION_RIGHT:
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146 return lindent_;
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147 case tesseract::JUSTIFICATION_LEFT:
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148 return rindent_;
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149 default:
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150 return lindent_ > rindent_ ? lindent_ : rindent_;
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151 }
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152 }
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153
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154 // Return the indentation for the side the text is aligned to.
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parents:
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155 int AlignsideIndent(tesseract::ParagraphJustification just) const {
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156 switch (just) {
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157 case tesseract::JUSTIFICATION_RIGHT:
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158 return rindent_;
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parents:
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159 case tesseract::JUSTIFICATION_LEFT:
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160 return lindent_;
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parents:
diff changeset
161 default:
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162 return lindent_ > rindent_ ? lindent_ : rindent_;
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163 }
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parents:
diff changeset
164 }
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diff changeset
165
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166 // Append header fields to a vector of row headings.
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parents:
diff changeset
167 static void AppendDebugHeaderFields(std::vector<std::string> &header);
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168
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parents:
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169 // Append data for this row to a vector of debug strings.
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parents:
diff changeset
170 void AppendDebugInfo(const ParagraphTheory &theory, std::vector<std::string> &dbg) const;
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171
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diff changeset
172 const RowInfo *ri_;
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173
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parents:
diff changeset
174 // These four constants form a horizontal box model for the white space
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parents:
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175 // on the edges of each line. At each point in the algorithm, the following
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176 // shall hold:
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parents:
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177 // ri_->pix_ldistance = lmargin_ + lindent_
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178 // ri_->pix_rdistance = rindent_ + rmargin_
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parents:
diff changeset
179 int lmargin_;
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180 int lindent_;
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parents:
diff changeset
181 int rindent_;
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
182 int rmargin_;
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parents:
diff changeset
183
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parents:
diff changeset
184 private:
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parents:
diff changeset
185 // Hypotheses of either LT_START or LT_BODY
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parents:
diff changeset
186 std::vector<LineHypothesis> hypotheses_;
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parents:
diff changeset
187 };
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parents:
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188
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parents:
diff changeset
189 // A collection of convenience functions for wrapping the set of
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parents:
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190 // Paragraph Models we believe correctly model the paragraphs in the image.
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parents:
diff changeset
191 class ParagraphTheory {
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parents:
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192 public:
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193 // We presume models will outlive us, and that models will take ownership
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parents:
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194 // of any ParagraphModel *'s we add.
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195 explicit ParagraphTheory(std::vector<ParagraphModel *> *models) : models_(models) {}
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parents:
diff changeset
196 std::vector<ParagraphModel *> &models() {
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parents:
diff changeset
197 return *models_;
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198 }
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parents:
diff changeset
199 const std::vector<ParagraphModel *> &models() const {
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200 return *models_;
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201 }
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202
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203 // Return an existing model if one that is Comparable() can be found.
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204 // Else, allocate a new copy of model to save and return a pointer to it.
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205 const ParagraphModel *AddModel(const ParagraphModel &model);
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206
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207 // Discard any models we've made that are not in the list of used models.
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208 void DiscardUnusedModels(const SetOfModels &used_models);
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209
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210 // Return the set of all non-centered models.
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211 void NonCenteredModels(SetOfModels *models);
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212
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213 // If any of the non-centered paragraph models we know about fit
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214 // rows[start, end), return it. Else nullptr.
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215 const ParagraphModel *Fits(const std::vector<RowScratchRegisters> *rows, int start,
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216 int end) const;
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217
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218 int IndexOf(const ParagraphModel *model) const;
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219
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220 private:
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221 std::vector<ParagraphModel *> *models_;
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222 std::vector<ParagraphModel *> models_we_added_;
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223 };
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224
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225 bool ValidFirstLine(const std::vector<RowScratchRegisters> *rows, int row,
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226 const ParagraphModel *model);
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227 bool ValidBodyLine(const std::vector<RowScratchRegisters> *rows, int row,
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228 const ParagraphModel *model);
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229 bool CrownCompatible(const std::vector<RowScratchRegisters> *rows, int a, int b,
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230 const ParagraphModel *model);
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231
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232 // A class for smearing Paragraph Model hypotheses to surrounding rows.
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233 // The idea here is that StrongEvidenceClassify first marks only exceedingly
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234 // obvious start and body rows and constructs models of them. Thereafter,
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235 // we may have left over unmarked lines (mostly end-of-paragraph lines) which
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236 // were too short to have much confidence about, but which fit the models we've
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237 // constructed perfectly and which we ought to mark. This class is used to
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238 // "smear" our models over the text.
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239 class ParagraphModelSmearer {
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240 public:
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241 ParagraphModelSmearer(std::vector<RowScratchRegisters> *rows, int row_start, int row_end,
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242 ParagraphTheory *theory);
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243
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244 // Smear forward paragraph models from existing row markings to subsequent
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245 // text lines if they fit, and mark any thereafter still unmodeled rows
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246 // with any model in the theory that fits them.
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247 void Smear();
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248
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249 private:
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250 // Record in open_models_ for rows [start_row, end_row) the list of models
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251 // currently open at each row.
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252 // A model is still open in a row if some previous row has said model as a
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253 // start hypothesis, and all rows since (including this row) would fit as
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254 // either a body or start line in that model.
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255 void CalculateOpenModels(int row_start, int row_end);
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256
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257 SetOfModels &OpenModels(int row) {
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258 return open_models_[row - row_start_ + 1];
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259 }
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260
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261 ParagraphTheory *theory_;
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262 std::vector<RowScratchRegisters> *rows_;
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263 int row_start_;
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264 int row_end_;
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265
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266 // open_models_ corresponds to rows[start_row_ - 1, end_row_]
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267 //
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268 // open_models_: Contains models which there was an active (open) paragraph
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269 // as of the previous line and for which the left and right
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270 // indents admit the possibility that this text line continues
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271 // to fit the same model.
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272 // TODO(eger): Think about whether we can get rid of "Open" models and just
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273 // use the current hypotheses on RowScratchRegisters.
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274 std::vector<SetOfModels> open_models_;
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275 };
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276
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277 // Clear all hypotheses about lines [start, end) and reset the margins to the
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278 // percentile (0..100) value of the left and right row edges for this run of
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279 // rows.
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280 void RecomputeMarginsAndClearHypotheses(std::vector<RowScratchRegisters> *rows, int start,
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281 int end, int percentile);
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282
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283 // Return the median inter-word space in rows[row_start, row_end).
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284 int InterwordSpace(const std::vector<RowScratchRegisters> &rows, int row_start, int row_end);
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285
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286 // Return whether the first word on the after line can fit in the space at
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287 // the end of the before line (knowing which way the text is aligned and read).
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288 bool FirstWordWouldHaveFit(const RowScratchRegisters &before, const RowScratchRegisters &after,
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289 tesseract::ParagraphJustification justification);
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290
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291 // Return whether the first word on the after line can fit in the space at
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292 // the end of the before line (not knowing the text alignment).
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293 bool FirstWordWouldHaveFit(const RowScratchRegisters &before, const RowScratchRegisters &after);
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294
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295 // Do rows[start, end) form a single instance of the given paragraph model?
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296 bool RowsFitModel(const std::vector<RowScratchRegisters> *rows, int start, int end,
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297 const ParagraphModel *model);
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299 // Given a set of row_owners pointing to PARAs or nullptr (no paragraph known),
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300 // normalize each row_owner to point to an actual PARA, and output the
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301 // paragraphs in order onto paragraphs.
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302 void CanonicalizeDetectionResults(std::vector<PARA *> *row_owners, PARA_LIST *paragraphs);
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304 } // namespace tesseract
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306 #endif // TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_