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  • Committer: Package Import Robot
  • Author(s): Jeff Breidenbach
  • Date: 2014-02-03 11:10:20 UTC
  • mfrom: (1.3.1) (19.1.1 experimental)
  • Revision ID: package-import@ubuntu.com-20140203111020-igquodd7pjlp3uri
Tags: 3.03.01-1
* New upstream release, includes critical fix to PDF rendering
* Complete leptonlib transition (see bug #735509)
* Promote from experimental to unstable

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classify/intmatcher.cpp
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  // Copies the pruned, sorted classes into the output results and returns
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  // the number of classes.
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  int SetupResults(CP_RESULT_STRUCT* results) const {
 
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  int SetupResults(GenericVector<CP_RESULT_STRUCT>* results) const {
 
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    CP_RESULT_STRUCT empty;
 
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    results->init_to_size(num_classes_, empty);
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    for (int c = 0; c < num_classes_; ++c) {
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      results[c].Class = sort_index_[num_classes_ - c];
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      results[c].Rating = 1.0 - sort_key_[num_classes_ - c] /
 
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      (*results)[c].Class = sort_index_[num_classes_ - c];
 
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      (*results)[c].Rating = 1.0 - sort_key_[num_classes_ - c] /
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        (static_cast<float>(CLASS_PRUNER_CLASS_MASK) * num_features_);
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    }
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    return num_classes_;
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                           const INT_FEATURE_STRUCT* features,
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                           const uinT8* normalization_factors,
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                           const uinT16* expected_num_features,
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                           CP_RESULT_STRUCT* results) {
 
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                           GenericVector<CP_RESULT_STRUCT>* results) {
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/*
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 **  Operation:
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 **    Prunes the classes using a modified fast match table.
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/*---------------------------------------------------------------------------*/
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void IntegerMatcher::Init(tesseract::IntParam *classify_debug_level,
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                          int classify_integer_matcher_multiplier) {
 
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void IntegerMatcher::Init(tesseract::IntParam *classify_debug_level) {
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  classify_debug_level_ = classify_debug_level;
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  /* Set default mode of operation of IntegerMatcher */
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  SetCharNormMatch(classify_integer_matcher_multiplier);
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  /* Initialize table for evidence to similarity lookup */
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  for (int i = 0; i < SE_TABLE_SIZE; i++) {
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    uinT32 IntSimilarity = i << (27 - SE_TABLE_BITS);
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  evidence_mult_mask_ = ((1 << kIntEvidenceTruncBits) - 1);
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}
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/*--------------------------------------------------------------------------*/
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void IntegerMatcher::SetBaseLineMatch() {
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  local_matcher_multiplier_ = 0;
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}
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/*--------------------------------------------------------------------------*/
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void IntegerMatcher::SetCharNormMatch(int integer_matcher_multiplier) {
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  local_matcher_multiplier_ = integer_matcher_multiplier;
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}
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/**----------------------------------------------------------------------------
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              Private Code
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// Applies the CN normalization factor to the given rating and returns
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// the modified rating.
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float IntegerMatcher::ApplyCNCorrection(float rating, int blob_length,
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                                        int normalization_factor) {
 
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                                        int normalization_factor,
 
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                                        int matcher_multiplier) {
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  return (rating * blob_length +
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    local_matcher_multiplier_ * normalization_factor / 256.0) /
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    (blob_length + local_matcher_multiplier_);
 
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          matcher_multiplier * normalization_factor / 256.0) /
 
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      (blob_length + matcher_multiplier);
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}
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/*---------------------------------------------------------------------------*/