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More std::vector.
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@ -168,8 +168,8 @@ ErrorCounter::ErrorCounter(const UNICHARSET& unicharset, int fontsize)
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ok_score_hist_(0, 101), bad_score_hist_(0, 101),
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unicharset_(unicharset) {
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Counts empty_counts;
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font_counts_.init_to_size(fontsize, empty_counts);
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multi_unichar_counts_.init_to_size(unicharset.size(), 0);
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font_counts_.resize(fontsize, empty_counts);
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multi_unichar_counts_.resize(unicharset.size(), 0);
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}
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// Accumulates the errors from the classifier results on a single sample.
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@ -16,11 +16,10 @@
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#ifndef THIRD_PARTY_TESSERACT_CLASSIFY_ERRORCOUNTER_H_
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#define THIRD_PARTY_TESSERACT_CLASSIFY_ERRORCOUNTER_H_
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#include "genericvector.h"
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#include "matrix.h"
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#include "statistc.h"
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#include "genericvector.h"
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struct Pix;
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namespace tesseract {
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@ -209,13 +208,13 @@ class ErrorCounter {
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// Difference in result rating to be thought of as an "equal" choice.
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double rating_epsilon_;
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// Vector indexed by font_id from the samples of error accumulators.
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GenericVector<Counts> font_counts_;
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std::vector<Counts> font_counts_;
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// Counts of the results that map each unichar_id (from samples) to an
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// incorrect shape_id.
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GENERIC_2D_ARRAY<int> unichar_counts_;
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// Count of the number of times each shape_id occurs, is correct, and multi-
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// unichar.
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GenericVector<int> multi_unichar_counts_;
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std::vector<int> multi_unichar_counts_;
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// Histogram of scores (as percent) for correct answers.
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STATS ok_score_hist_;
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// Histogram of scores (as percent) for incorrect answers.
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@ -367,7 +367,7 @@ bool MasterTrainer::LoadFontInfo(const char* filename) {
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// Returns false on failure.
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bool MasterTrainer::LoadXHeights(const char* filename) {
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tprintf("fontinfo table is of size %d\n", fontinfo_table_.size());
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xheights_.init_to_size(fontinfo_table_.size(), -1);
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xheights_.resize(fontinfo_table_.size(), -1);
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if (filename == nullptr) return true;
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FILE *f = fopen(filename, "rb");
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if (f == nullptr) {
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