mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-11-24 19:19:05 +08:00
Replace malloc / free by new / delete for FEATURE_STRUCT, FEATURE_SET_STRUCT
Signed-off-by: Stefan Weil <sw@weilnetz.de>
This commit is contained in:
parent
aa8dda89a3
commit
b15b5d1de7
@ -39,7 +39,7 @@
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#include "mfoutline.h" // for baseline, character, MF_SCALE_FACTOR
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#include "normalis.h" // for DENORM, kBlnBaselineOffset, kBlnXHeight
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#include "normfeat.h" // for ActualOutlineLength, CharNormLength
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#include "ocrfeatures.h" // for FEATURE_STRUCT, FreeFeatureSet, FEATURE
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#include "ocrfeatures.h" // for FEATURE_STRUCT, FEATURE
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#include "oldlist.h" // for push, delete_d
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#include "outfeat.h" // for OutlineFeatDir, OutlineFeatLength
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#include "pageres.h" // for WERD_RES
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@ -68,7 +68,6 @@
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#include <cmath> // for fabs
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#include <cstdint> // for INT32_MAX, UINT8_MAX
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#include <cstdio> // for fflush, fclose, fopen, stdout, FILE
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#include <cstdlib> // for malloc
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#include <cstring> // for strstr, memset, strcmp
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namespace tesseract {
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@ -693,7 +692,7 @@ void Classify::InitAdaptedClass(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, A
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Features = ExtractOutlineFeatures(Blob);
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NumFeatures = Features->NumFeatures;
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if (NumFeatures > UNLIKELY_NUM_FEAT || NumFeatures <= 0) {
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FreeFeatureSet(Features);
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delete Features;
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return;
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}
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@ -732,7 +731,7 @@ void Classify::InitAdaptedClass(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, A
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Class->TempProtos = push(Class->TempProtos, TempProto);
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}
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FreeFeatureSet(Features);
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delete Features;
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AddIntConfig(IClass);
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ConvertConfig(AllProtosOn, 0, IClass);
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@ -781,7 +780,7 @@ int Classify::GetAdaptiveFeatures(TBLOB *Blob, INT_FEATURE_ARRAY IntFeatures,
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NumFeatures = Features->NumFeatures;
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if (NumFeatures == 0 || NumFeatures > UNLIKELY_NUM_FEAT) {
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FreeFeatureSet(Features);
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delete Features;
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return 0;
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}
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@ -885,7 +884,7 @@ void Classify::AdaptToChar(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, float
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tprintf("Found good match to perm config %d = %4.1f%%.\n", int_result.config,
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int_result.rating * 100.0);
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}
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FreeFeatureSet(FloatFeatures);
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delete FloatFeatures;
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return;
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}
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@ -927,7 +926,7 @@ void Classify::AdaptToChar(TBLOB *Blob, CLASS_ID ClassId, int FontinfoId, float
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}
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#endif
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}
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FreeFeatureSet(FloatFeatures);
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delete FloatFeatures;
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}
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} /* AdaptToChar */
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@ -1611,7 +1610,7 @@ bool Classify::LooksLikeGarbage(TBLOB *blob) {
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*/
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int Classify::GetCharNormFeature(const INT_FX_RESULT_STRUCT &fx_info, INT_TEMPLATES_STRUCT *templates,
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uint8_t *pruner_norm_array, uint8_t *char_norm_array) {
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FEATURE norm_feature = NewFeature(&CharNormDesc);
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auto norm_feature = new FEATURE_STRUCT(&CharNormDesc);
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float baseline = kBlnBaselineOffset;
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float scale = MF_SCALE_FACTOR;
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norm_feature->Params[CharNormY] = (fx_info.Ymean - baseline) * scale;
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@ -1649,7 +1648,7 @@ void Classify::ComputeCharNormArrays(FEATURE_STRUCT *norm_feature, INT_TEMPLATES
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}
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}
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}
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FreeFeature(norm_feature);
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delete norm_feature;
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}
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/*---------------------------------------------------------------------------*/
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@ -57,7 +57,7 @@ struct CHAR_DESC_STRUCT {
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/// description and all of the features in that description.
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~CHAR_DESC_STRUCT() {
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for (size_t i = 0; i < NumFeatureSets; i++) {
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FreeFeatureSet(FeatureSets[i]);
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delete FeatureSets[i];
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}
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}
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@ -2,7 +2,6 @@
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** Filename: mf.c
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** Purpose: Micro-feature interface to flexible feature extractor.
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** Author: Dan Johnson
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** History: Thu May 24 09:08:38 1990, DSJ, Created.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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** Licensed under the Apache License, Version 2.0 (the "License");
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@ -42,8 +41,6 @@ namespace tesseract {
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FEATURE_SET ExtractMicros(TBLOB *Blob, const DENORM &cn_denorm) {
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int NumFeatures;
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MICROFEATURES Features, OldFeatures;
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FEATURE_SET FeatureSet;
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FEATURE Feature;
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MICROFEATURE OldFeature;
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OldFeatures = BlobMicroFeatures(Blob, cn_denorm);
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@ -51,12 +48,12 @@ FEATURE_SET ExtractMicros(TBLOB *Blob, const DENORM &cn_denorm) {
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return nullptr;
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}
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NumFeatures = count(OldFeatures);
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FeatureSet = NewFeatureSet(NumFeatures);
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auto FeatureSet = new FEATURE_SET_STRUCT(NumFeatures);
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Features = OldFeatures;
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iterate(Features) {
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OldFeature = reinterpret_cast<MICROFEATURE> first_node(Features);
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Feature = NewFeature(&MicroFeatureDesc);
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auto Feature = new FEATURE_STRUCT(&MicroFeatureDesc);
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Feature->Params[MFDirection] = OldFeature[ORIENTATION];
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Feature->Params[MFXPosition] = OldFeature[XPOSITION];
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Feature->Params[MFYPosition] = OldFeature[YPOSITION];
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@ -2,7 +2,6 @@
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** Filename: normfeat.c
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** Purpose: Definition of char normalization features.
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** Author: Dan Johnson
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** History: 12/14/90, DSJ, Created.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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** Licensed under the Apache License, Version 2.0 (the "License");
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@ -55,8 +54,8 @@ float ActualOutlineLength(FEATURE Feature) {
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* - English: [0.011, 0.31]
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*/
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FEATURE_SET ExtractCharNormFeatures(const INT_FX_RESULT_STRUCT &fx_info) {
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FEATURE_SET feature_set = NewFeatureSet(1);
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FEATURE feature = NewFeature(&CharNormDesc);
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auto feature_set = new FEATURE_SET_STRUCT(1);
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auto feature = new FEATURE_STRUCT(&CharNormDesc);
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feature->Params[CharNormY] = MF_SCALE_FACTOR * (fx_info.Ymean - kBlnBaselineOffset);
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feature->Params[CharNormLength] = MF_SCALE_FACTOR * fx_info.Length / LENGTH_COMPRESSION;
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@ -38,7 +38,7 @@ namespace tesseract {
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*/
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bool AddFeature(FEATURE_SET FeatureSet, FEATURE Feature) {
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if (FeatureSet->NumFeatures >= FeatureSet->MaxNumFeatures) {
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FreeFeature(Feature);
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delete Feature;
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return false;
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}
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@ -46,64 +46,6 @@ bool AddFeature(FEATURE_SET FeatureSet, FEATURE Feature) {
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return true;
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} /* AddFeature */
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/**
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* Release the memory consumed by the specified feature.
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* @param Feature feature to be deallocated.
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*/
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void FreeFeature(FEATURE Feature) {
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free(Feature);
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} /* FreeFeature */
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/**
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* Release the memory consumed by the specified feature
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* set. This routine also frees the memory consumed by the
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* features contained in the set.
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* @param FeatureSet set of features to be freed
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*/
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void FreeFeatureSet(FEATURE_SET FeatureSet) {
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int i;
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if (FeatureSet) {
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for (i = 0; i < FeatureSet->NumFeatures; i++) {
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FreeFeature(FeatureSet->Features[i]);
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}
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free(FeatureSet);
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}
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} /* FreeFeatureSet */
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/**
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* Allocate and return a new feature of the specified
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* type.
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* @param FeatureDesc description of feature to be created.
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* @return New #FEATURE.
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*/
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FEATURE NewFeature(const FEATURE_DESC_STRUCT *FeatureDesc) {
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FEATURE Feature;
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Feature = static_cast<FEATURE>(
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malloc(sizeof(FEATURE_STRUCT) + (FeatureDesc->NumParams - 1) * sizeof(float)));
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Feature->Type = FeatureDesc;
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return (Feature);
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} /* NewFeature */
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/**
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* Allocate and return a new feature set large enough to
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* hold the specified number of features.
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* @param NumFeatures maximum # of features to be put in feature set
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* @return New #FEATURE_SET.
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*/
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FEATURE_SET NewFeatureSet(int NumFeatures) {
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FEATURE_SET FeatureSet;
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FeatureSet = static_cast<FEATURE_SET>(
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malloc(sizeof(FEATURE_SET_STRUCT) + (NumFeatures - 1) * sizeof(FEATURE)));
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FeatureSet->MaxNumFeatures = NumFeatures;
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FeatureSet->NumFeatures = 0;
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return (FeatureSet);
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} /* NewFeatureSet */
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/**
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* Create a new feature of the specified type and read in
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* the value of its parameters from File. The extra penalty
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@ -116,11 +58,8 @@ FEATURE_SET NewFeatureSet(int NumFeatures) {
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* @return New #FEATURE read from File.
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*/
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static FEATURE ReadFeature(FILE *File, const FEATURE_DESC_STRUCT *FeatureDesc) {
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FEATURE Feature;
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int i;
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Feature = NewFeature(FeatureDesc);
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for (i = 0; i < Feature->Type->NumParams; i++) {
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auto Feature = new FEATURE_STRUCT(FeatureDesc);
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for (int i = 0; i < Feature->Type->NumParams; i++) {
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ASSERT_HOST(tfscanf(File, "%f", &(Feature->Params[i])) == 1);
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#ifndef _WIN32
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assert(!std::isnan(Feature->Params[i]));
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@ -144,7 +83,7 @@ FEATURE_SET ReadFeatureSet(FILE *File, const FEATURE_DESC_STRUCT *FeatureDesc) {
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ASSERT_HOST(tfscanf(File, "%d", &NumFeatures) == 1);
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ASSERT_HOST(NumFeatures >= 0);
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FEATURE_SET FeatureSet = NewFeatureSet(NumFeatures);
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auto FeatureSet = new FEATURE_SET_STRUCT(NumFeatures);
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for (int i = 0; i < NumFeatures; i++) {
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AddFeature(FeatureSet, ReadFeature(File, FeatureDesc));
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}
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@ -56,15 +56,33 @@ struct FEATURE_DESC_STRUCT {
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using FEATURE_DESC = FEATURE_DESC_STRUCT *;
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struct FEATURE_STRUCT {
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/// Constructor for a new feature of the specified type.
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/// @param FeatureDesc description of feature to be created.
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FEATURE_STRUCT(const FEATURE_DESC_STRUCT *FeatureDesc) : Type(FeatureDesc), Params(FeatureDesc->NumParams) {
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}
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~FEATURE_STRUCT() {
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}
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const FEATURE_DESC_STRUCT *Type; // points to description of feature type
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float Params[1]; // variable size array - params for feature
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std::vector<float> Params; // variable size array - params for feature
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};
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using FEATURE = FEATURE_STRUCT *;
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struct FEATURE_SET_STRUCT {
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/// Creator for a new feature set large enough to
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/// hold the specified number of features.
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/// @param NumFeatures maximum # of features to be put in feature set
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FEATURE_SET_STRUCT(int numFeatures) : NumFeatures(0), MaxNumFeatures(numFeatures), Features(numFeatures) {
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}
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~FEATURE_SET_STRUCT() {
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for (uint16_t i = 0; i < NumFeatures; i++) {
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delete Features[i];
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}
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}
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uint16_t NumFeatures; // number of features in set
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uint16_t MaxNumFeatures; // maximum size of feature set
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FEATURE Features[1]; // variable size array of features
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std::vector<FEATURE_STRUCT *> Features; // variable size array of features
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};
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using FEATURE_SET = FEATURE_SET_STRUCT *;
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@ -105,17 +123,6 @@ DefineFeature (Name, NumLinear, NumCircular, ShortName, ParamName)
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----------------------------------------------------------------------*/
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bool AddFeature(FEATURE_SET FeatureSet, FEATURE Feature);
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TESS_API
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void FreeFeature(FEATURE Feature);
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TESS_API
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void FreeFeatureSet(FEATURE_SET FeatureSet);
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TESS_API
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FEATURE NewFeature(const FEATURE_DESC_STRUCT *FeatureDesc);
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FEATURE_SET NewFeatureSet(int NumFeatures);
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FEATURE_SET ReadFeatureSet(FILE *File, const FEATURE_DESC_STRUCT *FeatureDesc);
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void WriteFeatureSet(FEATURE_SET FeatureSet, std::string &str);
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@ -41,10 +41,9 @@ FEATURE_SET Classify::ExtractOutlineFeatures(TBLOB *Blob) {
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LIST Outlines;
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LIST RemainingOutlines;
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MFOUTLINE Outline;
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FEATURE_SET FeatureSet;
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float XScale, YScale;
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FeatureSet = NewFeatureSet(MAX_OUTLINE_FEATURES);
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auto FeatureSet = new FEATURE_SET_STRUCT(MAX_OUTLINE_FEATURES);
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if (Blob == nullptr) {
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return (FeatureSet);
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}
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@ -81,9 +80,7 @@ FEATURE_SET Classify::ExtractOutlineFeatures(TBLOB *Blob) {
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* @param FeatureSet set to add outline-feature to
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*/
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void AddOutlineFeatureToSet(FPOINT *Start, FPOINT *End, FEATURE_SET FeatureSet) {
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FEATURE Feature;
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Feature = NewFeature(&OutlineFeatDesc);
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auto Feature = new FEATURE_STRUCT(&OutlineFeatDesc);
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Feature->Params[OutlineFeatDir] = NormalizedAngleFrom(Start, End, 1.0);
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Feature->Params[OutlineFeatX] = AverageOf(Start->x, End->x);
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Feature->Params[OutlineFeatY] = AverageOf(Start->y, End->y);
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@ -61,10 +61,9 @@ FEATURE_SET Classify::ExtractPicoFeatures(TBLOB *Blob) {
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LIST Outlines;
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LIST RemainingOutlines;
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MFOUTLINE Outline;
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FEATURE_SET FeatureSet;
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float XScale, YScale;
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FeatureSet = NewFeatureSet(MAX_PICO_FEATURES);
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auto FeatureSet = new FEATURE_SET_STRUCT(MAX_PICO_FEATURES);
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Outlines = ConvertBlob(Blob);
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NormalizeOutlines(Outlines, &XScale, &YScale);
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RemainingOutlines = Outlines;
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@ -98,7 +97,6 @@ FEATURE_SET Classify::ExtractPicoFeatures(TBLOB *Blob) {
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* @param FeatureSet set to add pico-feature to
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*/
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void ConvertSegmentToPicoFeat(FPOINT *Start, FPOINT *End, FEATURE_SET FeatureSet) {
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FEATURE Feature;
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float Angle;
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float Length;
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int NumFeatures;
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@ -123,7 +121,7 @@ void ConvertSegmentToPicoFeat(FPOINT *Start, FPOINT *End, FEATURE_SET FeatureSet
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/* compute each pico feature in segment and add to feature set */
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for (i = 0; i < NumFeatures; i++) {
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Feature = NewFeature(&PicoFeatDesc);
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auto Feature = new FEATURE_STRUCT(&PicoFeatDesc);
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Feature->Params[PicoFeatDir] = Angle;
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Feature->Params[PicoFeatX] = Center.x;
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Feature->Params[PicoFeatY] = Center.y;
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@ -218,10 +216,9 @@ FEATURE_SET Classify::ExtractIntCNFeatures(const TBLOB &blob, const INT_FX_RESUL
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uint32_t num_features = sample->num_features();
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const INT_FEATURE_STRUCT *features = sample->features();
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FEATURE_SET feature_set = NewFeatureSet(num_features);
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auto feature_set = new FEATURE_SET_STRUCT(num_features);
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for (uint32_t f = 0; f < num_features; ++f) {
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FEATURE feature = NewFeature(&IntFeatDesc);
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auto feature = new FEATURE_STRUCT(&IntFeatDesc);
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feature->Params[IntX] = features[f].X;
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feature->Params[IntY] = features[f].Y;
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feature->Params[IntDir] = features[f].Theta;
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@ -248,8 +245,8 @@ FEATURE_SET Classify::ExtractIntGeoFeatures(const TBLOB &blob,
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return nullptr;
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}
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FEATURE_SET feature_set = NewFeatureSet(1);
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FEATURE feature = NewFeature(&IntFeatDesc);
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auto feature_set = new FEATURE_SET_STRUCT(1);
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auto feature = new FEATURE_STRUCT(&IntFeatDesc);
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feature->Params[GeoBottom] = sample->geo_feature(GeoBottom);
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feature->Params[GeoTop] = sample->geo_feature(GeoTop);
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@ -183,7 +183,7 @@ TrainingSample *TrainingSample::CopyFromFeatures(const INT_FX_RESULT_STRUCT &fx_
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// Returns the cn_feature as a FEATURE_STRUCT* needed by cntraining.
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FEATURE_STRUCT *TrainingSample::GetCNFeature() const {
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FEATURE feature = NewFeature(&CharNormDesc);
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auto feature = new FEATURE_STRUCT(&CharNormDesc);
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for (int i = 0; i < kNumCNParams; ++i) {
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feature->Params[i] = cn_feature_[i];
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}
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@ -413,11 +413,11 @@ void ReadTrainingSamples(const FEATURE_DEFS_STRUCT &feature_definitions, const c
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char_sample->SampleCount++;
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char_sample->font_sample_count++;
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} else {
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FreeFeatureSet(feature_samples);
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delete feature_samples;
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}
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for (size_t i = 0; i < char_desc->NumFeatureSets; i++) {
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if (feature_type != i) {
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FreeFeatureSet(char_desc->FeatureSets[i]);
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delete char_desc->FeatureSets[i];
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}
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}
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free(char_desc);
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@ -441,7 +441,7 @@ void FreeTrainingSamples(LIST CharList) {
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FeatureList = char_sample->List;
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iterate(FeatureList) { /* iterate through all of the classes */
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FeatureSet = reinterpret_cast<FEATURE_SET> first_node(FeatureList);
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FreeFeatureSet(FeatureSet);
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delete FeatureSet;
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}
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FreeLabeledList(char_sample);
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}
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@ -64,7 +64,6 @@ static double_VAR(training_angle_pad, 45.0, "Angle pad ...");
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* @return Worst possible result when matching p1 to p2.
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*/
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float CompareProtos(PROTO_STRUCT *p1, PROTO_STRUCT *p2) {
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FEATURE Feature;
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float WorstEvidence = WORST_EVIDENCE;
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float Evidence;
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float Angle, Length;
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@ -76,7 +75,7 @@ float CompareProtos(PROTO_STRUCT *p1, PROTO_STRUCT *p2) {
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}
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/* create a dummy pico-feature to be used for comparisons */
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Feature = NewFeature(&PicoFeatDesc);
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auto Feature = new FEATURE_STRUCT(&PicoFeatDesc);
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Feature->Params[PicoFeatDir] = p1->Angle;
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/* convert angle to radians */
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@ -97,7 +96,7 @@ float CompareProtos(PROTO_STRUCT *p1, PROTO_STRUCT *p2) {
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WorstEvidence = Evidence;
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||||
}
|
||||
} else {
|
||||
FreeFeature(Feature);
|
||||
delete Feature;
|
||||
return 0.0;
|
||||
}
|
||||
|
||||
@ -110,11 +109,11 @@ float CompareProtos(PROTO_STRUCT *p1, PROTO_STRUCT *p2) {
|
||||
WorstEvidence = Evidence;
|
||||
}
|
||||
} else {
|
||||
FreeFeature(Feature);
|
||||
delete Feature;
|
||||
return 0.0;
|
||||
}
|
||||
|
||||
FreeFeature(Feature);
|
||||
delete Feature;
|
||||
return (WorstEvidence);
|
||||
|
||||
} /* CompareProtos */
|
||||
|
Loading…
Reference in New Issue
Block a user