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text: fix memleak in ocr_hmm_decoder

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changed double *p to vector<double>
This commit is contained in:
berak
2016-10-08 10:07:20 +02:00
parent 12cd33c962
commit c3c9723fbd
1 changed files with 3 additions and 7 deletions
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10
modules/text/src/ocr_hmm_decoder.cpp
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@@ -935,7 +935,7 @@ public:
protected: protected:
void normalizeAndZCA(Mat& patches); void normalizeAndZCA(Mat& patches);
double eval_feature(Mat& feature, double* prob_estimates); double eval_feature(Mat& feature, vector<double>& prob_estimates);
private: private:
int nr_class; // number of classes int nr_class; // number of classes
@@ -1089,7 +1089,7 @@ void OCRHMMClassifierCNN::eval( InputArray _src, vector<int>& out_class, vector<
(feature_max.at<double>(0,k)-feature_min.at<double>(0,k)); (feature_max.at<double>(0,k)-feature_min.at<double>(0,k));
} }
double *p = new double[nr_class]; vector<double> p(nr_class, 0);
double predict_label = eval_feature(feature,p); double predict_label = eval_feature(feature,p);
//cout << " Prediction: " << vocabulary[predict_label] << " with probability " << p[0] << endl; //cout << " Prediction: " << vocabulary[predict_label] << " with probability " << p[0] << endl;
if (predict_label < 0) if (predict_label < 0)
@@ -1107,7 +1107,6 @@ void OCRHMMClassifierCNN::eval( InputArray _src, vector<int>& out_class, vector<
} }
} }
} }
// normalize for contrast and apply ZCA whitening to a set of image patches // normalize for contrast and apply ZCA whitening to a set of image patches
@@ -1157,11 +1156,8 @@ void OCRHMMClassifierCNN::normalizeAndZCA(Mat& patches)
} }
double OCRHMMClassifierCNN::eval_feature(Mat& feature, double* prob_estimates) double OCRHMMClassifierCNN::eval_feature(Mat& feature, vector<double>& prob_estimates)
{ {
for(int i=0;i<nr_class;i++)
prob_estimates[i] = 0;
for(int idx=0; idx<nr_feature; idx++) for(int idx=0; idx<nr_feature; idx++)
for(int i=0;i<nr_class;i++) for(int i=0;i<nr_class;i++)
prob_estimates[i] += weights.at<float>(idx,i)*feature.at<double>(0,idx); //TODO use vectorized dot product prob_estimates[i] += weights.at<float>(idx,i)*feature.at<double>(0,idx); //TODO use vectorized dot product