Commit 26d348a5 authored by Vladimir Dudnik's avatar Vladimir Dudnik

fixed build issue (MSVC2010, x64)

parent a811a08d
...@@ -519,9 +519,9 @@ int build_knearest_classifier( char* data_filename, int K ) ...@@ -519,9 +519,9 @@ int build_knearest_classifier( char* data_filename, int K )
CvKNearest knearest(&train_data, train_resp); CvKNearest knearest(&train_data, train_resp);
CvMat* nearests = cvCreateMat( (nsamples_all - ntrain_samples), K, CV_32FC1); CvMat* nearests = cvCreateMat( (nsamples_all - ntrain_samples), K, CV_32FC1);
float _sample[var_count * (nsamples_all - ntrain_samples)]; float* _sample = new float[var_count * (nsamples_all - ntrain_samples)];
CvMat sample = cvMat( nsamples_all - ntrain_samples, 16, CV_32FC1, _sample ); CvMat sample = cvMat( nsamples_all - ntrain_samples, 16, CV_32FC1, _sample );
float true_results[nsamples_all - ntrain_samples]; float* true_results = new float[nsamples_all - ntrain_samples];
for (int j = ntrain_samples; j < nsamples_all; j++) for (int j = ntrain_samples; j < nsamples_all; j++)
{ {
float *s = data->data.fl + j * var_count; float *s = data->data.fl + j * var_count;
...@@ -550,6 +550,8 @@ int build_knearest_classifier( char* data_filename, int K ) ...@@ -550,6 +550,8 @@ int build_knearest_classifier( char* data_filename, int K )
printf("true_resp = %f%%\tavg accuracy = %f%%\n", (float)true_resp / (nsamples_all - ntrain_samples) * 100, printf("true_resp = %f%%\tavg accuracy = %f%%\n", (float)true_resp / (nsamples_all - ntrain_samples) * 100,
(float)accuracy / (nsamples_all - ntrain_samples) / K * 100); (float)accuracy / (nsamples_all - ntrain_samples) / K * 100);
delete[] true_results;
delete[] _sample;
cvReleaseMat( &train_resp ); cvReleaseMat( &train_resp );
cvReleaseMat( &nearests ); cvReleaseMat( &nearests );
cvReleaseMat( &result ); cvReleaseMat( &result );
...@@ -593,9 +595,9 @@ int build_nbayes_classifier( char* data_filename ) ...@@ -593,9 +595,9 @@ int build_nbayes_classifier( char* data_filename )
train_resp->data.fl[i] = responses->data.fl[i]; train_resp->data.fl[i] = responses->data.fl[i];
CvNormalBayesClassifier nbayes(&train_data, train_resp); CvNormalBayesClassifier nbayes(&train_data, train_resp);
float _sample[var_count * (nsamples_all - ntrain_samples)]; float* _sample = new float[var_count * (nsamples_all - ntrain_samples)];
CvMat sample = cvMat( nsamples_all - ntrain_samples, 16, CV_32FC1, _sample ); CvMat sample = cvMat( nsamples_all - ntrain_samples, 16, CV_32FC1, _sample );
float true_results[nsamples_all - ntrain_samples]; float* true_results = new float[nsamples_all - ntrain_samples];
for (int j = ntrain_samples; j < nsamples_all; j++) for (int j = ntrain_samples; j < nsamples_all; j++)
{ {
float *s = data->data.fl + j * var_count; float *s = data->data.fl + j * var_count;
...@@ -618,6 +620,8 @@ int build_nbayes_classifier( char* data_filename ) ...@@ -618,6 +620,8 @@ int build_nbayes_classifier( char* data_filename )
printf("true_resp = %f%%\n", (float)true_resp / (nsamples_all - ntrain_samples) * 100); printf("true_resp = %f%%\n", (float)true_resp / (nsamples_all - ntrain_samples) * 100);
delete[] true_results;
delete[] _sample;
cvReleaseMat( &train_resp ); cvReleaseMat( &train_resp );
cvReleaseMat( &result ); cvReleaseMat( &result );
cvReleaseMat( &data ); cvReleaseMat( &data );
......
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