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Merged the trunk r8589:8653 - all changes related to build warnings

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This commit is contained in:
Andrey Kamaev
2012-06-15 13:04:17 +00:00
parent 73c152abc4
commit bd0e0b5800
438 changed files with 20374 additions and 19674 deletions
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22
modules/ml/src/nbayes.cpp
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@@ -241,13 +241,13 @@ bool CvNormalBayesClassifier::train( const CvMat* _train_data, const CvMat* _res
double* cov_data = cov->data.db + i*_var_count;
double s1val = sum1[i];
double avg1 = avg_data[i];
int count = count_data[i];
int _count = count_data[i];
for( j = 0; j <= i; j++ )
{
double avg2 = avg2_data[j];
double cov_val = prod_data[j] - avg1 * sum2[j] - avg2 * s1val + avg1 * avg2 * count;
cov_val = (count > 1) ? cov_val / (count - 1) : cov_val;
double cov_val = prod_data[j] - avg1 * sum2[j] - avg2 * s1val + avg1 * avg2 * _count;
cov_val = (_count > 1) ? cov_val / (_count - 1) : cov_val;
cov_data[j] = cov_val;
}
}
@@ -294,7 +294,7 @@ struct predict_body {
value = _value;
var_count1 = _var_count1;
}
CvMat* c;
CvMat** cov_rotate_mats;
CvMat** inv_eigen_values;
@@ -306,15 +306,15 @@ struct predict_body {
CvMat* results;
float* value;
int var_count1;
void operator()( const cv::BlockedRange& range ) const
{
int cls = -1;
int rtype = 0, rstep = 0;
int rtype = 0, rstep = 0;
int nclasses = cls_labels->cols;
int _var_count = avg[0]->cols;
if (results)
{
rtype = CV_MAT_TYPE(results->type);
@@ -323,7 +323,7 @@ struct predict_body {
// allocate memory and initializing headers for calculating
cv::AutoBuffer<double> buffer(nclasses + var_count1);
CvMat diff = cvMat( 1, var_count1, CV_64FC1, &buffer[0] );
for(int k = range.begin(); k < range.end(); k += 1 )
{
int ival;
@@ -592,7 +592,7 @@ CvNormalBayesClassifier::CvNormalBayesClassifier( const Mat& _train_data, const
cov_rotate_mats = 0;
c = 0;
default_model_name = "my_nb";
CvMat tdata = _train_data, responses = _responses, vidx = _var_idx, sidx = _sample_idx;
train(&tdata, &responses, vidx.data.ptr ? &vidx : 0,
sidx.data.ptr ? &sidx : 0);
@@ -609,7 +609,7 @@ bool CvNormalBayesClassifier::train( const Mat& _train_data, const Mat& _respons
float CvNormalBayesClassifier::predict( const Mat& _samples, Mat* _results ) const
{
CvMat samples = _samples, results, *presults = 0;
if( _results )
{
if( !(_results->data && _results->type() == CV_32F &&
@@ -618,7 +618,7 @@ float CvNormalBayesClassifier::predict( const Mat& _samples, Mat* _results ) con
_results->create(_samples.rows, 1, CV_32F);
presults = &(results = *_results);
}
return predict(&samples, presults);
}