generic-library/opencv
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Warning fixes continued

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This commit is contained in:
Andrey Kamaev
2012-06-09 15:00:04 +00:00
parent f6b451c607
commit f2d3b9b4a1
127 changed files with 6298 additions and 6277 deletions
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28
modules/ml/test/test_emknearestkmeans.cpp
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@@ -80,7 +80,7 @@ void generateData( Mat& data, Mat& labels, const vector<int>& sizes, const Mat&
CV_Assert( _means.rows == (int)sizes.size() && covs.size() == sizes.size() );
CV_Assert( !data.empty() && data.rows == total );
CV_Assert( data.type() == dataType );
labels.create( data.rows, 1, labelType );
randn( data, Scalar::all(-1.0), Scalar::all(1.0) );
@@ -99,7 +99,7 @@ void generateData( Mat& data, Mat& labels, const vector<int>& sizes, const Mat&
for( int i = bi; i < ei; i++, p++ )
{
Mat r = data.row(i);
r = r * (*cit) + *mit;
r = r * (*cit) + *mit;
if( labelType == CV_32FC1 )
labels.at<float>(p, 0) = (float)l;
else if( labelType == CV_32SC1 )
@@ -224,14 +224,14 @@ void CV_KMeansTest::run( int /*start_from*/ )
const int iters = 100;
int sizesArr[] = { 5000, 7000, 8000 };
int pointsCount = sizesArr[0]+ sizesArr[1] + sizesArr[2];
Mat data( pointsCount, 2, CV_32FC1 ), labels;
vector<int> sizes( sizesArr, sizesArr + sizeof(sizesArr) / sizeof(sizesArr[0]) );
Mat means;
vector<Mat> covs;
defaultDistribs( means, covs );
generateData( data, labels, sizes, means, covs, CV_32FC1, CV_32SC1 );
int code = cvtest::TS::OK;
float err;
Mat bestLabels;
@@ -327,24 +327,24 @@ void CV_KNearestTest::run( int /*start_from*/ )
class EM_Params
{
public:
EM_Params(int nclusters=10, int covMatType=EM::COV_MAT_DIAGONAL, int startStep=EM::START_AUTO_STEP,
const cv::TermCriteria& termCrit=cv::TermCriteria(cv::TermCriteria::COUNT+cv::TermCriteria::EPS, 100, FLT_EPSILON),
const cv::Mat* probs=0, const cv::Mat* weights=0,
const cv::Mat* means=0, const std::vector<cv::Mat>* covs=0)
: nclusters(nclusters), covMatType(covMatType), startStep(startStep),
probs(probs), weights(weights), means(means), covs(covs), termCrit(termCrit)
EM_Params(int _nclusters=10, int _covMatType=EM::COV_MAT_DIAGONAL, int _startStep=EM::START_AUTO_STEP,
const cv::TermCriteria& _termCrit=cv::TermCriteria(cv::TermCriteria::COUNT+cv::TermCriteria::EPS, 100, FLT_EPSILON),
const cv::Mat* _probs=0, const cv::Mat* _weights=0,
const cv::Mat* _means=0, const std::vector<cv::Mat>* _covs=0)
: nclusters(_nclusters), covMatType(_covMatType), startStep(_startStep),
probs(_probs), weights(_weights), means(_means), covs(_covs), termCrit(_termCrit)
{}
int nclusters;
int covMatType;
int startStep;
// all 4 following matrices should have type CV_32FC1
const cv::Mat* probs;
const cv::Mat* weights;
const cv::Mat* means;
const std::vector<cv::Mat>* covs;
cv::TermCriteria termCrit;
};
@@ -497,7 +497,7 @@ void CV_EMTest::run( int /*start_from*/ )
int currCode = runCase(caseIndex++, params, trainData, trainLabels, testData, testLabels, sizes);
code = currCode == cvtest::TS::OK ? code : currCode;
}
ts->set_failed_test_info( code );
}