ret.clear();
ret.reserve(glob_result.gl_pathc);
- for(uint i = 0; i < glob_result.gl_pathc; ++i)
+ for(unsigned int i = 0; i < glob_result.gl_pathc; ++i)
{
ret.push_back(std::string(glob_result.gl_pathv[i]));
dprintf("%s\n", ret[i].c_str());
for (int si = 0; si < nsamples; ++si)
{
float decision = dptr[si] = predict(trainData.col(si), stab, false, false);
- mptr[si] = cv::saturate_cast<uchar>((uint)( (responses.ptr<float>(si)[0] == 1.f) && (decision == 1.f)));
+ mptr[si] = cv::saturate_cast<uchar>((unsigned int)( (responses.ptr<float>(si)[0] == 1.f) && (decision == 1.f)));
}
int weaks = weak->total;
void cv::Octave::write( cv::FileStorage &fso, const FeaturePool* pool, InputArray _thresholds) const
{
CV_Assert(!_thresholds.empty());
- cv::Mat used( 1, weak->total * (pow(2, params.max_depth) - 1), CV_32SC1);
+ cv::Mat used( 1, weak->total * ( pow(2.f, params.max_depth) - 1), CV_32SC1);
int* usedPtr = used.ptr<int>(0);
int nfeatures = 0;
cv::Mat thresholds = _thresholds.getMat();