Fixed several warnings on various platforms
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07f8bf9226
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4
3rdparty/libjasper/CMakeLists.txt
vendored
4
3rdparty/libjasper/CMakeLists.txt
vendored
@ -29,6 +29,10 @@ if(MSVC)
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add_definitions(-DJAS_WIN_MSVC_BUILD)
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endif()
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if(CMAKE_COMPILER_IS_GNUCXX)
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wno-uninitialized")
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endif()
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if(UNIX)
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if(CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
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@ -47,7 +47,7 @@ static void sortMatrixRowsByIndices(InputArray _src, InputArray _indices, Output
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Mat dst = _dst.getMat();
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for(size_t idx = 0; idx < indices.size(); idx++) {
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Mat originalRow = src.row(indices[idx]);
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Mat sortedRow = dst.row(idx);
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Mat sortedRow = dst.row((int)idx);
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originalRow.copyTo(sortedRow);
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}
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}
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@ -127,8 +127,9 @@ static Mat interp1(InputArray _x, InputArray _Y, InputArray _xi)
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case CV_32SC1: return interp1_<int>(x,Y,xi); break;
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case CV_32FC1: return interp1_<float>(x,Y,xi); break;
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case CV_64FC1: return interp1_<double>(x,Y,xi); break;
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default: CV_Error(CV_StsUnsupportedFormat, ""); return Mat();
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default: CV_Error(CV_StsUnsupportedFormat, ""); break;
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}
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return Mat();
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}
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namespace colormap
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@ -384,7 +384,7 @@ void Fisherfaces::train(InputArray src, InputArray _lbls) {
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if(labels.size() != (size_t)N)
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CV_Error(CV_StsUnsupportedFormat, "Labels must be given as integer (CV_32SC1).");
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// compute the Fisherfaces
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int C = remove_dups(labels).size(); // number of unique classes
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int C = (int)remove_dups(labels).size(); // number of unique classes
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// clip number of components to be a valid number
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if((_num_components <= 0) || (_num_components > (C-1)))
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_num_components = (C-1);
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@ -549,7 +549,7 @@ histc_(const Mat& src, int minVal=0, int maxVal=255, bool normed=false)
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calcHist(&src, 1, 0, Mat(), result, 1, &histSize, &histRange, true, false);
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// normalize
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if(normed) {
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result /= src.total();
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result /= (int)src.total();
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}
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return result.reshape(1,1);
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}
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@ -62,7 +62,7 @@ static Mat asRowMatrix(InputArrayOfArrays src, int rtype, double alpha=1, double
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if(n == 0)
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return Mat();
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// dimensionality of samples
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int d = src.getMat(0).total();
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int d = (int)src.getMat(0).total();
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// create data matrix
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Mat data(n, d, rtype);
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// copy data
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@ -82,7 +82,7 @@ void sortMatrixColumnsByIndices(InputArray _src, InputArray _indices, OutputArra
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Mat dst = _dst.getMat();
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for(size_t idx = 0; idx < indices.size(); idx++) {
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Mat originalCol = src.col(indices[idx]);
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Mat sortedCol = dst.col(idx);
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Mat sortedCol = dst.col((int)idx);
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originalCol.copyTo(sortedCol);
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}
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}
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@ -947,14 +947,14 @@ void LDA::lda(InputArray _src, InputArray _lbls) {
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vector<int> num2label = remove_dups(labels);
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map<int, int> label2num;
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for (size_t i = 0; i < num2label.size(); i++)
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label2num[num2label[i]] = i;
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label2num[num2label[i]] = (int)i;
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for (size_t i = 0; i < labels.size(); i++)
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mapped_labels[i] = label2num[labels[i]];
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// get sample size, dimension
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int N = data.rows;
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int D = data.cols;
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// number of unique labels
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int C = num2label.size();
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int C = (int)num2label.size();
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// throw error if less labels, than samples
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if (labels.size() != (size_t)N)
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CV_Error(CV_StsBadArg, "Error: The number of samples must equal the number of labels.");
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@ -1171,7 +1171,7 @@ private:
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break;
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std::transform(left.begin(), left.end(), buf_beg, WgcHelper(group, groupingMat));
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int minInd = min_element(buf_beg, buf_beg + left_size) - buf_beg;
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size_t minInd = min_element(buf_beg, buf_beg + left_size) - buf_beg;
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if (buf[minInd] < model.T_GroupingCorespondances) /* can add corespondance to group */
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{
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@ -47,6 +47,7 @@ namespace cv
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// On Win64 optimized versions of DFT and DCT fail the tests (fixed in VS2010)
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#if defined _MSC_VER && !defined CV_ICC && defined _M_X64 && _MSC_VER < 1600
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#pragma optimize("", off)
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#pragma warning( disable : 4748 )
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#endif
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/****************************************************************************************\
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@ -249,7 +249,7 @@ TEST_P(ProjectPoints, Accuracy)
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for (size_t i = 0; i < dst_gold.size(); ++i)
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{
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cv::Point2f res = h_dst.at<cv::Point2f>(0, i);
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cv::Point2f res = h_dst.at<cv::Point2f>(0, (int)i);
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cv::Point2f res_gold = dst_gold[i];
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ASSERT_LE(cv::norm(res_gold - res) / cv::norm(res_gold), 1e-3f);
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@ -291,7 +291,7 @@ TEST_P(SolvePnPRansac, Accuracy)
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cv::Mat rvec, tvec;
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std::vector<int> inliers;
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cv::gpu::solvePnPRansac(object, cv::Mat(1, image_vec.size(), CV_32FC2, &image_vec[0]),
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cv::gpu::solvePnPRansac(object, cv::Mat(1, (int)image_vec.size(), CV_32FC2, &image_vec[0]),
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camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)),
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rvec, tvec, false, 200, 2.f, 100, &inliers);
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@ -244,7 +244,7 @@ TEST_P(PyrLKOpticalFlow, Sparse)
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cv::goodFeaturesToTrack(gray_frame, pts, 1000, 0.01, 0.0);
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cv::gpu::GpuMat d_pts;
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cv::Mat pts_mat(1, pts.size(), CV_32FC2, (void*)&pts[0]);
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cv::Mat pts_mat(1, (int)pts.size(), CV_32FC2, (void*)&pts[0]);
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d_pts.upload(pts_mat);
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cv::gpu::PyrLKOpticalFlow pyrLK;
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@ -376,8 +376,9 @@ static bool pyopencv_to(PyObject* obj, uchar& value, const char* name = "<unknow
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{
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if(!obj || obj == Py_None)
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return true;
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value = (int)PyInt_AsLong(obj);
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return value != -1 || !PyErr_Occurred();
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int ivalue = (int)PyInt_AsLong(obj);
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value = cv::saturate_cast<uchar>(ivalue);
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return ivalue != -1 || !PyErr_Occurred();
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}
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static PyObject* pyopencv_from(double value)
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@ -353,7 +353,7 @@ Mat getMotion(int from, int to, const Mat *motions, int size)
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Mat getMotion(int from, int to, const vector<Mat> &motions)
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{
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return getMotion(from, to, &motions[0], motions.size());
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return getMotion(from, to, &motions[0], (int)motions.size());
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}
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} // namespace videostab
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@ -258,7 +258,7 @@ void OnePassStabilizer::estimateMotion()
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void OnePassStabilizer::stabilizeFrame()
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{
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Mat stabilizationMotion = motionFilter_->stabilize(curStabilizedPos_, &motions_[0], motions_.size());
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Mat stabilizationMotion = motionFilter_->stabilize(curStabilizedPos_, &motions_[0], (int)motions_.size());
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StabilizerBase::stabilizeFrame(stabilizationMotion);
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}
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@ -49,7 +49,7 @@ static void findCComp( IplImage* img )
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}
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int main( int argc, char** argv )
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int main()
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{
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int i, j;
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CvMemStorage* storage = cvCreateMemStorage(0);
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@ -24,7 +24,7 @@ void drawOptFlowMap(const CvMat* flow, CvMat* cflowmap, int step,
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}
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}
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int main(int argc, char** argv)
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int main()
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{
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CvCapture* capture = cvCreateCameraCapture(0);
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CvMat* prevgray = 0, *gray = 0, *flow = 0, *cflow = 0;
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@ -215,7 +215,6 @@ int main(int argc, const char* argv[])
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switch (key)
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{
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case 27:
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return 0;
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break;
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case 'A':
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