fixed warnings

modules/bioinspired/src/retina.cpp

@@ -599,7 +599,7 @@ void RetinaImpl::getParvoRAW(OutputArray parvoOutputBufferCopy){
 // original API level data accessors : get buffers addresses...
 const Mat RetinaImpl::getMagnoRAW() const {
     // create a cv::Mat header for the valarray
-    return Mat(_retinaFilter->getMovingContours().size(),1, CV_32F, (void*)get_data(_retinaFilter->getMovingContours()));
+    return Mat((int)_retinaFilter->getMovingContours().size(),1, CV_32F, (void*)get_data(_retinaFilter->getMovingContours()));
 
 }
 
@@ -607,11 +607,11 @@ const Mat RetinaImpl::getParvoRAW() const {
     if (_retinaFilter->getColorMode()) // check if color mode is enabled
     {
         // create a cv::Mat table (for RGB planes as a single vector)
-        return Mat(_retinaFilter->getColorOutput().size(), 1, CV_32F, (void*)get_data(_retinaFilter->getColorOutput()));
+        return Mat((int)_retinaFilter->getColorOutput().size(), 1, CV_32F, (void*)get_data(_retinaFilter->getColorOutput()));
     }
     // otherwise, output is gray level
     // create a cv::Mat header for the valarray
-    return Mat( _retinaFilter->getContours().size(), 1, CV_32F, (void*)get_data(_retinaFilter->getContours()));
+    return Mat((int)_retinaFilter->getContours().size(), 1, CV_32F, (void*)get_data(_retinaFilter->getContours()));
 }
 
 // private method called by constructirs

modules/calib3d/test/test_chesscorners.cpp

@@ -208,7 +208,7 @@ void CV_ChessboardDetectorTest::run_batch( const string& filename )
     }
 
     int progress = 0;
-    int max_idx = board_list.size()/2;
+    int max_idx = (int)board_list.size()/2;
     double sum_error = 0.0;
     int count = 0;
 

modules/features2d/test/test_descriptors_regression.cpp

@@ -80,10 +80,10 @@ static Mat readMatFromBin( const string& filename )
         size_t elements_read4 = fread( (void*)&dataSize, sizeof(int), 1, f );
         CV_Assert(elements_read1 == 1 && elements_read2 == 1 && elements_read3 == 1 && elements_read4 == 1);
 
-        size_t step = dataSize / rows / CV_ELEM_SIZE(type);
+        int step = dataSize / rows / CV_ELEM_SIZE(type);
-        CV_Assert(step >= (size_t)cols);
+        CV_Assert(step >= cols);
 
-        Mat m = Mat( rows, step, type).colRange(0, cols);
+        Mat m = Mat(rows, step, type).colRange(0, cols);
 
         size_t elements_read = fread( m.ptr(), 1, dataSize, f );
         CV_Assert(elements_read == (size_t)(dataSize));

modules/highgui/src/grfmt_tiff.cpp

@@ -406,9 +406,9 @@ bool TiffDecoder::readHdrData(Mat& img)
     TIFFGetField( tif, TIFFTAG_PHOTOMETRIC, &photometric );
     TIFFSetField(tif, TIFFTAG_SGILOGDATAFMT, SGILOGDATAFMT_FLOAT);
     int size = 3 * m_width * m_height * sizeof (float);
-    int strip_size = 3 * m_width * rows_per_strip;
+    tstrip_t strip_size = 3 * m_width * rows_per_strip;
     float *ptr = img.ptr<float>();
-    for (size_t i = 0; i < TIFFNumberOfStrips(tif); i++, ptr += strip_size)
+    for (tstrip_t i = 0; i < TIFFNumberOfStrips(tif); i++, ptr += strip_size)
     {
         TIFFReadEncodedStrip(tif, i, ptr, size);
         size -= strip_size * sizeof(float);

modules/highgui/src/grfmt_webp.cpp

@@ -174,12 +174,12 @@ bool WebPDecoder::readData(Mat &img)
         if (channels == 3)
         {
             res_ptr = WebPDecodeBGRInto(data.data, data.total(), out_data,
-                                        out_data_size, img.step);
+                                        (int)out_data_size, (int)img.step);
         }
         else if (channels == 4)
         {
             res_ptr = WebPDecodeBGRAInto(data.data, data.total(), out_data,
-                                         out_data_size, img.step);
+                                         (int)out_data_size, (int)img.step);
         }
 
         if(res_ptr == out_data)
@@ -255,22 +255,22 @@ bool WebPEncoder::write(const Mat& img, const std::vector<int>& params)
     {
         if(channels == 3)
         {
-            size = WebPEncodeLosslessBGR(image->data, width, height, image->step, &out);
+            size = WebPEncodeLosslessBGR(image->data, width, height, (int)image->step, &out);
         }
         else if(channels == 4)
         {
-            size = WebPEncodeLosslessBGRA(image->data, width, height, image->step, &out);
+            size = WebPEncodeLosslessBGRA(image->data, width, height, (int)image->step, &out);
         }
     }
     else
     {
         if(channels == 3)
         {
-            size = WebPEncodeBGR(image->data, width, height, image->step, quality, &out);
+            size = WebPEncodeBGR(image->data, width, height, (int)image->step, quality, &out);
         }
         else if(channels == 4)
         {
-            size = WebPEncodeBGRA(image->data, width, height, image->step, quality, &out);
+            size = WebPEncodeBGRA(image->data, width, height, (int)image->step, quality, &out);
         }
     }
 

modules/imgproc/src/intersection.cpp

@@ -49,7 +49,7 @@ namespace cv
 
 int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion )
 {
-    const float samePointEps = 0.00001; // used to test if two points are the same
+    const float samePointEps = 0.00001f; // used to test if two points are the same
 
     Point2f vec1[4], vec2[4];
     Point2f pts1[4], pts2[4];

modules/imgproc/src/lsd.cpp

@@ -473,8 +473,7 @@ void LineSegmentDetectorImpl::flsd(std::vector<Vec4i>& lines,
 
     // Search for line segments
     unsigned int ls_count = 0;
-    unsigned int list_size = list.size();
+    for(size_t i = 0, list_size = list.size(); i < list_size; ++i)
-    for(unsigned int i = 0; i < list_size; ++i)
     {
         unsigned int adx = list[i].p.x + list[i].p.y * img_width;
         if((used.data[adx] == NOTUSED) && (angles_data[adx] != NOTDEF))

modules/imgproc/test/test_intersection.cpp

@@ -376,8 +376,8 @@ void CV_RotatedRectangleIntersectionTest::test7()
 
     rect1.center.x = 0;
     rect1.center.y = 0;
-    rect1.size.width = 12.34;
+    rect1.size.width = 12.34f;
-    rect1.size.height = 56.78;
+    rect1.size.height = 56.78f;
     rect1.angle = 0;
 
     rect2.center.x = 0;
@@ -464,7 +464,7 @@ void CV_RotatedRectangleIntersectionTest::test9()
     rect2.center.x = 2;
     rect2.center.y = 0;
     rect2.size.width = 2;
-    rect2.size.height = 123.45;
+    rect2.size.height = 123.45f;
     rect2.angle = 0;
 
     vector<Point2f> vertices;

modules/nonfree/test/test_features2d.cpp

@@ -275,8 +275,8 @@ static Mat readMatFromBin( const string& filename )
         size_t elements_read4 = fread( (void*)&dataSize, sizeof(int), 1, f );
         CV_Assert(elements_read1 == 1 && elements_read2 == 1 && elements_read3 == 1 && elements_read4 == 1);
 
-        size_t step = dataSize / rows / CV_ELEM_SIZE(type);
+        int step = dataSize / rows / CV_ELEM_SIZE(type);
-        CV_Assert(step >= (size_t)cols);
+        CV_Assert(step >= cols);
 
         Mat m = Mat( rows, step, type).colRange(0, cols);
 

modules/objdetect/src/erfilter.cpp

@@ -795,7 +795,7 @@ ERStat* ERFilterNM::er_tree_filter ( InputArray image, ERStat * stat, ERStat *pa
         int p_prev = p-1;
         int p_next = p+1;
         if (p_prev == -1)
-            p_prev = contour_poly.size()-1;
+            p_prev = (int)contour_poly.size()-1;
         if (p_next == (int)contour_poly.size())
             p_next = 0;
 
@@ -2455,9 +2455,9 @@ void MaxMeaningfulClustering::build_merge_info(double *Z, int N, vector<HCluster
 
         cluster.dist   = dist;
         if (cluster.dist >= 1)
-            cluster.dist = 0.999999;
+            cluster.dist = 0.999999f;
         if (cluster.dist == 0)
-            cluster.dist = 1.e-25;
+            cluster.dist = 1.e-25f;
 
         cluster.dist_ext   = 1;
 
@@ -2811,7 +2811,7 @@ void erGrouping(InputArrayOfArrays _src, vector<vector<ERStat> > &regions, const
 
         for (int f=0; f<num_features; f++)
         {
-            unsigned int N = regions.at(c).size();
+            unsigned int N = (unsigned int)regions.at(c).size();
             if (N<3) break;
             int dim = dims[f];
             double *data = (double*)malloc(dim*N * sizeof(double));
@@ -2892,7 +2892,7 @@ void erGrouping(InputArrayOfArrays _src, vector<vector<ERStat> > &regions, const
         }
 
         // Find the Max. Meaningful Clusters in the co-occurrence matrix
-        mm_clustering(D, regions.at(c).size(), METHOD_METR_AVERAGE, &meaningful_clusters);
+        mm_clustering(D, (unsigned int)regions.at(c).size(), METHOD_METR_AVERAGE, &meaningful_clusters);
         free(D);
 
 

modules/optim/src/lpsolver.cpp

@@ -84,11 +84,12 @@ int solveLP(const Mat& Func, const Mat& Constr, Mat& z){
     //return the optimal solution
     z.create(c.cols,1,CV_64FC1);
     MatIterator_<double> it=z.begin<double>();
+    unsigned int nsize = (unsigned int)N.size();
     for(int i=1;i<=c.cols;i++,it++){
-        if(indexToRow[i]<N.size()){
+        if(indexToRow[i]<nsize){
             *it=0;
         }else{
-            *it=b.at<double>(indexToRow[i]-N.size(),b.cols-1);
+            *it=b.at<double>(indexToRow[i]-nsize,b.cols-1);
         }
     }
 
@@ -102,7 +103,7 @@ static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<
         *it=it[-1]+1;
     }
     B.resize(b.rows);
-    B[0]=N.size();
+    B[0]=(int)N.size();
     for (std::vector<int>::iterator it = B.begin()+1 ; it != B.end(); ++it){
         *it=it[-1]+1;
     }
@@ -151,8 +152,9 @@ static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<
     dprintf(("\tAFTER INNER_SIMPLEX\n"));
     print_simplex_state(c,b,v,N,B);
 
-    if(indexToRow[0]>=N.size()){
+    unsigned int nsize = (unsigned int)N.size();
-        int iterator_offset=indexToRow[0]-N.size();
+    if(indexToRow[0]>=nsize){
+        int iterator_offset=indexToRow[0]-nsize;
         if(b(iterator_offset,b.cols-1)>0){
             return SOLVELP_UNFEASIBLE;
         }
@@ -176,14 +178,14 @@ static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<
     c=0;
     v=0;
     for(int I=1;I<old_c.cols;I++){
-        if(indexToRow[I]<N.size()){
+        if(indexToRow[I]<nsize){
             dprintf(("I=%d from nonbasic\n",I));
             int iterator_offset=indexToRow[I];
             c(0,iterator_offset)+=old_c(0,I);
             print_matrix(c);
         }else{
             dprintf(("I=%d from basic\n",I));
-            int iterator_offset=indexToRow[I]-N.size();
+            int iterator_offset=indexToRow[I]-nsize;
             c-=old_c(0,I)*b.row(iterator_offset).colRange(0,b.cols-1);
             v+=old_c(0,I)*b(iterator_offset,b.cols-1);
             print_matrix(c);

modules/photo/src/align.cpp

@@ -135,7 +135,7 @@ public:
             computeBitmaps(pyr0[level], tb1, eb1);
             computeBitmaps(pyr1[level], tb2, eb2);
 
-            int min_err = pyr0[level].total();
+            int min_err = (int)pyr0[level].total();
             Point new_shift(shift);
             for(int i = -1; i <= 1; i++) {
                 for(int j = -1; j <= 1; j++) {
@@ -253,7 +253,7 @@ protected:
         calcHist(&img, 1, &channels, Mat(), hist, 1, &hist_size, ranges);
         float *ptr = hist.ptr<float>();
         int median = 0, sum = 0;
-        int thresh = img.total() / 2;
+        int thresh = (int)img.total() / 2;
         while(sum < thresh && median < LDR_SIZE) {
             sum += static_cast<int>(ptr[median]);
             median++;

modules/photo/src/calibrate.cpp

@@ -97,7 +97,7 @@ public:
 
         std::vector<Mat> result_split(channels);
         for(int channel = 0; channel < channels; channel++) {
-            Mat A = Mat::zeros(sample_points.size() * images.size() + LDR_SIZE + 1, LDR_SIZE + sample_points.size(), CV_32F);
+            Mat A = Mat::zeros((int)sample_points.size() * (int)images.size() + LDR_SIZE + 1, LDR_SIZE + (int)sample_points.size(), CV_32F);
             Mat B = Mat::zeros(A.rows, 1, CV_32F);
 
             int eq = 0;
@@ -106,8 +106,8 @@ public:
 
                     int val = images[j].ptr()[3*(sample_points[i].y * images[j].cols + sample_points[j].x) + channel];
                     A.at<float>(eq, val) = w.at<float>(val);
-                    A.at<float>(eq, LDR_SIZE + i) = -w.at<float>(val);
+                    A.at<float>(eq, LDR_SIZE + (int)i) = -w.at<float>(val);
-                    B.at<float>(eq, 0) = w.at<float>(val) * log(times.at<float>(j));
+                    B.at<float>(eq, 0) = w.at<float>(val) * log(times.at<float>((int)j));
                     eq++;
                 }
             }
@@ -219,7 +219,7 @@ public:
                 float* rad_ptr = radiance.ptr<float>();
                 for(size_t pos = 0; pos < images[i].total(); pos++) {
                     for(int c = 0; c < channels; c++, ptr++, rad_ptr++) {
-                        new_response.at<Vec3f>(*ptr)[c] += times.at<float>(i) * *rad_ptr;
+                        new_response.at<Vec3f>(*ptr)[c] += times.at<float>((int)i) * *rad_ptr;
                     }
                 }
             }

modules/photo/src/merge.cpp

@@ -106,7 +106,7 @@ public:
             LUT(images[i], response, response_img);
             split(response_img, splitted);
             for(int c = 0; c < channels; c++) {
-                result_split[c] += w.mul(splitted[c] - exp_values.at<float>(i));
+                result_split[c] += w.mul(splitted[c] - exp_values.at<float>((int)i));
             }
             weight_sum += w;
         }
@@ -327,8 +327,8 @@ public:
             LUT(images[i], weight, w);
             LUT(images[i], response, im);
 
-            result += times.at<float>(i) * w.mul(im);
+            result += times.at<float>((int)i) * w.mul(im);
-            wsum += times.at<float>(i) * times.at<float>(i) * w;
+            wsum += times.at<float>((int)i) * times.at<float>((int)i) * w;
         }
         result = result.mul(1 / wsum);
     }

modules/photo/src/tonemap.cpp

@@ -505,7 +505,7 @@ protected:
     void calculateSum(std::vector<Mat>& x_contrast, std::vector<Mat>& y_contrast, Mat& sum)
     {
         sum = Mat::zeros(x_contrast[x_contrast.size() - 1].size(), CV_32F);
-        for(int i = x_contrast.size() - 1; i >= 0; i--)
+        for(int i = (int)x_contrast.size() - 1; i >= 0; i--)
         {
             Mat grad_x, grad_y;
             getGradient(x_contrast[i], grad_x, 1);

modules/shape/src/aff_trans.cpp

@@ -112,7 +112,7 @@ static Mat _localAffineEstimate(const std::vector<Point2f>& shape1, const std::v
                                 bool fullAfine)
 {
     Mat out(2,3,CV_32F);
-    int siz=2*shape1.size();
+    int siz=2*(int)shape1.size();
 
     if (fullAfine)
     {

modules/shape/src/sc_dis.cpp

@@ -65,10 +65,10 @@ public:
         comparer=_comparer;
         iterations=_iterations;
         transformer=_transformer;
-        bendingEnergyWeight=0.3;
+        bendingEnergyWeight=0.3f;
-        imageAppearanceWeight=0.0;
+        imageAppearanceWeight=0.0f;
-        shapeContextWeight=1.0;
+        shapeContextWeight=1.0f;
-        sigma=10;
+        sigma=10.0f;
         name_ = "ShapeDistanceExtractor.SCD";
     }
 
@@ -503,7 +503,7 @@ void SCDMatcher::hungarian(cv::Mat &costMatrix, std::vector<cv::DMatch> &outMatc
     std::vector<int> matches(costMatrix.rows, 0), colsol(costMatrix.rows), rowsol(costMatrix.rows);
     std::vector<float> d(costMatrix.rows), pred(costMatrix.rows), v(costMatrix.rows);
 
-    const float LOWV=1e-10;
+    const float LOWV = 1e-10f;
     bool unassignedfound;
     int  i=0, imin=0, numfree=0, prvnumfree=0, f=0, i0=0, k=0, freerow=0;
     int  j=0, j1=0, j2=0, endofpath=0, last=0, low=0, up=0;

modules/shape/src/tps_trans.cpp

@@ -212,9 +212,9 @@ void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts
     }
 
     // Organizing the correspondent points in matrix style //
-    Mat shape1(matches.size(),2,CV_32F); // transforming shape
+    Mat shape1((int)matches.size(),2,CV_32F); // transforming shape
-    Mat shape2(matches.size(),2,CV_32F); // target shape
+    Mat shape2((int)matches.size(),2,CV_32F); // target shape
-    for (size_t i=0; i<matches.size(); i++)
+    for (int i=0, end = (int)matches.size(); i<end; i++)
     {
         Point2f pt1=pts1.at<Point2f>(0,matches[i].queryIdx);
         shape1.at<float>(i,0) = pt1.x;
@@ -229,11 +229,11 @@ void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts
     // Building the matrices for solving the L*(w|a)=(v|0) problem with L={[K|P];[P'|0]}
 
     //Building K and P (Neede to buil L)
-    Mat matK(matches.size(),matches.size(),CV_32F);
+    Mat matK((int)matches.size(),(int)matches.size(),CV_32F);
-    Mat matP(matches.size(),3,CV_32F);
+    Mat matP((int)matches.size(),3,CV_32F);
-    for (size_t i=0; i<matches.size(); i++)
+    for (int i=0, end=(int)matches.size(); i<end; i++)
     {
-        for (size_t j=0; j<matches.size(); j++)
+        for (int j=0; j<end; j++)
         {
             if (i==j)
             {
@@ -251,19 +251,19 @@ void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts
     }
 
     //Building L
-    Mat matL=Mat::zeros(matches.size()+3,matches.size()+3,CV_32F);
+    Mat matL=Mat::zeros((int)matches.size()+3,(int)matches.size()+3,CV_32F);
-    Mat matLroi(matL, Rect(0,0,matches.size(),matches.size())); //roi for K
+    Mat matLroi(matL, Rect(0,0,(int)matches.size(),(int)matches.size())); //roi for K
     matK.copyTo(matLroi);
-    matLroi = Mat(matL,Rect(matches.size(),0,3,matches.size())); //roi for P
+    matLroi = Mat(matL,Rect((int)matches.size(),0,3,(int)matches.size())); //roi for P
     matP.copyTo(matLroi);
     Mat matPt;
     transpose(matP,matPt);
-    matLroi = Mat(matL,Rect(0,matches.size(),matches.size(),3)); //roi for P'
+    matLroi = Mat(matL,Rect(0,(int)matches.size(),(int)matches.size(),3)); //roi for P'
     matPt.copyTo(matLroi);
 
     //Building B (v|0)
-    Mat matB = Mat::zeros(matches.size()+3,2,CV_32F);
+    Mat matB = Mat::zeros((int)matches.size()+3,2,CV_32F);
-    for (size_t i=0; i<matches.size(); i++)
+    for (int i=0, end = (int)matches.size(); i<end; i++)
     {
         matB.at<float>(i,0) = shape2.at<float>(i,0); //x's
         matB.at<float>(i,1) = shape2.at<float>(i,1); //y's

modules/shape/test/test_emdl1.cpp

@@ -46,11 +46,11 @@ using namespace std;
 
 const int angularBins=12;
 const int radialBins=4;
-const float minRad=0.2;
+const float minRad=0.2f;
 const float maxRad=2;
 const int NSN=5;//10;//20; //number of shapes per class
 const int NP=100; //number of points sympliying the contour
-const float outlierWeight=0.1;
+const float outlierWeight=0.1f;
 const int numOutliers=20;
 const float CURRENT_MAX_ACCUR=95; //98% and 99% reached in several tests, 95 is fixed as minimum boundary
 
@@ -96,7 +96,7 @@ vector <Point2f> CV_ShapeEMDTest::convertContourType(const Mat& currentQuery, in
 
     // In case actual number of points is less than n
     int dum=0;
-    for (int add=contoursQuery.size()-1; add<n; add++)
+    for (int add=(int)contoursQuery.size()-1; add<n; add++)
     {
         contoursQuery.push_back(contoursQuery[dum++]); //adding dummy values
     }
@@ -148,14 +148,14 @@ void CV_ShapeEMDTest::mpegTest()
     listShapeNames(namesHeaders);
 
     // distance matrix //
-    Mat distanceMat=Mat::zeros(NSN*namesHeaders.size(), NSN*namesHeaders.size(), CV_32F);
+    Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
 
     // query contours (normal v flipped, h flipped) and testing contour //
     vector<Point2f> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
 
     // reading query and computing its properties //
     int counter=0;
-    const int loops=NSN*namesHeaders.size()*NSN*namesHeaders.size();
+    const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
     for (size_t n=0; n<namesHeaders.size(); n++)
     {
         for (int i=1; i<=NSN; i++)
@@ -165,7 +165,6 @@ void CV_ShapeEMDTest::mpegTest()
             thepathandname<<path+namesHeaders[n]<<"-"<<i<<".png";
             Mat currentQuery, flippedHQuery, flippedVQuery;
             currentQuery=imread(thepathandname.str(), IMREAD_GRAYSCALE);
-            Mat currentQueryBuf=currentQuery.clone();
             flip(currentQuery, flippedHQuery, 0);
             flip(currentQuery, flippedVQuery, 1);
             // compute border of the query and its flipped versions //
@@ -184,8 +183,8 @@ void CV_ShapeEMDTest::mpegTest()
                     counter++;
                     if (nt==n && it==i)
                     {
-                        distanceMat.at<float>(NSN*n+i-1,
+                        distanceMat.at<float>(NSN*(int)n+i-1,
-                                              NSN*nt+it-1)=0;
+                                              NSN*(int)nt+it-1)=0;
                         continue;
                     }
                     // read testing image //
@@ -200,9 +199,9 @@ void CV_ShapeEMDTest::mpegTest()
                     std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
                     std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
                                " and "<<namesHeaders[nt]<<it<<": ";
-                    distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)=
+                    distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
                             computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
-                    std::cout<<distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)<<std::endl;
+                    std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
                 }
             }
         }

modules/shape/test/test_hausdorff.cpp

@@ -75,13 +75,13 @@ CV_HaussTest::~CV_HaussTest()
 vector<Point2f> CV_HaussTest::normalizeContour(const vector<Point> &contour)
 {
     vector<Point2f> output(contour.size());
-    Mat disMat(contour.size(),contour.size(),CV_32F);
+    Mat disMat((int)contour.size(),(int)contour.size(),CV_32F);
     Point2f meanpt(0,0);
     float meanVal=1;
 
-    for (size_t ii=0; ii<contour.size(); ii++)
+    for (int ii=0, end1 = (int)contour.size(); ii<end1; ii++)
     {
-        for (size_t jj=0; jj<contour.size(); jj++)
+        for (int jj=0, end2 = (int)contour.size(); end2; jj++)
         {
             if (ii==jj) disMat.at<float>(ii,jj)=0;
             else
@@ -128,7 +128,7 @@ vector <Point> CV_HaussTest::convertContourType(const Mat& currentQuery, int n)
     }
 
     // In case actual number of points is less than n
-    for (int add=contoursQuery.size()-1; add<n; add++)
+    for (int add=(int)contoursQuery.size()-1; add<n; add++)
     {
         contoursQuery.push_back(contoursQuery[contoursQuery.size()-add+1]); //adding dummy values
     }
@@ -160,14 +160,14 @@ void CV_HaussTest::mpegTest()
     listShapeNames(namesHeaders);
 
     // distance matrix //
-    Mat distanceMat=Mat::zeros(NSN*namesHeaders.size(), NSN*namesHeaders.size(), CV_32F);
+    Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
 
     // query contours (normal v flipped, h flipped) and testing contour //
     vector<Point> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
 
     // reading query and computing its properties //
     int counter=0;
-    const int loops=NSN*namesHeaders.size()*NSN*namesHeaders.size();
+    const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
     for (size_t n=0; n<namesHeaders.size(); n++)
     {
         for (int i=1; i<=NSN; i++)
@@ -195,8 +195,8 @@ void CV_HaussTest::mpegTest()
                     counter++;
                     if (nt==n && it==i)
                     {
-                        distanceMat.at<float>(NSN*n+i-1,
+                        distanceMat.at<float>(NSN*(int)n+i-1,
-                                              NSN*nt+it-1)=0;
+                                              NSN*(int)nt+it-1)=0;
                         continue;
                     }
                     // read testing image //
@@ -212,9 +212,9 @@ void CV_HaussTest::mpegTest()
                     std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
                     std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
                                " and "<<namesHeaders[nt]<<it<<": ";
-                    distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)=
+                    distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
                             computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
-                    std::cout<<distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)<<std::endl;
+                    std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
                 }
             }
         }

modules/shape/test/test_shape.cpp

@@ -46,13 +46,13 @@ using namespace std;
 
 const int angularBins=12;
 const int radialBins=4;
-const float minRad=0.2;
+const float minRad=0.2f;
 const float maxRad=2;
 const int NSN=5;//10;//20; //number of shapes per class
 const int NP=120; //number of points sympliying the contour
-const float outlierWeight=0.1;
+const float outlierWeight=0.1f;
 const int numOutliers=20;
-const float CURRENT_MAX_ACCUR=95.0; //99% and 100% reached in several tests, 95 is fixed as minimum boundary
+const float CURRENT_MAX_ACCUR=95; //99% and 100% reached in several tests, 95 is fixed as minimum boundary
 
 class CV_ShapeTest : public cvtest::BaseTest
 {
@@ -95,7 +95,7 @@ vector <Point2f> CV_ShapeTest::convertContourType(const Mat& currentQuery, int n
     }
 
     // In case actual number of points is less than n
-    for (int add=contoursQuery.size()-1; add<n; add++)
+    for (int add=(int)contoursQuery.size()-1; add<n; add++)
     {
         contoursQuery.push_back(contoursQuery[contoursQuery.size()-add+1]); //adding dummy values
     }
@@ -126,7 +126,7 @@ float CV_ShapeTest::computeShapeDistance(vector <Point2f>& query1, vector <Point
     //waitKey(0);
     Ptr <ShapeContextDistanceExtractor> mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad);
     //Ptr <HistogramCostExtractor> cost = createNormHistogramCostExtractor(cv::DIST_L1);
-    Ptr <HistogramCostExtractor> cost = createChiHistogramCostExtractor(30,0.15);
+    Ptr <HistogramCostExtractor> cost = createChiHistogramCostExtractor(30,0.15f);
     //Ptr <HistogramCostExtractor> cost = createEMDHistogramCostExtractor();
     //Ptr <HistogramCostExtractor> cost = createEMDL1HistogramCostExtractor();
     mysc->setIterations(1);
@@ -148,14 +148,14 @@ void CV_ShapeTest::mpegTest()
     listShapeNames(namesHeaders);
 
     // distance matrix //
-    Mat distanceMat=Mat::zeros(NSN*namesHeaders.size(), NSN*namesHeaders.size(), CV_32F);
+    Mat distanceMat=Mat::zeros(NSN*(int)namesHeaders.size(), NSN*(int)namesHeaders.size(), CV_32F);
 
     // query contours (normal v flipped, h flipped) and testing contour //
     vector<Point2f> contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting;
 
     // reading query and computing its properties //
     int counter=0;
-    const int loops=NSN*namesHeaders.size()*NSN*namesHeaders.size();
+    const int loops=NSN*(int)namesHeaders.size()*NSN*(int)namesHeaders.size();
     for (size_t n=0; n<namesHeaders.size(); n++)
     {
         for (int i=1; i<=NSN; i++)
@@ -184,8 +184,8 @@ void CV_ShapeTest::mpegTest()
                     counter++;
                     if (nt==n && it==i)
                     {
-                        distanceMat.at<float>(NSN*n+i-1,
+                        distanceMat.at<float>(NSN*(int)n+i-1,
-                                              NSN*nt+it-1)=0;
+                                              NSN*(int)nt+it-1)=0;
                         continue;
                     }
                     // read testing image //
@@ -200,9 +200,9 @@ void CV_ShapeTest::mpegTest()
                     std::cout<<std::endl<<"Progress: "<<counter<<"/"<<loops<<": "<<100*double(counter)/loops<<"% *******"<<std::endl;
                     std::cout<<"Computing shape distance between "<<namesHeaders[n]<<i<<
                                " and "<<namesHeaders[nt]<<it<<": ";
-                    distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)=
+                    distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)=
                             computeShapeDistance(contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting);
-                    std::cout<<distanceMat.at<float>(NSN*n+i-1, NSN*nt+it-1)<<std::endl;
+                    std::cout<<distanceMat.at<float>(NSN*(int)n+i-1, NSN*(int)nt+it-1)<<std::endl;
                 }
             }
         }

samples/cpp/shape_example.cpp

@@ -36,7 +36,7 @@ static vector<Point> simpleContour( const Mat& currentQuery, int n=300 )
 
     // In case actual number of points is less than n
     int dummy=0;
-    for (int add=contoursQuery.size()-1; add<n; add++)
+    for (int add=(int)contoursQuery.size()-1; add<n; add++)
     {
         contoursQuery.push_back(contoursQuery[dummy++]); //adding dummy values
     }

samples/cpp/textdetection.cpp

@@ -44,7 +44,7 @@ int  main(int argc, const char * argv[])
         channels.push_back(255-channels[c]);
 
     // Create ERFilter objects with the 1st and 2nd stage default classifiers
-    Ptr<ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"),16,0.00015,0.13,0.2,true,0.1);
+    Ptr<ERFilter> er_filter1 = createERFilterNM1(loadClassifierNM1("trained_classifierNM1.xml"),16,0.00015f,0.13f,0.2f,true,0.1f);
     Ptr<ERFilter> er_filter2 = createERFilterNM2(loadClassifierNM2("trained_classifierNM2.xml"),0.5);
 
     vector<vector<ERStat> > regions(channels.size());
@@ -94,7 +94,7 @@ void show_help_and_exit(const char *cmd)
 
 void groups_draw(Mat &src, vector<Rect> &groups)
 {
-    for (int i=groups.size()-1; i>=0; i--)
+    for (int i=(int)groups.size()-1; i>=0; i--)
     {
         if (src.type() == CV_8UC3)
             rectangle(src,groups.at(i).tl(),groups.at(i).br(),Scalar( 0, 255, 255 ), 3, 8 );