attempt to add 0d/1d mat support to OpenCV

modules/3d/misc/java/test/Cv3dTest.java

@@ -549,7 +549,8 @@ public void testUndistortPointsListOfPointListOfPointMatMat() {
 
         Cv3d.undistortPoints(src, dst, cameraMatrix, distCoeffs);
 
-        assertEquals(src.size(), dst.size());
+        assertEquals(src.cols(), dst.rows());
+        assertEquals(src.rows(), dst.cols());
         for(int i=0; i<src.toList().size(); i++) {
             //Log.d("UndistortPoints", "s="+src.get(i)+", d="+dst.get(i));
             assertTrue(src.toList().get(i).equals(dst.toList().get(i)));

modules/3d/perf/perf_pnp.cpp

@@ -40,7 +40,8 @@ PERF_TEST_P(PointsNum_Algo, solvePnP,
     projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
 
     //add noise
-    Mat noise(1, (int)points2d.size(), CV_32FC2);
+    int sz = (int)points2d.size();
+    Mat noise(1, &sz, CV_32FC2);
     randu(noise, 0, 0.01);
     cv::add(points2d, noise, points2d);
 
@@ -93,7 +94,8 @@ PERF_TEST_P(PointsNum_Algo, solvePnPSmallPoints,
     cv::projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
 
     //add noise
-    Mat noise(1, (int)points2d.size(), CV_32FC2);
+    int npoints = (int)points2d.size();
+    Mat noise(1, &npoints, CV_32FC2);
     randu(noise, -0.001, 0.001);
     cv::add(points2d, noise, points2d);
 

modules/3d/src/solvepnp.cpp

@@ -1112,9 +1112,10 @@ int solvePnPGeneric( InputArray _opoints, InputArray _ipoints,
 
         for (size_t i = 0; i < vec_rvecs.size(); i++)
         {
-            std::vector<Point2d> projectedPoints;
+            Mat projectedPoints;
             projectPoints(objectPoints, vec_rvecs[i], vec_tvecs[i], cameraMatrix, distCoeffs, projectedPoints);
-            double rmse = norm(Mat(projectedPoints, false), imagePoints, NORM_L2) / sqrt(2*projectedPoints.size());
+            int nprojectedPoints = (int)projectedPoints.total();
+            double rmse = norm(projectedPoints, imagePoints, NORM_L2) / sqrt(2*nprojectedPoints);
 
             Mat err = reprojectionError.getMat();
             if (type == CV_32F)

modules/calib/misc/java/test/CalibTest.java

@@ -67,8 +67,8 @@ public void testFindCirclesGridMatSizeMat() {
 
         assertTrue(Calib.findCirclesGrid(img, new Size(5, 5), centers));
 
-        assertEquals(25, centers.rows());
-        assertEquals(1, centers.cols());
+        assertEquals(1, centers.rows());
+        assertEquals(25, centers.cols());
         assertEquals(CvType.CV_32FC2, centers.type());
     }
 
@@ -93,8 +93,8 @@ public void testFindCirclesGridMatSizeMatInt() {
         assertTrue(Calib.findCirclesGrid(img, new Size(3, 5), centers, Calib.CALIB_CB_CLUSTERING
                 | Calib.CALIB_CB_ASYMMETRIC_GRID));
 
-        assertEquals(15, centers.rows());
-        assertEquals(1, centers.cols());
+        assertEquals(1, centers.rows());
+        assertEquals(15, centers.cols());
         assertEquals(CvType.CV_32FC2, centers.type());
     }
 

modules/calib/src/calibration.cpp

@@ -334,7 +334,7 @@ static double calibrateCameraInternal( const Mat& objectPoints,
     //std::cout << "dist0:" << _k << std::endl;
 
     std::vector<double> param(nparams, 0.0);
-    Mat paramM(param, false);
+    Mat paramM = Mat(param, false).reshape(1, nparams);
     std::vector<uchar> mask(nparams, (uchar)1);
 
     int solveMethod = DECOMP_EIG;

modules/calib/src/chessboard.cpp

@@ -272,7 +272,7 @@ void polyfit(const Mat& src_x, const Mat& src_y, Mat& dst, int order)
             A.at<double>(y,x) = srcX.at<double>(y)*A.at<double>(y,x-1);
     }
     cv::Mat w;
-    solve(A,srcY,w,DECOMP_SVD);
+    solve(A,srcY.reshape(1, npoints),w,DECOMP_SVD);
     w.convertTo(dst, ((src_x.depth() == CV_64F || src_y.depth() == CV_64F) ? CV_64F : CV_32F));
 }
 

modules/calib/src/circlesgrid.cpp

@@ -204,16 +204,16 @@ void CirclesGridClusterFinder::findCorners(const std::vector<cv::Point2f> &hull2
   //corners are the most sharp angles (6)
   Mat anglesMat = Mat(angles);
   Mat sortedIndices;
-  sortIdx(anglesMat, sortedIndices, SORT_EVERY_COLUMN + SORT_DESCENDING);
+  sortIdx(anglesMat, sortedIndices, SORT_EVERY_ROW + SORT_DESCENDING);
   CV_Assert(sortedIndices.type() == CV_32SC1);
-  CV_Assert(sortedIndices.cols == 1);
+  CV_Assert(sortedIndices.rows == 1);
   const int cornersCount = isAsymmetricGrid ? 6 : 4;
   Mat cornersIndices;
-  cv::sort(sortedIndices.rowRange(0, cornersCount), cornersIndices, SORT_EVERY_COLUMN + SORT_ASCENDING);
+  cv::sort(sortedIndices.colRange(0, cornersCount), cornersIndices, SORT_EVERY_ROW + SORT_ASCENDING);
   corners.clear();
   for(int i=0; i<cornersCount; i++)
   {
-    corners.push_back(hull2f[cornersIndices.at<int>(i, 0)]);
+    corners.push_back(hull2f[cornersIndices.at<int>(i)]);
   }
 }
 
@@ -427,7 +427,8 @@ void CirclesGridClusterFinder::parsePatternPoints(const std::vector<cv::Point2f>
   CV_Error(Error::StsNotImplemented, "The desired functionality requires flann module, which was disabled.");
 #else
   flann::LinearIndexParams flannIndexParams;
-  flann::Index flannIndex(Mat(rectifiedPatternPoints).reshape(1), flannIndexParams);
+  flann::Index flannIndex(Mat(rectifiedPatternPoints).reshape(1,
+                (int)rectifiedPatternPoints.size()), flannIndexParams);
 
   centers.clear();
   for( int i = 0; i < patternSize.height; i++ )
@@ -1126,7 +1127,8 @@ void CirclesGridFinder::findBasis(const std::vector<Point2f> &samples, std::vect
   TermCriteria termCriteria;
   Mat centers;
   const int clustersCount = 4;
-  kmeans(Mat(samples).reshape(1, 0), clustersCount, bestLabels, termCriteria, parameters.kmeansAttempts,
+  int nsamples = (int)samples.size();
+  kmeans(Mat(samples).reshape(1, nsamples), clustersCount, bestLabels, termCriteria, parameters.kmeansAttempts,
          KMEANS_RANDOM_CENTERS, centers);
   CV_Assert( centers.type() == CV_32FC1 );
 

modules/calib/src/fisheye.cpp

@@ -183,8 +183,8 @@ double cv::fisheye::calibrate(InputArrayOfArrays objectPoints, InputArrayOfArray
     }
     else
     {
-        if (rvecs.needed()) Mat(omc).convertTo(rvecs, rvecs.empty() ? CV_64FC3 : rvecs.type());
-        if (tvecs.needed()) Mat(Tc).convertTo(tvecs, tvecs.empty() ? CV_64FC3 : tvecs.type());
+        if (rvecs.needed()) Mat(omc).reshape(3, (int)omc.size()).convertTo(rvecs, rvecs.empty() ? CV_64FC3 : rvecs.type());
+        if (tvecs.needed()) Mat(Tc).reshape(3, (int)Tc.size()).convertTo(tvecs, tvecs.empty() ? CV_64FC3 : tvecs.type());
     }
 
     return rms;
@@ -340,7 +340,9 @@ double cv::fisheye::stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayO
             Mat rvec = Mat(rvecs1[image_idx]);
             Mat tvec  = Mat(tvecs1[image_idx]);
             cv::internal::projectPoints(object, projected, rvec, tvec, intrinsicLeft, jacobians);
-            Mat(Mat((imageLeft - projected).t()).reshape(1, 1).t()).copyTo(ekk.rowRange(0, 2 * n_points));
+            Mat pt_diff = imageLeft.reshape(1, n_points*2) -
+                          projected.reshape(1, n_points*2);
+            pt_diff.copyTo(ekk.rowRange(0, 2 * n_points));
             jacobians.colRange(8, 11).copyTo(Jkk.colRange(24 + image_idx * 6, 27 + image_idx * 6).rowRange(0, 2 * n_points));
             jacobians.colRange(11, 14).copyTo(Jkk.colRange(27 + image_idx * 6, 30 + image_idx * 6).rowRange(0, 2 * n_points));
             jacobians.colRange(0, 2).copyTo(Jkk.colRange(0, 2).rowRange(0, 2 * n_points));
@@ -354,7 +356,10 @@ double cv::fisheye::stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayO
             tvec  = Mat(tvecs2[image_idx]);
 
             cv::internal::projectPoints(object, projected, omr, Tr, intrinsicRight, jacobians);
-            Mat(Mat((imageRight - projected).t()).reshape(1, 1).t()).copyTo(ekk.rowRange(2 * n_points, 4 * n_points));
+
+            pt_diff = imageRight.reshape(1, n_points*2) -
+                      projected.reshape(1, n_points*2);
+            pt_diff.copyTo(ekk.rowRange(2 * n_points, 4 * n_points));
             Mat dxrdom = jacobians.colRange(8, 11) * domrdom + jacobians.colRange(11, 14) * dTrdom;
             Mat dxrdT = jacobians.colRange(8, 11) * domrdT + jacobians.colRange(11, 14)* dTrdT;
             Mat dxrdomckk = jacobians.colRange(8, 11) * domrdomckk + jacobians.colRange(11, 14) * dTrdomckk;
@@ -580,7 +585,7 @@ void cv::internal::ComputeExtrinsicRefine(const Mat& imagePoints, const Mat& obj
         Mat jacobians;
         projectPoints(objectPoints, x, rvec, tvec, param, jacobians);
 
-        Mat ex = imagePoints - Mat(x).t();
+        Mat ex = imagePoints - Mat(x);
         ex = ex.reshape(1, 2);
 
         J = jacobians.colRange(8, 14).clone();
@@ -826,7 +831,7 @@ void cv::internal::ComputeJacobians(InputArrayOfArrays objectPoints, InputArrayO
         objectPoints.getMat(image_idx).convertTo(object, CV_64FC3);
         imagePoints.getMat (image_idx).convertTo(image, CV_64FC2);
 
-        bool imT = image.rows < image.cols;
+        bool imT = image.channels() == 1 && image.rows > image.cols;
         Mat om(omc.getMat().col(image_idx)), T(Tc.getMat().col(image_idx));
 
         std::vector<Point2d> x;
@@ -850,8 +855,9 @@ void cv::internal::ComputeJacobians(InputArrayOfArrays objectPoints, InputArrayO
         JJ2(Rect(9 + 6 * image_idx, 0, 6, 9)) = A * B.t();
         JJ2(Rect(0, 9 + 6 * image_idx, 9, 6)) = JJ2(Rect(9 + 6 * image_idx, 0, 6, 9)).t();
 
-        ex3.rowRange(0, 9) += A * exkk.reshape(1, 2 * exkk.rows);
-        ex3.rowRange(9 + 6 * image_idx, 9 + 6 * (image_idx + 1)) = B * exkk.reshape(1, 2 * exkk.rows);
+        Mat exkk_col = exkk.reshape(1, 2 * (int)exkk.total());
+        ex3.rowRange(0, 9) += A * exkk_col;
+        ex3.rowRange(9 + 6 * image_idx, 9 + 6 * (image_idx + 1)) = B *  exkk_col;
 
         if (check_cond)
         {
@@ -891,13 +897,14 @@ void cv::internal::EstimateUncertainties(InputArrayOfArrays objectPoints, InputA
         objectPoints.getMat(image_idx).convertTo(object, CV_64FC3);
         imagePoints.getMat (image_idx).convertTo(image, CV_64FC2);
 
-        bool imT = image.rows < image.cols;
+        bool imT = image.channels() == 1 && image.rows > image.cols;
 
         Mat om(omc.getMat().col(image_idx)), T(Tc.getMat().col(image_idx));
 
         std::vector<Point2d> x;
         projectPoints(object, x, om, T, params, noArray());
         Mat ex_ = (imT ? image.t() : image) - Mat(x);
+        ex_ = ex_.reshape(2, (int)ex_.total());
         ex_.copyTo(ex.rowRange(insert_idx, insert_idx + ex_.rows));
         insert_idx += ex_.rows;
     }

modules/calib/test/test_fisheye.cpp

@@ -206,7 +206,7 @@ TEST_F(fisheyeTest, Homography)
     cv::Mat _objectPoints(objectPoints[0]);
 
     cv::Mat imagePointsNormalized = NormalizePixels(_imagePoints, param).reshape(1).t();
-    _objectPoints = _objectPoints.reshape(1).t();
+    _objectPoints = _objectPoints.reshape(1, (int)_objectPoints.total()).t();
     cv::Mat objectPointsMean, covObjectPoints;
 
     int Np = imagePointsNormalized.cols;

modules/calib/test/test_multiview_calib.cpp

@@ -58,7 +58,7 @@ TEST(multiview_calibration, accuracy) {
 
     const int MAX_SAMPLES = 2000, MAX_FRAMES = 50;
     cv::Mat pattern (board_pattern, true/*copy*/);
-    pattern = pattern.reshape(1).t();
+    pattern = pattern.reshape(1, num_pts).t();
     pattern.row(2) = 2.0; // set approximate depth of object points
     const double ty_min = -2, ty_max = 2, tx_min = -2, tx_max = 2, tz_min = -1, tz_max = 1;
     const double yaw_min = -45, yaw_max = 45, pitch_min = -45, pitch_max = 45, roll_min = -45, roll_max = 45;

modules/core/include/opencv2/core/mat.hpp

@@ -243,6 +243,7 @@ class CV_EXPORTS _InputArray
     bool isUMat() const;
     bool isMatVector() const;
     bool isUMatVector() const;
+    bool isVecVector() const;
     bool isMatx() const;
     bool isVector() const;
     bool isGpuMat() const;
@@ -355,6 +356,9 @@ class CV_EXPORTS _OutputArray : public _InputArray
     UMat& getUMatRef(int i=-1) const;
     cuda::GpuMat& getGpuMatRef() const;
     std::vector<cuda::GpuMat>& getGpuMatVecRef() const;
+    std::vector<Mat>& getMatVecRef() const;
+    std::vector<UMat>& getUMatVecRef() const;
+    template<typename _Tp> std::vector<std::vector<_Tp> >& getVecVecRef() const;
     ogl::Buffer& getOGlBufferRef() const;
     cuda::HostMem& getHostMemRef() const;
     void create(Size sz, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
@@ -602,7 +606,7 @@ struct CV_EXPORTS MatStep
     MatStep& operator = (size_t s);
 
     size_t* p;
-    size_t buf[2];
+    size_t buf[3];
 protected:
     MatStep& operator = (const MatStep&);
 };
@@ -1510,6 +1514,15 @@ class CV_EXPORTS Mat
     */
     void create(const std::vector<int>& sizes, int type);
 
+    /** @brief Creates the matrix of the same size as another array.
+
+    The method is similar to _OutputArray::createSameSize(arr, type),
+    but is applied to Mat.
+    @param arr The other array.
+    @param type New matrix type.
+    */
+    void createSameSize(InputArray arr, int type);
+
     /** @brief Increments the reference counter.
 
     The method increments the reference counter associated with the matrix data. If the matrix header
@@ -2134,6 +2147,7 @@ class CV_EXPORTS Mat
     int dims;
     //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
     int rows, cols;
+    int dummy = 153;
     //! pointer to the data
     uchar* data;
 
@@ -2307,6 +2321,8 @@ template<typename _Tp> class Mat_ : public Mat
     void create(Size _size);
     //! equivalent to Mat::create(_ndims, _sizes, DatType<_Tp>::type)
     void create(int _ndims, const int* _sizes);
+    //! equivalent to Mat::create(arr.ndims, arr.size.p, DatType<_Tp>::type)
+    void createSameSize(InputArray arr);
     //! equivalent to Mat::release()
     void release();
     //! cross-product
@@ -2526,6 +2542,10 @@ class CV_EXPORTS UMat
     void create(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
     void create(const std::vector<int>& sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
 
+    //! allocates new matrix data unless the matrix already has specified size and type.
+    // the size is taken from the specified array.
+    void createSameSize(InputArray arr, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+
     //! increases the reference counter; use with care to avoid memleaks
     void addref();
     //! decreases reference counter;
@@ -2980,7 +3000,6 @@ class CV_EXPORTS SparseMat
 };
 
 
-
 ///////////////////////////////// SparseMat_<_Tp> ////////////////////////////////////
 
 /** @brief Template sparse n-dimensional array class derived from SparseMat