case HALF_SIZE:\r
if (i > map_x.cols*0.25 && i < map_x.cols*0.75 && j > map_x.rows*0.25 && j < map_x.rows*0.75)\r
{\r
- map_x.at<float>(j,i) = 2 * (i - map_x.cols * 0.25) + 0.5;\r
- map_y.at<float>(j,i) = 2 * (j - map_x.rows * 0.25) + 0.5;\r
+ map_x.at<float>(j,i) = 2.f * (i - map_x.cols * 0.25f) + 0.5f;\r
+ map_y.at<float>(j,i) = 2.f * (j - map_x.rows * 0.25f) + 0.5f;\r
}\r
else\r
{\r
- map_x.at<float>(j,i) = 0;\r
- map_y.at<float>(j,i) = 0;\r
+ map_x.at<float>(j,i) = 0.f;\r
+ map_y.at<float>(j,i) = 0.f;\r
}\r
break;\r
case UPSIDE_DOWN:\r
- map_x.at<float>(j,i) = i;\r
- map_y.at<float>(j,i) = map_x.rows - j;\r
+ map_x.at<float>(j,i) = static_cast<float>(i);\r
+ map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);\r
break;\r
case REFLECTION_X:\r
- map_x.at<float>(j,i) = map_x.cols - i;\r
- map_y.at<float>(j,i) = j;\r
+ map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);\r
+ map_y.at<float>(j,i) = static_cast<float>(j);\r
break;\r
case REFLECTION_BOTH:\r
- map_x.at<float>(j,i) = map_x.cols - i;\r
- map_y.at<float>(j,i) = map_x.rows - j;\r
+ map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);\r
+ map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);\r
break;\r
} // end of switch\r
}\r
PERF_TEST_P(Sz_Depth_Cn_Inter_Border_Mode, ImgProc_Remap, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),\r
ALL_BORDER_MODES,\r
ALL_REMAP_MODES))\r
PERF_TEST_P(Sz_Depth_Cn_Inter_Scale, ImgProc_Resize, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
ALL_INTERPOLATIONS,\r
Values(0.5, 0.3, 2.0)))\r
{\r
PERF_TEST_P(Sz_Depth_Cn_Scale, ImgProc_ResizeArea, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(0.2, 0.1, 0.05)))\r
{\r
declare.time(1.0);\r
PERF_TEST_P(Sz_Depth_Cn_Inter_Border, ImgProc_WarpAffine, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),\r
ALL_BORDER_MODES))\r
{\r
PERF_TEST_P(Sz_Depth_Cn_Inter_Border, ImgProc_WarpPerspective, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),\r
ALL_BORDER_MODES))\r
{\r
PERF_TEST_P(Sz_Depth_Cn_Border, ImgProc_CopyMakeBorder, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
ALL_BORDER_MODES))\r
{\r
cv::Size size = GET_PARAM(0);\r
//////////////////////////////////////////////////////////////////////\r
// BlendLinear\r
\r
-PERF_TEST_P(Sz_Depth_Cn, ImgProc_BlendLinear, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_32F), Values(1, 3, 4)))\r
+PERF_TEST_P(Sz_Depth_Cn, ImgProc_BlendLinear, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_32F), GPU_CHANNELS_1_3_4))\r
{\r
cv::Size size = GET_PARAM(0);\r
int depth = GET_PARAM(1);\r
PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate8U, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(cv::Size(5, 5), cv::Size(16, 16), cv::Size(30, 30)),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
ALL_TEMPLATE_METHODS))\r
{\r
cv::Size size = GET_PARAM(0);\r
PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate32F, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(cv::Size(5, 5), cv::Size(16, 16), cv::Size(30, 30)),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))))\r
{\r
cv::Size size = GET_PARAM(0);\r
PERF_TEST_P(Sz_Depth_Cn_Inter, ImgProc_Rotate, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4),\r
+ GPU_CHANNELS_1_3_4,\r
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC))))\r
{\r
cv::Size size = GET_PARAM(0);\r
PERF_TEST_P(Sz_Depth_Cn, ImgProc_PyrDown, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4)))\r
+ GPU_CHANNELS_1_3_4))\r
{\r
cv::Size size = GET_PARAM(0);\r
int depth = GET_PARAM(1);\r
PERF_TEST_P(Sz_Depth_Cn, ImgProc_PyrUp, Combine(\r
GPU_TYPICAL_MAT_SIZES,\r
Values(CV_8U, CV_16U, CV_32F),\r
- Values(1, 3, 4)))\r
+ GPU_CHANNELS_1_3_4))\r
{\r
cv::Size size = GET_PARAM(0);\r
int depth = GET_PARAM(1);\r
//////////////////////////////////////////////////////////////////////\r
// ImagePyramidBuild\r
\r
-PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidBuild, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), Values(1, 3, 4)))\r
+PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidBuild, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), GPU_CHANNELS_1_3_4))\r
{\r
cv::Size size = GET_PARAM(0);\r
int depth = GET_PARAM(1);\r
//////////////////////////////////////////////////////////////////////\r
// ImagePyramidGetLayer\r
\r
-PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidGetLayer, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), Values(1, 3, 4)))\r
+PERF_TEST_P(Sz_Depth_Cn, ImgProc_ImagePyramidGetLayer, Combine(GPU_TYPICAL_MAT_SIZES, Values(CV_8U, CV_16U, CV_32F), GPU_CHANNELS_1_3_4))\r
{\r
cv::Size size = GET_PARAM(0);\r
int depth = GET_PARAM(1);\r
//////////////////////////////////////////////////////////////////////\r
// HoughLines\r
\r
-DEF_PARAM_TEST(Sz_DoSort, cv::Size, bool);\r
-\r
-PERF_TEST_P(Sz_DoSort, ImgProc_HoughLines, Combine(GPU_TYPICAL_MAT_SIZES, Bool()))\r
+PERF_TEST_P(Sz, ImgProc_HoughLines, GPU_TYPICAL_MAT_SIZES)\r
{\r
declare.time(30.0);\r
\r
- const cv::Size size = GET_PARAM(0);\r
- const bool doSort = GET_PARAM(1);\r
+ const cv::Size size = GetParam();\r
\r
const float rho = 1.0f;\r
- const float theta = CV_PI / 180.0f;\r
+ const float theta = static_cast<float>(CV_PI / 180.0);\r
const int threshold = 300;\r
\r
cv::RNG rng(123456789);\r
\r
cv::Mat src(size, CV_8UC1, cv::Scalar::all(0));\r
\r
- const int numLines = rng.uniform(500, 2000);\r
+ const int numLines = rng.uniform(100, 300);\r
for (int i = 0; i < numLines; ++i)\r
{\r
cv::Point p1(rng.uniform(0, src.cols), rng.uniform(0, src.rows));\r
{\r
cv::gpu::GpuMat d_src(src);\r
cv::gpu::GpuMat d_lines;\r
- cv::gpu::GpuMat d_accum;\r
- cv::gpu::GpuMat d_buf;\r
+ cv::gpu::HoughLinesBuf d_buf;\r
\r
- cv::gpu::HoughLines(d_src, d_lines, d_accum, d_buf, rho, theta, threshold, doSort);\r
+ cv::gpu::HoughLines(d_src, d_lines, d_buf, rho, theta, threshold);\r
\r
TEST_CYCLE()\r
{\r
- cv::gpu::HoughLines(d_src, d_lines, d_accum, d_buf, rho, theta, threshold, doSort);\r
+ cv::gpu::HoughLines(d_src, d_lines, d_buf, rho, theta, threshold);\r
}\r
}\r
else\r
}\r
}\r
\r
+//////////////////////////////////////////////////////////////////////\r
+// HoughCircles\r
+\r
+DEF_PARAM_TEST(Sz_Dp_MinDist, cv::Size, float, float);\r
+\r
+PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles, Combine(GPU_TYPICAL_MAT_SIZES, Values(1.0f, 2.0f, 4.0f), Values(1.0f, 10.0f)))\r
+{\r
+ declare.time(30.0);\r
+\r
+ const cv::Size size = GET_PARAM(0);\r
+ const float dp = GET_PARAM(1);\r
+ const float minDist = GET_PARAM(2);\r
+\r
+ const int minRadius = 10;\r
+ const int maxRadius = 30;\r
+ const int cannyThreshold = 100;\r
+ const int votesThreshold = 15;\r
+\r
+ cv::RNG rng(123456789);\r
+\r
+ cv::Mat src(size, CV_8UC1, cv::Scalar::all(0));\r
+\r
+ const int numCircles = rng.uniform(50, 100);\r
+ for (int i = 0; i < numCircles; ++i)\r
+ {\r
+ cv::Point center(rng.uniform(0, src.cols), rng.uniform(0, src.rows));\r
+ const int radius = rng.uniform(minRadius, maxRadius + 1);\r
+\r
+ cv::circle(src, center, radius, cv::Scalar::all(255), -1);\r
+ }\r
+\r
+ if (runOnGpu)\r
+ {\r
+ cv::gpu::GpuMat d_src(src);\r
+ cv::gpu::GpuMat d_circles;\r
+ cv::gpu::HoughCirclesBuf d_buf;\r
+\r
+ cv::gpu::HoughCircles(d_src, d_circles, d_buf, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);\r
+\r
+ TEST_CYCLE()\r
+ {\r
+ cv::gpu::HoughCircles(d_src, d_circles, d_buf, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);\r
+ }\r
+ }\r
+ else\r
+ {\r
+ std::vector<cv::Vec3f> circles;\r
+\r
+ cv::HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);\r
+\r
+ TEST_CYCLE()\r
+ {\r
+ cv::HoughCircles(src, circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius);\r
+ }\r
+ }\r
+}\r
+\r
+//////////////////////////////////////////////////////////////////////\r
+// GeneralizedHough\r
+\r
+CV_FLAGS(GHMethod, cv::GHT_POSITION, cv::GHT_SCALE, cv::GHT_ROTATION);\r
+\r
+DEF_PARAM_TEST(Method_Sz, GHMethod, cv::Size);\r
+\r
+PERF_TEST_P(Method_Sz, GeneralizedHough, Combine(\r
+ Values(GHMethod(cv::GHT_POSITION), GHMethod(cv::GHT_POSITION | cv::GHT_SCALE), GHMethod(cv::GHT_POSITION | cv::GHT_ROTATION), GHMethod(cv::GHT_POSITION | cv::GHT_SCALE | cv::GHT_ROTATION)),\r
+ GPU_TYPICAL_MAT_SIZES))\r
+{\r
+ declare.time(10);\r
+\r
+ const int method = GET_PARAM(0);\r
+ const cv::Size imageSize = GET_PARAM(1);\r
+\r
+ const cv::Mat templ = readImage("cv/shared/templ.png", cv::IMREAD_GRAYSCALE);\r
+ ASSERT_FALSE(templ.empty());\r
+\r
+ cv::Mat image(imageSize, CV_8UC1, cv::Scalar::all(0));\r
+\r
+ cv::RNG rng(123456789);\r
+ const int objCount = rng.uniform(5, 15);\r
+ for (int i = 0; i < objCount; ++i)\r
+ {\r
+ double scale = rng.uniform(0.7, 1.3);\r
+ bool rotate = rng.uniform(0, 2);\r
+\r
+ cv::Mat obj;\r
+ cv::resize(templ, obj, cv::Size(), scale, scale);\r
+ if (rotate)\r
+ obj = obj.t();\r
+\r
+ cv::Point pos;\r
+\r
+ pos.x = rng.uniform(0, image.cols - obj.cols);\r
+ pos.y = rng.uniform(0, image.rows - obj.rows);\r
+\r
+ cv::Mat roi = image(cv::Rect(pos, obj.size()));\r
+ cv::add(roi, obj, roi);\r
+ }\r
+\r
+ cv::Mat edges;\r
+ cv::Canny(image, edges, 50, 100);\r
+\r
+ cv::Mat dx, dy;\r
+ cv::Sobel(image, dx, CV_32F, 1, 0);\r
+ cv::Sobel(image, dy, CV_32F, 0, 1);\r
+\r
+ if (runOnGpu)\r
+ {\r
+ cv::gpu::GpuMat d_edges(edges);\r
+ cv::gpu::GpuMat d_dx(dx);\r
+ cv::gpu::GpuMat d_dy(dy);\r
+ cv::gpu::GpuMat d_position;\r
+\r
+ cv::Ptr<cv::gpu::GeneralizedHough_GPU> d_hough = cv::gpu::GeneralizedHough_GPU::create(method);\r
+ if (method & cv::GHT_ROTATION)\r
+ {\r
+ d_hough->set("maxAngle", 90.0);\r
+ d_hough->set("angleStep", 2.0);\r
+ }\r
+\r
+ d_hough->setTemplate(cv::gpu::GpuMat(templ));\r
+\r
+ d_hough->detect(d_edges, d_dx, d_dy, d_position);\r
+\r
+ TEST_CYCLE()\r
+ {\r
+ d_hough->detect(d_edges, d_dx, d_dy, d_position);\r
+ }\r
+ }\r
+ else\r
+ {\r
+ cv::Mat positions;\r
+\r
+ cv::Ptr<cv::GeneralizedHough> hough = cv::GeneralizedHough::create(method);\r
+ if (method & cv::GHT_ROTATION)\r
+ {\r
+ hough->set("maxAngle", 90.0);\r
+ hough->set("angleStep", 2.0);\r
+ }\r
+\r
+ hough->setTemplate(templ);\r
+\r
+ hough->detect(edges, dx, dy, positions);\r
+\r
+ TEST_CYCLE()\r
+ {\r
+ hough->detect(edges, dx, dy, positions);\r
+ }\r
+ }\r
+}\r
+\r
} // namespace\r
projects / profile / ivi / opencv.git / blobdiff