/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" #ifdef HAVE_CUDA using namespace cvtest; /////////////////////////////////////////////////////////////////////////////////////////////////////// // HoughLines PARAM_TEST_CASE(HoughLines, cv::gpu::DeviceInfo, cv::Size, UseRoi) { static void generateLines(cv::Mat& img) { img.setTo(cv::Scalar::all(0)); cv::line(img, cv::Point(20, 0), cv::Point(20, img.rows), cv::Scalar::all(255)); cv::line(img, cv::Point(0, 50), cv::Point(img.cols, 50), cv::Scalar::all(255)); cv::line(img, cv::Point(0, 0), cv::Point(img.cols, img.rows), cv::Scalar::all(255)); cv::line(img, cv::Point(img.cols, 0), cv::Point(0, img.rows), cv::Scalar::all(255)); } static void drawLines(cv::Mat& dst, const std::vector& lines) { dst.setTo(cv::Scalar::all(0)); for (size_t i = 0; i < lines.size(); ++i) { float rho = lines[i][0], theta = lines[i][1]; cv::Point pt1, pt2; double a = std::cos(theta), b = std::sin(theta); double x0 = a*rho, y0 = b*rho; pt1.x = cvRound(x0 + 1000*(-b)); pt1.y = cvRound(y0 + 1000*(a)); pt2.x = cvRound(x0 - 1000*(-b)); pt2.y = cvRound(y0 - 1000*(a)); cv::line(dst, pt1, pt2, cv::Scalar::all(255)); } } }; GPU_TEST_P(HoughLines, Accuracy) { const cv::gpu::DeviceInfo devInfo = GET_PARAM(0); cv::gpu::setDevice(devInfo.deviceID()); const cv::Size size = GET_PARAM(1); const bool useRoi = GET_PARAM(2); const float rho = 1.0f; const float theta = (float) (1.5 * CV_PI / 180.0); const int threshold = 100; cv::Mat src(size, CV_8UC1); generateLines(src); cv::gpu::GpuMat d_lines; cv::gpu::HoughLines(loadMat(src, useRoi), d_lines, rho, theta, threshold); std::vector lines; cv::gpu::HoughLinesDownload(d_lines, lines); cv::Mat dst(size, CV_8UC1); drawLines(dst, lines); ASSERT_MAT_NEAR(src, dst, 0.0); } INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HoughLines, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, WHOLE_SUBMAT)); /////////////////////////////////////////////////////////////////////////////////////////////////////// // HoughCircles PARAM_TEST_CASE(HoughCircles, cv::gpu::DeviceInfo, cv::Size, UseRoi) { static void drawCircles(cv::Mat& dst, const std::vector& circles, bool fill) { dst.setTo(cv::Scalar::all(0)); for (size_t i = 0; i < circles.size(); ++i) cv::circle(dst, cv::Point2f(circles[i][0], circles[i][1]), (int)circles[i][2], cv::Scalar::all(255), fill ? -1 : 1); } }; GPU_TEST_P(HoughCircles, Accuracy) { const cv::gpu::DeviceInfo devInfo = GET_PARAM(0); cv::gpu::setDevice(devInfo.deviceID()); const cv::Size size = GET_PARAM(1); const bool useRoi = GET_PARAM(2); const float dp = 2.0f; const float minDist = 0.0f; const int minRadius = 10; const int maxRadius = 20; const int cannyThreshold = 100; const int votesThreshold = 20; std::vector circles_gold(4); circles_gold[0] = cv::Vec3i(20, 20, minRadius); circles_gold[1] = cv::Vec3i(90, 87, minRadius + 3); circles_gold[2] = cv::Vec3i(30, 70, minRadius + 8); circles_gold[3] = cv::Vec3i(80, 10, maxRadius); cv::Mat src(size, CV_8UC1); drawCircles(src, circles_gold, true); cv::gpu::GpuMat d_circles; cv::gpu::HoughCircles(loadMat(src, useRoi), d_circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius); std::vector circles; cv::gpu::HoughCirclesDownload(d_circles, circles); ASSERT_FALSE(circles.empty()); for (size_t i = 0; i < circles.size(); ++i) { cv::Vec3f cur = circles[i]; bool found = false; for (size_t j = 0; j < circles_gold.size(); ++j) { cv::Vec3f gold = circles_gold[j]; if (std::fabs(cur[0] - gold[0]) < 5 && std::fabs(cur[1] - gold[1]) < 5 && std::fabs(cur[2] - gold[2]) < 5) { found = true; break; } } ASSERT_TRUE(found); } } INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HoughCircles, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, WHOLE_SUBMAT)); /////////////////////////////////////////////////////////////////////////////////////////////////////// // GeneralizedHough #if !defined(__GNUC__) || (__GNUC__ * 10 + __GNUC_MINOR__ != 47) PARAM_TEST_CASE(GeneralizedHough, cv::gpu::DeviceInfo, UseRoi) { }; GPU_TEST_P(GeneralizedHough, POSITION) { const cv::gpu::DeviceInfo devInfo = GET_PARAM(0); cv::gpu::setDevice(devInfo.deviceID()); const bool useRoi = GET_PARAM(1); cv::Mat templ = readImage("../cv/shared/templ.png", cv::IMREAD_GRAYSCALE); ASSERT_FALSE(templ.empty()); cv::Point templCenter(templ.cols / 2, templ.rows / 2); const size_t gold_count = 3; cv::Point pos_gold[gold_count]; pos_gold[0] = cv::Point(templCenter.x + 10, templCenter.y + 10); pos_gold[1] = cv::Point(2 * templCenter.x + 40, templCenter.y + 10); pos_gold[2] = cv::Point(2 * templCenter.x + 40, 2 * templCenter.y + 40); cv::Mat image(templ.rows * 3, templ.cols * 3, CV_8UC1, cv::Scalar::all(0)); for (size_t i = 0; i < gold_count; ++i) { cv::Rect rec(pos_gold[i].x - templCenter.x, pos_gold[i].y - templCenter.y, templ.cols, templ.rows); cv::Mat imageROI = image(rec); templ.copyTo(imageROI); } cv::Ptr hough = cv::gpu::GeneralizedHough_GPU::create(cv::GHT_POSITION); hough->set("votesThreshold", 200); hough->setTemplate(loadMat(templ, useRoi)); cv::gpu::GpuMat d_pos; hough->detect(loadMat(image, useRoi), d_pos); std::vector pos; hough->download(d_pos, pos); ASSERT_EQ(gold_count, pos.size()); for (size_t i = 0; i < gold_count; ++i) { cv::Point gold = pos_gold[i]; bool found = false; for (size_t j = 0; j < pos.size(); ++j) { cv::Point2f p(pos[j][0], pos[j][1]); if (::fabs(p.x - gold.x) < 2 && ::fabs(p.y - gold.y) < 2) { found = true; break; } } ASSERT_TRUE(found); } } INSTANTIATE_TEST_CASE_P(GPU_ImgProc, GeneralizedHough, testing::Combine( ALL_DEVICES, WHOLE_SUBMAT)); #endif #endif // HAVE_CUDA