// This file is part of OpenCV project. // It is subject to the license terms in the LICENSE file found in the top-level directory // of this distribution and at http://opencv.org/license.html. #include "perf_precomp.hpp" namespace opencv_test { namespace { CV_ENUM(RetrMode, RETR_EXTERNAL, RETR_LIST, RETR_CCOMP, RETR_TREE) CV_ENUM(ApproxMode, CHAIN_APPROX_NONE, CHAIN_APPROX_SIMPLE, CHAIN_APPROX_TC89_L1, CHAIN_APPROX_TC89_KCOS) typedef TestBaseWithParam< tuple > TestFindContours; PERF_TEST_P(TestFindContours, findContours, Combine( Values( szVGA, sz1080p ), // image size RetrMode::all(), // retrieval mode ApproxMode::all(), // approximation method Values( 32, 128 ) // blob count ) ) { Size img_size = get<0>(GetParam()); int retr_mode = get<1>(GetParam()); int approx_method = get<2>(GetParam()); int blob_count = get<3>(GetParam()); RNG rng; Mat img = Mat::zeros(img_size, CV_8UC1); for(int i = 0; i < blob_count; i++ ) { Point center; center.x = (unsigned)rng % (img.cols-2); center.y = (unsigned)rng % (img.rows-2); Size axes; axes.width = ((unsigned)rng % 49 + 2)/2; axes.height = ((unsigned)rng % 49 + 2)/2; double angle = (unsigned)rng % 180; int brightness = (unsigned)rng % 2; // keep the border clear ellipse( img(Rect(1,1,img.cols-2,img.rows-2)), Point(center), Size(axes), angle, 0., 360., Scalar(brightness), -1); } vector< vector > contours; TEST_CYCLE() findContours( img, contours, retr_mode, approx_method ); SANITY_CHECK_NOTHING(); } typedef TestBaseWithParam< tuple > TestFindContoursFF; PERF_TEST_P(TestFindContoursFF, findContours, Combine( Values(szVGA, sz1080p), // image size ApproxMode::all(), // approximation method Values(32, 128) // blob count ) ) { Size img_size = get<0>(GetParam()); int approx_method = get<1>(GetParam()); int blob_count = get<2>(GetParam()); RNG rng; Mat img = Mat::zeros(img_size, CV_32SC1); for (int i = 0; i < blob_count; i++) { Point center; center.x = (unsigned)rng % (img.cols - 2); center.y = (unsigned)rng % (img.rows - 2); Size axes; axes.width = ((unsigned)rng % 49 + 2) / 2; axes.height = ((unsigned)rng % 49 + 2) / 2; double angle = (unsigned)rng % 180; int brightness = (unsigned)rng % 2; // keep the border clear ellipse(img(Rect(1, 1, img.cols - 2, img.rows - 2)), Point(center), Size(axes), angle, 0., 360., Scalar(brightness), -1); } vector< vector > contours; TEST_CYCLE() findContours(img, contours, RETR_FLOODFILL, approx_method); SANITY_CHECK_NOTHING(); } // ============================================================ // findTRUContours performance tests // ============================================================ typedef TestBaseWithParam< tuple > TestFindTRUContours; PERF_TEST_P(TestFindTRUContours, findTRUContours, Combine( Values(sz1080p, sz2160p), // image size Values(128, 512, 2048), // circle count Values(1, 0) // nthreads: 1=single-thread baseline, 0=all available ) ) { Size img_size = get<0>(GetParam()); int num_circles = get<1>(GetParam()); int nthreads = get<2>(GetParam()); RNG rng(12345); Mat img = Mat::zeros(img_size, CV_8UC1); for (int i = 0; i < num_circles; ++i) { Point center(rng.uniform(50, img_size.width - 50), rng.uniform(50, img_size.height - 50)); int radius = rng.uniform(10, 200); circle(img, center, radius, Scalar::all(255), FILLED); } Mat binary; adaptiveThreshold(img, binary, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 11, 0); vector> contours; int prev_nthreads=cv::getNumThreads(); cv::setNumThreads(nthreads); TEST_CYCLE() findContours(binary, contours, RETR_LIST, CHAIN_APPROX_NONE); cv::setNumThreads(prev_nthreads); SANITY_CHECK_NOTHING(); } // Baseline: same image, findContours(RETR_LIST, CHAIN_APPROX_NONE) for direct comparison typedef TestBaseWithParam< tuple > TestFindContoursBaseline; PERF_TEST_P(TestFindContoursBaseline, findContours_baseline_for_TRUCO, Combine( Values(sz1080p, sz2160p), Values(128, 512, 2048) ) ) { Size img_size = get<0>(GetParam()); int num_circles = get<1>(GetParam()); RNG rng(12345); Mat img = Mat::zeros(img_size, CV_8UC1); for (int i = 0; i < num_circles; ++i) { Point center(rng.uniform(50, img_size.width - 50), rng.uniform(50, img_size.height - 50)); int radius = rng.uniform(10, 200); circle(img, center, radius, Scalar::all(255), FILLED); } Mat binary; adaptiveThreshold(img, binary, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 11, 0); vector> contours; vector hierarchy; TEST_CYCLE() findContours(binary, contours, hierarchy, RETR_LIST, CHAIN_APPROX_NONE); SANITY_CHECK_NOTHING(); } } } // namespace