/*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. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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" namespace opencv_test { namespace { #ifdef HAVE_OPENCV_XFEATURES2D TEST(SurfFeaturesFinder, CanFindInROIs) { Ptr finder = xfeatures2d::SURF::create(); Mat img = imread(string(cvtest::TS::ptr()->get_data_path()) + "cv/shared/lena.png"); vector rois; rois.push_back(Rect(0, 0, img.cols / 2, img.rows / 2)); rois.push_back(Rect(img.cols / 2, img.rows / 2, img.cols - img.cols / 2, img.rows - img.rows / 2)); // construct mask Mat mask = Mat::zeros(img.size(), CV_8U); for (const Rect &roi : rois) { Mat(mask, roi) = 1; } detail::ImageFeatures roi_features; detail::computeImageFeatures(finder, img, roi_features, mask); int tl_rect_count = 0, br_rect_count = 0, bad_count = 0; for (const auto &keypoint : roi_features.keypoints) { if (rois[0].contains(keypoint.pt)) tl_rect_count++; else if (rois[1].contains(keypoint.pt)) br_rect_count++; else bad_count++; } EXPECT_GT(tl_rect_count, 0); EXPECT_GT(br_rect_count, 0); EXPECT_EQ(bad_count, 0); } #endif // HAVE_OPENCV_XFEATURES2D TEST(ParallelFeaturesFinder, IsSameWithSerial) { Ptr para_finder = ORB::create(); Ptr serial_finder = ORB::create(); Mat img = imread(string(cvtest::TS::ptr()->get_data_path()) + "stitching/a3.png", IMREAD_GRAYSCALE); detail::ImageFeatures serial_features; detail::computeImageFeatures(serial_finder, img, serial_features); vector imgs(50, img); vector para_features(imgs.size()); detail::computeImageFeatures(para_finder, imgs, para_features); // FIXIT This call doesn't use parallel_for_() // results must be the same Mat serial_descriptors; serial_features.descriptors.copyTo(serial_descriptors); for(size_t i = 0; i < para_features.size(); ++i) { SCOPED_TRACE(cv::format("i=%zu", i)); EXPECT_EQ(serial_descriptors.size(), para_features[i].descriptors.size()); #if 0 // FIXIT ORB descriptors are not bit-exact (perhaps due internal parallel_for usage) ASSERT_EQ(0, cv::norm(u_serial_descriptors, para_features[i].descriptors, NORM_L1)) << "serial_size=" << u_serial_descriptors.size() << " par_size=" << para_features[i].descriptors.size() << endl << u_serial_descriptors.getMat(ACCESS_READ) << endl << endl << para_features[i].descriptors.getMat(ACCESS_READ); #endif EXPECT_EQ(serial_features.img_size, para_features[i].img_size); EXPECT_EQ(serial_features.keypoints.size(), para_features[i].keypoints.size()); } } }} // namespace