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Open Source Computer Vision Library
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46 lines
1.6 KiB
46 lines
1.6 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html |
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#include "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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TEST(Features2d_SIFT, descriptor_type) |
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{ |
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Mat image = imread(cvtest::findDataFile("features2d/tsukuba.png")); |
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ASSERT_FALSE(image.empty()); |
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Mat gray; |
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cvtColor(image, gray, COLOR_BGR2GRAY); |
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vector<KeyPoint> keypoints; |
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Mat descriptorsFloat, descriptorsUchar; |
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Ptr<SIFT> siftFloat = cv::SIFT::create(0, 3, 0.04, 10, 1.6, CV_32F); |
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siftFloat->detectAndCompute(gray, Mat(), keypoints, descriptorsFloat, false); |
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ASSERT_EQ(descriptorsFloat.type(), CV_32F) << "type mismatch"; |
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Ptr<SIFT> siftUchar = cv::SIFT::create(0, 3, 0.04, 10, 1.6, CV_8U); |
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siftUchar->detectAndCompute(gray, Mat(), keypoints, descriptorsUchar, false); |
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ASSERT_EQ(descriptorsUchar.type(), CV_8U) << "type mismatch"; |
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Mat descriptorsFloat2; |
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descriptorsUchar.assignTo(descriptorsFloat2, CV_32F); |
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Mat diff = descriptorsFloat != descriptorsFloat2; |
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ASSERT_EQ(countNonZero(diff), 0) << "descriptors are not identical"; |
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} |
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TEST(Features2d_SIFT, regression_26139) |
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{ |
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auto extractor = cv::SIFT::create(); |
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cv::Mat1b image{cv::Size{300, 300}, 0}; |
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std::vector<cv::KeyPoint> kps { |
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cv::KeyPoint(154.076813f, 136.160904f, 111.078636f, 216.195618f, 0.00000899323549f, 7) |
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}; |
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cv::Mat descriptors; |
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extractor->compute(image, kps, descriptors); // we expect no memory corruption |
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ASSERT_EQ(descriptors.size(), Size(128, 1)); |
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} |
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}} // namespace
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