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2c7591c57f
Depends on https://github.com/opencv/opencv/pull/26316 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
85 lines
2.6 KiB
C++
85 lines
2.6 KiB
C++
/*
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* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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*/
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#include "test_precomp.hpp"
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namespace opencv_test { namespace {
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typedef tuple<cv::Size /*imgSize*/, int /*nPts*/, int /*channels*/> FillConvexTestParams;
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class FillConvexTest : public ::testing::TestWithParam<FillConvexTestParams> {};
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TEST_P(FillConvexTest, randomDraw)
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{
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auto p = GetParam();
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Size imgSize = std::get<0>(p);
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int nPts = std::get<1>(p);
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int channels = std::get<2>(p);
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cv::RNG rng = cv::theRNG();
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std::vector<Point> allPts, contour;
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for (int i = 0; i < nPts; i++)
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{
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allPts.push_back(Point(rng() % imgSize.width, rng() % imgSize.height));
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}
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cv::convexHull(allPts, contour);
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Scalar color(rng() % 256, rng() % 256, rng() % 256);
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Mat imgRef(imgSize, CV_MAKE_TYPE(CV_8U, channels), Scalar(0));
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Mat imgFast = imgRef.clone();
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cv::fillConvexPoly(imgRef, contour, color);
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cv::fastcv::fillConvexPoly(imgFast, contour, color);
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double normInf = cvtest::norm(imgRef, imgFast, cv::NORM_INF);
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double normL2 = cvtest::norm(imgRef, imgFast, cv::NORM_L2);
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EXPECT_EQ(normInf, 0);
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EXPECT_EQ(normL2, 0);
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}
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TEST_P(FillConvexTest, circle)
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{
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auto p = GetParam();
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Size imgSize = std::get<0>(p);
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int nPts = std::get<1>(p);
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int channels = std::get<2>(p);
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cv::RNG rng = cv::theRNG();
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float r = std::min(imgSize.width, imgSize.height) / 2 * 0.9f;
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float angle = CV_PI * 2.0f / (float)nPts;
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std::vector<Point> contour;
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for (int i = 0; i < nPts; i++)
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{
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Point2f pt(r * cos((float)i * angle),
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r * sin((float)i * angle));
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contour.push_back({ imgSize.width / 2 + int(pt.x),
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imgSize.height / 2 + int(pt.y)});
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}
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Scalar color(rng() % 256, rng() % 256, rng() % 256);
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Mat imgRef(imgSize, CV_MAKE_TYPE(CV_8U, channels), Scalar(0));
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Mat imgFast = imgRef.clone();
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cv::fillConvexPoly(imgRef, contour, color);
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cv::fastcv::fillConvexPoly(imgFast, contour, color);
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double normInf = cvtest::norm(imgRef, imgFast, cv::NORM_INF);
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double normL2 = cvtest::norm(imgRef, imgFast, cv::NORM_L2);
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EXPECT_EQ(normInf, 0);
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EXPECT_EQ(normL2, 0);
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}
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INSTANTIATE_TEST_CASE_P(FastCV_Extension, FillConvexTest,
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::testing::Combine(testing::Values(Size(640, 480), Size(512, 512), Size(1920, 1080)), // imgSize
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testing::Values(4, 64, 1024), // nPts
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testing::Values(1, 2, 3, 4))); // channels
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}} // namespaces opencv_test, ::
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