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FastCV extension 3rd Post #3891 Adding FastCV extensions for merge, split, gemm and arithm APIs add, subtract ### 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
173 lines
5.8 KiB
C++
173 lines
5.8 KiB
C++
/*
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* Copyright (c) 2024-2025 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 std::tuple<bool /*useFloat*/, int /*nLevels*/, bool /*scaleBy2*/> PyramidTestParams;
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class PyramidTest : public ::testing::TestWithParam<PyramidTestParams> { };
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TEST_P(PyramidTest, accuracy)
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{
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auto par = GetParam();
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bool useFloat = std::get<0>(par);
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int nLevels = std::get<1>(par);
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bool scaleBy2 = std::get<2>(par);
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cv::Mat src = imread(cvtest::findDataFile("cv/shared/baboon.png"), cv::IMREAD_GRAYSCALE);
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if (useFloat)
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{
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cv::Mat f;
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src.convertTo(f, CV_32F);
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src = f;
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}
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std::vector<cv::Mat> pyr;
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cv::fastcv::buildPyramid(src, pyr, nLevels, scaleBy2);
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ASSERT_EQ(pyr.size(), (size_t)nLevels);
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std::vector<cv::Mat> refPyr;
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if (scaleBy2)
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{
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cv::buildPyramid(src, refPyr, nLevels - 1);
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}
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else // ORB downscaling
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{
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for (int i = 0; i < nLevels; i++)
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{
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// we don't know how exactly the bit-accurate size is calculated
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cv::Mat level;
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cv::resize(src, level, pyr[i].size(), 0, 0, cv::INTER_AREA);
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refPyr.push_back(level);
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}
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}
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for (int i = 0; i < nLevels; i++)
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{
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cv::Mat ref = refPyr[i];
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cv::Mat m = pyr[i];
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ASSERT_EQ(m.size(), ref.size());
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double l2diff = cv::norm(m, ref, cv::NORM_L2);
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double linfdiff = cv::norm(m, ref, cv::NORM_INF);
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double l2Thresh = scaleBy2 ? 178.0 : 5216.0;
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double linfThresh = scaleBy2 ? 16.0 : 116.0;
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EXPECT_LE(l2diff, l2Thresh);
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EXPECT_LE(linfdiff, linfThresh);
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}
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if (cvtest::debugLevel > 0)
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{
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for (int i = 0; i < nLevels; i++)
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{
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char tchar = useFloat ? 'f' : 'i';
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std::string scaleStr = scaleBy2 ? "x2" : "xORB";
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cv::imwrite(cv::format("pyr_diff_%c_%d_%s_l%d.png", tchar, nLevels, scaleStr.c_str(), i), cv::abs(pyr[i] - refPyr[i]));
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}
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}
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}
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INSTANTIATE_TEST_CASE_P(FastCV_Extension, PyramidTest,
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// useFloat, nLevels, scaleBy2
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::testing::Values(
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PyramidTestParams { true, 2, true}, PyramidTestParams { true, 3, true}, PyramidTestParams { true, 4, true},
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PyramidTestParams {false, 2, true}, PyramidTestParams {false, 3, true}, PyramidTestParams {false, 4, true},
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PyramidTestParams {false, 2, false}, PyramidTestParams {false, 3, false}, PyramidTestParams {false, 4, false}
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));
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typedef std::tuple<MatType, size_t> SobelPyramidTestParams;
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class SobelPyramidTest : public ::testing::TestWithParam<SobelPyramidTestParams> {};
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TEST_P(SobelPyramidTest, accuracy)
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{
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auto p = GetParam();
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int type = std::get<0>(p);
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size_t nLevels = std::get<1>(p);
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// NOTE: test files should be manually loaded to folder on a device, for example like this:
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// adb push fastcv/misc/bilateral_recursive/ /sdcard/testdata/fastcv/bilateral/
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cv::Mat src = imread(cvtest::findDataFile("cv/shared/baboon.png"), cv::IMREAD_GRAYSCALE);
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std::vector<cv::Mat> pyr;
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cv::fastcv::buildPyramid(src, pyr, nLevels);
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std::vector<cv::Mat> pyrDx, pyrDy;
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cv::fastcv::sobelPyramid(pyr, pyrDx, pyrDy, type);
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ASSERT_EQ(pyrDx.size(), nLevels);
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ASSERT_EQ(pyrDy.size(), nLevels);
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for (size_t i = 0; i < nLevels; i++)
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{
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ASSERT_EQ(pyrDx[i].type(), type);
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ASSERT_EQ(pyrDx[i].size(), pyr[i].size());
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ASSERT_EQ(pyrDy[i].type(), type);
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ASSERT_EQ(pyrDy[i].size(), pyr[i].size());
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}
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std::vector<cv::Mat> refPyrDx(nLevels), refPyrDy(nLevels);
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for (size_t i = 0; i < nLevels; i++)
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{
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int stype = (type == CV_8S) ? CV_16S : type;
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cv::Mat dx, dy;
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cv::Sobel(pyr[i], dx, stype, 1, 0);
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cv::Sobel(pyr[i], dy, stype, 0, 1);
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dx.convertTo(refPyrDx[i], type, 1.0/8.0, 0.0);
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dy.convertTo(refPyrDy[i], type, 1.0/8.0, 0.0);
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}
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for (size_t i = 0; i < nLevels; i++)
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{
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cv::Mat ref, dst;
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double normInf, normL2;
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cv::Rect roi(1, 1, pyr[i].cols - 2, pyr[i].rows - 2);
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ref = refPyrDx[i](roi);
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dst = pyrDx[i](roi);
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normInf = cvtest::norm(dst, ref, cv::NORM_INF);
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normL2 = cvtest::norm(dst, ref, cv::NORM_L2) / dst.total();
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EXPECT_LE(normInf, 76.1);
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EXPECT_LT(normL2, 0.4);
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ref = refPyrDy[i](roi);
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dst = pyrDy[i](roi);
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normInf = cvtest::norm(dst, ref, cv::NORM_INF);
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normL2 = cvtest::norm(dst, ref, cv::NORM_L2) / dst.total();
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EXPECT_LE(normInf, 66.6);
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EXPECT_LT(normL2, 0.4);
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}
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if (cvtest::debugLevel > 0)
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{
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std::map<int, std::string> typeToString =
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{
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{CV_8U, "8u"}, {CV_8S, "8s"}, {CV_16U, "16u"}, {CV_16S, "16s"},
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{CV_32S, "32s"}, {CV_32F, "32f"}, {CV_64F, "64f"}, {CV_16F, "16f"},
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};
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for (size_t i = 0; i < nLevels; i++)
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{
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cv::imwrite(cv::format("pyr_l%zu.png", i), pyr[i]);
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cv::imwrite(cv::format("pyr_sobel_x_t%s_l%zu.png", typeToString.at(type).c_str(), i), pyrDx[i] + 128);
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cv::imwrite(cv::format("pyr_sobel_y_t%s_l%zu.png", typeToString.at(type).c_str(), i), pyrDy[i] + 128);
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cv::imwrite(cv::format("ref_pyr_sobel_x_t%s_l%zu.png", typeToString.at(type).c_str(), i), refPyrDx[i] + 128);
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cv::imwrite(cv::format("ref_pyr_sobel_y_t%s_l%zu.png", typeToString.at(type).c_str(), i), refPyrDy[i] + 128);
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}
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}
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}
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INSTANTIATE_TEST_CASE_P(FastCV_Extension, SobelPyramidTest, ::testing::Combine(
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::testing::Values(CV_8S, CV_16S, CV_32F), // depth
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::testing::Values(3, 6))); // nLevels
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}} // namespaces opencv_test, ::
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