1
0
mirror of https://github.com/opencv/opencv_contrib.git synced 2025-10-18 17:24:28 +08:00
Files
opencv_contrib/modules/fastcv/test/test_fft.cpp
quic-xuezha 67815e94c8 Merge pull request #3844 from CodeLinaro:xuezha_2ndPost
FastCV Extension code for OpenCV 2ndpost-1 #3844

Depends on: [opencv/opencv#26617](https://github.com/opencv/opencv/pull/26617)
Requires binary from [opencv/opencv_3rdparty#90](https://github.com/opencv/opencv_3rdparty/pull/90)

### 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
2024-12-20 18:13:09 +03:00

69 lines
1.8 KiB
C++

/*
* Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
class FFTExtTest : public ::testing::TestWithParam<cv::Size> {};
TEST_P(FFTExtTest, forward)
{
Size size = GetParam();
RNG& rng = cv::theRNG();
Mat src(size, CV_8UC1);
cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(256));
Mat srcFloat;
src.convertTo(srcFloat, CV_32F);
Mat dst, ref;
cv::fastcv::FFT(src, dst);
cv::dft(srcFloat, ref, DFT_COMPLEX_OUTPUT);
double normInf = cvtest::norm(dst, ref, cv::NORM_INF);
double normL2 = cvtest::norm(dst, ref, cv::NORM_L2) / dst.size().area();
EXPECT_LT(normInf, 19.1); // for 512x512 case
EXPECT_LT(normL2, 18.0 / 256.0 );
}
TEST_P(FFTExtTest, inverse)
{
Size size = GetParam();
RNG& rng = cv::theRNG();
Mat src(size, CV_8UC1);
cvtest::randUni(rng, src, Scalar::all(0), Scalar::all(256));
Mat srcFloat;
src.convertTo(srcFloat, CV_32F);
Mat fwd, back;
cv::fastcv::FFT(src, fwd);
cv::fastcv::IFFT(fwd, back);
Mat backFloat;
back.convertTo(backFloat, CV_32F);
Mat fwdRef, backRef;
cv::dft(srcFloat, fwdRef, DFT_COMPLEX_OUTPUT);
cv::idft(fwdRef, backRef, DFT_REAL_OUTPUT);
backRef *= 1./(src.size().area());
double normInf = cvtest::norm(backFloat, backRef, cv::NORM_INF);
double normL2 = cvtest::norm(backFloat, backRef, cv::NORM_L2) / src.size().area();
EXPECT_LT(normInf, 9.16e-05);
EXPECT_LT(normL2, 1.228e-06);
}
INSTANTIATE_TEST_CASE_P(FastCV_Extension, FFTExtTest, ::testing::Values(Size(8, 8), Size(128, 128), Size(32, 256), Size(512, 512),
Size(32, 1), Size(512, 1)));
}} // namespaces opencv_test, ::