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1e4d4e0f3e
Add warpAffine and resizeDown APIs in FastCV Extension #3936 - Added warpAffine function to apply affine transformations. 2x3 affine transformations for both CV_8UC1 and CV_8UC3 input 2x2 matrix-based patch extraction for grayscale images, with ROI. - Deprecated resizeDownBy2 and resizeDownBy4 functions. - Introduced resizeDown function to down-scale images using specified scaling factors or dimensions, supporting both single-channel (CV_8UC1) and two-channel (CV_8UC2) images. ### 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
87 lines
2.6 KiB
C++
87 lines
2.6 KiB
C++
/*
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* Copyright (c) 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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TEST(resizeDownBy2, accuracy)
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{
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cv::Mat inputImage = cv::imread(cvtest::findDataFile("cv/shared/box_in_scene.png"), cv::IMREAD_GRAYSCALE);
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cv::Mat resized_image;
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cv::fastcv::resizeDown(inputImage, resized_image, cv::Size(inputImage.cols / 2, inputImage.rows / 2), 0, 0);
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EXPECT_FALSE(resized_image.empty());
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cv::Mat resizedImageOpenCV;
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cv::resize(inputImage, resizedImageOpenCV, cv::Size(inputImage.cols / 2, inputImage.rows / 2), 0, 0, INTER_AREA);
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double maxVal = cv::norm(resized_image, resizedImageOpenCV, cv::NORM_INF);
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CV_Assert(maxVal < 10 && "Difference between images is too high!");
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}
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TEST(resizeDownBy4, accuracy)
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{
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cv::Mat inputImage = cv::imread(cvtest::findDataFile("cv/shared/box_in_scene.png"), cv::IMREAD_GRAYSCALE);
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Size dsize;
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cv::Mat resized_image;
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cv::fastcv::resizeDown(inputImage, resized_image, dsize, 0.25, 0.25);
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EXPECT_FALSE(resized_image.empty());
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cv::Mat resizedImageOpenCV;
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cv::resize(inputImage, resizedImageOpenCV, cv::Size(inputImage.cols / 4, inputImage.rows / 4), 0, 0, INTER_AREA);
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double maxVal = cv::norm(resized_image, resizedImageOpenCV, cv::NORM_INF);
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CV_Assert(maxVal < 10 && "Difference between images is too high!");
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}
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TEST(resizeDownMN, accuracy)
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{
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cv::Mat inputImage = cv::imread(cvtest::findDataFile("cv/cascadeandhog/images/class57.png"), cv::IMREAD_GRAYSCALE);
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cv::Mat resized_image;
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cv::fastcv::resizeDown(inputImage, resized_image, cv::Size(800, 640), 0, 0);
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EXPECT_FALSE(resized_image.empty());
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cv::Mat resizedImageOpenCV;
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cv::resize(inputImage, resizedImageOpenCV, cv::Size(800, 640), 0, 0, INTER_LINEAR);
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double maxVal = cv::norm(resized_image, resizedImageOpenCV, cv::NORM_INF);
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CV_Assert(maxVal < 78 && "Difference between images is too high!");
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}
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TEST(resizeDownInterleaved, accuracy)
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{
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cv::Mat inputImage = cv::Mat::zeros(512, 512, CV_8UC2);
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cv::randu(inputImage, cv::Scalar(0), cv::Scalar(255));
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Size dsize;
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cv::Mat resized_image;
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cv::fastcv::resizeDown(inputImage, resized_image, dsize, 0.500, 0.125);
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EXPECT_FALSE(resized_image.empty());
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cv::Mat resizedImageOpenCV;
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cv::resize(inputImage, resizedImageOpenCV, dsize, 0.500, 0.125, INTER_AREA);
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double maxVal = cv::norm(resized_image, resizedImageOpenCV, cv::NORM_INF);
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CV_Assert(maxVal < 10 && "Difference between images is too high!");
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}
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}} // namespaces opencv_test, ::
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