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Merge pull request #26379 from cdcseacave:jxl_codec
Add jxl (JPEG XL) codec support #26379 ### Pull Request Readiness Checklist Related CI and Docker changes: - https://github.com/opencv/ci-gha-workflow/pull/190 - https://github.com/opencv-infrastructure/opencv-gha-dockerfile/pull/44 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 - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work https://github.com/opencv/opencv/issues/20178 - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
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// 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
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// directory 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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#ifdef HAVE_JPEGXL
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typedef tuple<perf::MatType, int> MatType_and_Distance;
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typedef testing::TestWithParam<MatType_and_Distance> Imgcodecs_JpegXL_MatType;
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TEST_P(Imgcodecs_JpegXL_MatType, write_read)
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{
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const int matType = get<0>(GetParam());
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const int distanceParam = get<1>(GetParam());
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cv::Scalar col;
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// Jpeg XL is lossy compression.
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// There may be small differences in decoding results by environments.
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double th;
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switch( CV_MAT_DEPTH(matType) )
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{
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case CV_16U:
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col = cv::Scalar(124 * 256, 76 * 256, 42 * 256, 192 * 256 );
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th = 656; // = 65535 / 100;
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break;
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case CV_32F:
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col = cv::Scalar(0.486, 0.298, 0.165, 0.75);
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th = 1.0 / 100.0;
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break;
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default:
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case CV_8U:
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col = cv::Scalar(124, 76, 42, 192);
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th = 3; // = 255 / 100 (1%);
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break;
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}
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// If increasing distanceParam, threshold should be increased.
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th *= (distanceParam >= 25) ? 5 : ( distanceParam > 2 ) ? 3 : (distanceParam == 2) ? 2: 1;
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bool ret = false;
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string tmp_fname = cv::tempfile(".jxl");
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Mat img_org(320, 480, matType, col);
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vector<int> param;
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param.push_back(IMWRITE_JPEGXL_DISTANCE);
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param.push_back(distanceParam);
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EXPECT_NO_THROW(ret = imwrite(tmp_fname, img_org, param));
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EXPECT_TRUE(ret);
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Mat img_decoded;
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EXPECT_NO_THROW(img_decoded = imread(tmp_fname, IMREAD_UNCHANGED));
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EXPECT_FALSE(img_decoded.empty());
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EXPECT_LE(cvtest::norm(img_org, img_decoded, NORM_INF), th);
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EXPECT_EQ(0, remove(tmp_fname.c_str()));
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}
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TEST_P(Imgcodecs_JpegXL_MatType, encode_decode)
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{
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const int matType = get<0>(GetParam());
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const int distanceParam = get<1>(GetParam());
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cv::Scalar col;
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// Jpeg XL is lossy compression.
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// There may be small differences in decoding results by environments.
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double th;
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// If alpha=0, libjxl modify color channels(BGR). So do not set it.
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switch( CV_MAT_DEPTH(matType) )
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{
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case CV_16U:
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col = cv::Scalar(124 * 256, 76 * 256, 42 * 256, 192 * 256 );
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th = 656; // = 65535 / 100;
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break;
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case CV_32F:
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col = cv::Scalar(0.486, 0.298, 0.165, 0.75);
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th = 1.0 / 100.0;
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break;
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default:
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case CV_8U:
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col = cv::Scalar(124, 76, 42, 192);
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th = 3; // = 255 / 100 (1%);
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break;
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}
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// If increasing distanceParam, threshold should be increased.
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th *= (distanceParam >= 25) ? 5 : ( distanceParam > 2 ) ? 3 : (distanceParam == 2) ? 2: 1;
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bool ret = false;
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vector<uchar> buff;
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Mat img_org(320, 480, matType, col);
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vector<int> param;
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param.push_back(IMWRITE_JPEGXL_DISTANCE);
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param.push_back(distanceParam);
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EXPECT_NO_THROW(ret = imencode(".jxl", img_org, buff, param));
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EXPECT_TRUE(ret);
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Mat img_decoded;
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EXPECT_NO_THROW(img_decoded = imdecode(buff, IMREAD_UNCHANGED));
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EXPECT_FALSE(img_decoded.empty());
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EXPECT_LE(cvtest::norm(img_org, img_decoded, NORM_INF), th);
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}
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INSTANTIATE_TEST_CASE_P(
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/**/,
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Imgcodecs_JpegXL_MatType,
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testing::Combine(
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testing::Values(
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CV_8UC1, CV_8UC3, CV_8UC4,
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CV_16UC1, CV_16UC3, CV_16UC4,
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CV_32FC1, CV_32FC3, CV_32FC4
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),
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testing::Values( // Distance
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0, // Lossless
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1, // Default
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3, // Recomended Lossy Max
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25 // Specification Max
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)
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) );
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typedef tuple<int, int> Effort_and_Decoding_speed;
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typedef testing::TestWithParam<Effort_and_Decoding_speed> Imgcodecs_JpegXL_Effort_DecodingSpeed;
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TEST_P(Imgcodecs_JpegXL_Effort_DecodingSpeed, encode_decode)
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{
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const int effort = get<0>(GetParam());
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const int speed = get<1>(GetParam());
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cv::Scalar col = cv::Scalar(124,76,42);
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// Jpeg XL is lossy compression.
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// There may be small differences in decoding results by environments.
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double th = 3; // = 255 / 100 (1%);
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bool ret = false;
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vector<uchar> buff;
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Mat img_org(320, 480, CV_8UC3, col);
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vector<int> param;
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param.push_back(IMWRITE_JPEGXL_EFFORT);
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param.push_back(effort);
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param.push_back(IMWRITE_JPEGXL_DECODING_SPEED);
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param.push_back(speed);
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EXPECT_NO_THROW(ret = imencode(".jxl", img_org, buff, param));
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EXPECT_TRUE(ret);
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Mat img_decoded;
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EXPECT_NO_THROW(img_decoded = imdecode(buff, IMREAD_UNCHANGED));
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EXPECT_FALSE(img_decoded.empty());
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EXPECT_LE(cvtest::norm(img_org, img_decoded, NORM_INF), th);
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}
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INSTANTIATE_TEST_CASE_P(
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/**/,
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Imgcodecs_JpegXL_Effort_DecodingSpeed,
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testing::Combine(
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testing::Values( // Effort
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1, // fastest
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7, // default
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9 // slowest
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),
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testing::Values( // Decoding Speed
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0, // default, slowest, and best quality/density
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2,
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4 // fastest, at the cost of some qulity/density
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)
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) );
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TEST(Imgcodecs_JpegXL, encode_from_uncontinued_image)
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{
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cv::Mat src(100, 100, CV_8UC1, Scalar(40,50,10));
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cv::Mat roi = src(cv::Rect(10,20,30,50));
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EXPECT_FALSE(roi.isContinuous()); // uncontinued image
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vector<uint8_t> buff;
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vector<int> param;
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bool ret = false;
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EXPECT_NO_THROW(ret = cv::imencode(".jxl", roi, buff, param));
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EXPECT_TRUE(ret);
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}
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#endif // HAVE_JPEGXL
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} // namespace
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} // namespace opencv_test
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