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314 lines
10 KiB
C++
314 lines
10 KiB
C++
// 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 directory
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// 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_JPEG
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/**
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* Test for check whether reading exif orientation tag was processed successfully or not
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* The test info is the set of 8 images named testExifRotate_{1 to 8}.jpg
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* The test image is the square 10x10 points divided by four sub-squares:
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* (R corresponds to Red, G to Green, B to Blue, W to white)
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* --------- ---------
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* | R | G | | G | R |
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* |-------| - (tag 1) |-------| - (tag 2)
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* | B | W | | W | B |
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* --------- ---------
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*
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* --------- ---------
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* | W | B | | B | W |
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* |-------| - (tag 3) |-------| - (tag 4)
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* | G | R | | R | G |
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* --------- ---------
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*
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* --------- ---------
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* | R | B | | G | W |
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* |-------| - (tag 5) |-------| - (tag 6)
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* | G | W | | R | B |
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* --------- ---------
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*
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* --------- ---------
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* | W | G | | B | R |
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* |-------| - (tag 7) |-------| - (tag 8)
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* | B | R | | W | G |
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* --------- ---------
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*
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*
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* Every image contains exif field with orientation tag (0x112)
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* After reading each image the corresponding matrix must be read as
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* ---------
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* | R | G |
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* |-------|
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* | B | W |
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* ---------
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*
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*/
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typedef testing::TestWithParam<string> Imgcodecs_Jpeg_Exif;
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TEST_P(Imgcodecs_Jpeg_Exif, exif_orientation)
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{
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const string root = cvtest::TS::ptr()->get_data_path();
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const string filename = root + GetParam();
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const int colorThresholdHigh = 250;
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const int colorThresholdLow = 5;
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Mat m_img = imread(filename);
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ASSERT_FALSE(m_img.empty());
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Vec3b vec;
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//Checking the first quadrant (with supposed red)
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vec = m_img.at<Vec3b>(2, 2); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_GE(vec.val[2], colorThresholdHigh);
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//Checking the second quadrant (with supposed green)
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vec = m_img.at<Vec3b>(2, 7); //some point inside the square
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EXPECT_LE(vec.val[0], colorThresholdLow);
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EXPECT_GE(vec.val[1], colorThresholdHigh);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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//Checking the third quadrant (with supposed blue)
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vec = m_img.at<Vec3b>(7, 2); //some point inside the square
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EXPECT_GE(vec.val[0], colorThresholdHigh);
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EXPECT_LE(vec.val[1], colorThresholdLow);
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EXPECT_LE(vec.val[2], colorThresholdLow);
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}
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const string exif_files[] =
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{
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"readwrite/testExifOrientation_1.jpg",
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"readwrite/testExifOrientation_2.jpg",
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"readwrite/testExifOrientation_3.jpg",
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"readwrite/testExifOrientation_4.jpg",
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"readwrite/testExifOrientation_5.jpg",
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"readwrite/testExifOrientation_6.jpg",
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"readwrite/testExifOrientation_7.jpg",
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"readwrite/testExifOrientation_8.jpg"
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};
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INSTANTIATE_TEST_CASE_P(ExifFiles, Imgcodecs_Jpeg_Exif,
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testing::ValuesIn(exif_files));
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//==================================================================================================
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TEST(Imgcodecs_Jpeg, encode_empty)
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{
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cv::Mat img;
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std::vector<uchar> jpegImg;
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ASSERT_THROW(cv::imencode(".jpg", img, jpegImg), cv::Exception);
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}
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TEST(Imgcodecs_Jpeg, encode_decode_progressive_jpeg)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
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cv::Mat img = cv::imread(input);
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ASSERT_FALSE(img.empty());
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std::vector<int> params;
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params.push_back(IMWRITE_JPEG_PROGRESSIVE);
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params.push_back(1);
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string output_progressive = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_progressive, img, params));
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cv::Mat img_jpg_progressive = cv::imread(output_progressive);
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string output_normal = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_normal, img));
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cv::Mat img_jpg_normal = cv::imread(output_normal);
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EXPECT_EQ(0, cvtest::norm(img_jpg_progressive, img_jpg_normal, NORM_INF));
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EXPECT_EQ(0, remove(output_progressive.c_str()));
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EXPECT_EQ(0, remove(output_normal.c_str()));
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}
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TEST(Imgcodecs_Jpeg, encode_decode_optimize_jpeg)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
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cv::Mat img = cv::imread(input);
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ASSERT_FALSE(img.empty());
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std::vector<int> params;
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params.push_back(IMWRITE_JPEG_OPTIMIZE);
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params.push_back(1);
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string output_optimized = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_optimized, img, params));
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cv::Mat img_jpg_optimized = cv::imread(output_optimized);
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string output_normal = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_normal, img));
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cv::Mat img_jpg_normal = cv::imread(output_normal);
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EXPECT_EQ(0, cvtest::norm(img_jpg_optimized, img_jpg_normal, NORM_INF));
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EXPECT_EQ(0, remove(output_optimized.c_str()));
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EXPECT_EQ(0, remove(output_normal.c_str()));
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}
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TEST(Imgcodecs_Jpeg, encode_decode_rst_jpeg)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
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cv::Mat img = cv::imread(input);
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ASSERT_FALSE(img.empty());
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std::vector<int> params;
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params.push_back(IMWRITE_JPEG_RST_INTERVAL);
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params.push_back(1);
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string output_rst = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_rst, img, params));
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cv::Mat img_jpg_rst = cv::imread(output_rst);
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string output_normal = cv::tempfile(".jpg");
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EXPECT_NO_THROW(cv::imwrite(output_normal, img));
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cv::Mat img_jpg_normal = cv::imread(output_normal);
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EXPECT_EQ(0, cvtest::norm(img_jpg_rst, img_jpg_normal, NORM_INF));
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EXPECT_EQ(0, remove(output_rst.c_str()));
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EXPECT_EQ(0, remove(output_normal.c_str()));
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}
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// See https://github.com/opencv/opencv/issues/25274
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typedef testing::TestWithParam<int> Imgcodecs_Jpeg_decode_cmyk;
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TEST_P(Imgcodecs_Jpeg_decode_cmyk, regression25274)
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{
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const int imread_flag = GetParam();
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/*
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* "test_1_c4.jpg" is CMYK-JPEG.
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* $ convert test_1_c3.jpg -colorspace CMYK test_1_c4.jpg
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* $ identify test_1_c4.jpg
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* test_1_c4.jpg JPEG 480x640 480x640+0+0 8-bit CMYK 11240B 0.000u 0:00.000
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*/
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cvtest::TS& ts = *cvtest::TS::ptr();
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string rgb_filename = string(ts.get_data_path()) + "readwrite/test_1_c3.jpg";
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cv::Mat rgb_img = cv::imread(rgb_filename, imread_flag);
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ASSERT_FALSE(rgb_img.empty());
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string cmyk_filename = string(ts.get_data_path()) + "readwrite/test_1_c4.jpg";
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cv::Mat cmyk_img = cv::imread(cmyk_filename, imread_flag);
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ASSERT_FALSE(cmyk_img.empty());
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EXPECT_EQ(rgb_img.size(), cmyk_img.size());
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EXPECT_EQ(rgb_img.type(), cmyk_img.type());
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// Jpeg is lossy compression.
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// There may be small differences in decoding results by environments.
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// -> 255 * 1% = 2.55 .
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EXPECT_LE(cvtest::norm(rgb_img, cmyk_img, NORM_INF), 3); // norm() <= 3
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}
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INSTANTIATE_TEST_CASE_P( /* nothing */,
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Imgcodecs_Jpeg_decode_cmyk,
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testing::Values(cv::IMREAD_COLOR,
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cv::IMREAD_GRAYSCALE,
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cv::IMREAD_ANYCOLOR));
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//==================================================================================================
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static const uint32_t default_sampling_factor = static_cast<uint32_t>(0x221111);
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static uint32_t test_jpeg_subsampling( const Mat src, const vector<int> param )
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{
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vector<uint8_t> jpeg;
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if ( cv::imencode(".jpg", src, jpeg, param ) == false )
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{
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return 0;
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}
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if ( src.channels() != 3 )
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{
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return 0;
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}
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// Find SOF Marker(FFC0)
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int sof_offset = 0; // not found.
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int jpeg_size = static_cast<int>( jpeg.size() );
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for ( int i = 0 ; i < jpeg_size - 1; i++ )
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{
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if ( (jpeg[i] == 0xff ) && ( jpeg[i+1] == 0xC0 ) )
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{
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sof_offset = i;
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break;
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}
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}
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if ( sof_offset == 0 )
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{
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return 0;
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}
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// Extract Subsampling Factor from SOF.
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return ( jpeg[sof_offset + 0x0A + 3 * 0 + 1] << 16 ) +
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( jpeg[sof_offset + 0x0A + 3 * 1 + 1] << 8 ) +
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( jpeg[sof_offset + 0x0A + 3 * 2 + 1] ) ;
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}
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TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_default)
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{
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vector<int> param;
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Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
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EXPECT_EQ( default_sampling_factor, test_jpeg_subsampling(src, param) );
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}
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TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_usersetting_valid)
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{
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Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
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const uint32_t sampling_factor_list[] = {
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IMWRITE_JPEG_SAMPLING_FACTOR_411,
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IMWRITE_JPEG_SAMPLING_FACTOR_420,
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IMWRITE_JPEG_SAMPLING_FACTOR_422,
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IMWRITE_JPEG_SAMPLING_FACTOR_440,
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IMWRITE_JPEG_SAMPLING_FACTOR_444,
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};
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const int sampling_factor_list_num = 5;
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for ( int i = 0 ; i < sampling_factor_list_num; i ++ )
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{
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vector<int> param;
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param.push_back( IMWRITE_JPEG_SAMPLING_FACTOR );
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param.push_back( sampling_factor_list[i] );
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EXPECT_EQ( sampling_factor_list[i], test_jpeg_subsampling(src, param) );
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}
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}
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TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_usersetting_invalid)
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{
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Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
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const uint32_t sampling_factor_list[] = { // Invalid list
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0x111112,
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0x000000,
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0x001111,
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0xFF1111,
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0x141111, // 1x4,1x1,1x1 - unknown
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0x241111, // 2x4,1x1,1x1 - unknown
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0x421111, // 4x2,1x1,1x1 - unknown
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0x441111, // 4x4,1x1,1x1 - 410(libjpeg cannot handle it)
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};
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const int sampling_factor_list_num = 8;
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for ( int i = 0 ; i < sampling_factor_list_num; i ++ )
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{
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vector<int> param;
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param.push_back( IMWRITE_JPEG_SAMPLING_FACTOR );
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param.push_back( sampling_factor_list[i] );
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EXPECT_EQ( default_sampling_factor, test_jpeg_subsampling(src, param) );
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}
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}
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#endif // HAVE_JPEG
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}} // namespace
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