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Tetragramm
GitHub Repository: Tetragramm/opencv
Path: blob/master/modules/imgcodecs/test/test_jpeg.cpp
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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 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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#endif // HAVE_JPEG
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}} // namespace
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