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183 lines
5.9 KiB
183 lines
5.9 KiB
// 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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