opencv/modules/imgcodecs/test/test_jpeg.cpp

#include "test_precomp.hpp"

using namespace cv;
using namespace std;
using namespace std::tr1;

#ifdef HAVE_JPEG

/**
 * Test for check whether reading exif orientation tag was processed successfully or not
 * The test info is the set of 8 images named testExifRotate_{1 to 8}.jpg
 * The test image is the square 10x10 points divided by four sub-squares:
 * (R corresponds to Red, G to Green, B to Blue, W to white)
 * ---------             ---------
 * | R | G |             | G | R |
 * |-------| - (tag 1)   |-------| - (tag 2)
 * | B | W |             | W | B |
 * ---------             ---------
 *
 * ---------             ---------
 * | W | B |             | B | W |
 * |-------| - (tag 3)   |-------| - (tag 4)
 * | G | R |             | R | G |
 * ---------             ---------
 *
 * ---------             ---------
 * | R | B |             | G | W |
 * |-------| - (tag 5)   |-------| - (tag 6)
 * | G | W |             | R | B |
 * ---------             ---------
 *
 * ---------             ---------
 * | W | G |             | B | R |
 * |-------| - (tag 7)   |-------| - (tag 8)
 * | B | R |             | W | G |
 * ---------             ---------
 *
 *
 * Every image contains exif field with orientation tag (0x112)
 * After reading each image the corresponding matrix must be read as
 * ---------
 * | R | G |
 * |-------|
 * | B | W |
 * ---------
 *
 */

typedef testing::TestWithParam<string> Imgcodecs_Jpeg_Exif;

TEST_P(Imgcodecs_Jpeg_Exif, exif_orientation)
{
    const string root = cvtest::TS::ptr()->get_data_path();
    const string filename = root + GetParam();
    const int colorThresholdHigh = 250;
    const int colorThresholdLow = 5;

    Mat m_img = imread(filename);
    ASSERT_FALSE(m_img.empty());
    Vec3b vec;

    //Checking the first quadrant (with supposed red)
    vec = m_img.at<Vec3b>(2, 2); //some point inside the square
    EXPECT_LE(vec.val[0], colorThresholdLow);
    EXPECT_LE(vec.val[1], colorThresholdLow);
    EXPECT_GE(vec.val[2], colorThresholdHigh);

    //Checking the second quadrant (with supposed green)
    vec = m_img.at<Vec3b>(2, 7);  //some point inside the square
    EXPECT_LE(vec.val[0], colorThresholdLow);
    EXPECT_GE(vec.val[1], colorThresholdHigh);
    EXPECT_LE(vec.val[2], colorThresholdLow);

    //Checking the third quadrant (with supposed blue)
    vec = m_img.at<Vec3b>(7, 2);  //some point inside the square
    EXPECT_GE(vec.val[0], colorThresholdHigh);
    EXPECT_LE(vec.val[1], colorThresholdLow);
    EXPECT_LE(vec.val[2], colorThresholdLow);
}

const string exif_files[] =
{
    "readwrite/testExifOrientation_1.jpg",
    "readwrite/testExifOrientation_2.jpg",
    "readwrite/testExifOrientation_3.jpg",
    "readwrite/testExifOrientation_4.jpg",
    "readwrite/testExifOrientation_5.jpg",
    "readwrite/testExifOrientation_6.jpg",
    "readwrite/testExifOrientation_7.jpg",
    "readwrite/testExifOrientation_8.jpg"
};

INSTANTIATE_TEST_CASE_P(ExifFiles, Imgcodecs_Jpeg_Exif,
                        testing::ValuesIn(exif_files));

//==================================================================================================

TEST(Imgcodecs_Jpeg, encode_empty)
{
    cv::Mat img;
    std::vector<uchar> jpegImg;
    ASSERT_THROW(cv::imencode(".jpg", img, jpegImg), cv::Exception);
}

TEST(Imgcodecs_Jpeg, encode_decode_progressive_jpeg)
{
    cvtest::TS& ts = *cvtest::TS::ptr();
    string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
    cv::Mat img = cv::imread(input);
    ASSERT_FALSE(img.empty());

    std::vector<int> params;
    params.push_back(IMWRITE_JPEG_PROGRESSIVE);
    params.push_back(1);

    string output_progressive = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_progressive, img, params));
    cv::Mat img_jpg_progressive = cv::imread(output_progressive);

    string output_normal = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_normal, img));
    cv::Mat img_jpg_normal = cv::imread(output_normal);

    EXPECT_EQ(0, cvtest::norm(img_jpg_progressive, img_jpg_normal, NORM_INF));

    remove(output_progressive.c_str());
    remove(output_normal.c_str());
}

TEST(Imgcodecs_Jpeg, encode_decode_optimize_jpeg)
{
    cvtest::TS& ts = *cvtest::TS::ptr();
    string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
    cv::Mat img = cv::imread(input);
    ASSERT_FALSE(img.empty());

    std::vector<int> params;
    params.push_back(IMWRITE_JPEG_OPTIMIZE);
    params.push_back(1);

    string output_optimized = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_optimized, img, params));
    cv::Mat img_jpg_optimized = cv::imread(output_optimized);

    string output_normal = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_normal, img));
    cv::Mat img_jpg_normal = cv::imread(output_normal);

    EXPECT_EQ(0, cvtest::norm(img_jpg_optimized, img_jpg_normal, NORM_INF));

    remove(output_optimized.c_str());
    remove(output_normal.c_str());
}

TEST(Imgcodecs_Jpeg, encode_decode_rst_jpeg)
{
    cvtest::TS& ts = *cvtest::TS::ptr();
    string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
    cv::Mat img = cv::imread(input);
    ASSERT_FALSE(img.empty());

    std::vector<int> params;
    params.push_back(IMWRITE_JPEG_RST_INTERVAL);
    params.push_back(1);

    string output_rst = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_rst, img, params));
    cv::Mat img_jpg_rst = cv::imread(output_rst);

    string output_normal = cv::tempfile(".jpg");
    EXPECT_NO_THROW(cv::imwrite(output_normal, img));
    cv::Mat img_jpg_normal = cv::imread(output_normal);

    EXPECT_EQ(0, cvtest::norm(img_jpg_rst, img_jpg_normal, NORM_INF));

    remove(output_rst.c_str());
    remove(output_normal.c_str());
}

#endif // HAVE_JPEG