// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "test_precomp.hpp"

namespace opencv_test { namespace {

#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));

    EXPECT_EQ(0, remove(output_progressive.c_str()));
    EXPECT_EQ(0, 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));

    EXPECT_EQ(0, remove(output_optimized.c_str()));
    EXPECT_EQ(0, 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));

    EXPECT_EQ(0, remove(output_rst.c_str()));
    EXPECT_EQ(0, remove(output_normal.c_str()));
}

// See https://github.com/opencv/opencv/issues/25274
typedef testing::TestWithParam<int> Imgcodecs_Jpeg_decode_cmyk;
TEST_P(Imgcodecs_Jpeg_decode_cmyk, regression25274)
{
    const int imread_flag = GetParam();

    /*
     * "test_1_c4.jpg" is CMYK-JPEG.
     * $ convert test_1_c3.jpg -colorspace CMYK test_1_c4.jpg
     * $ identify test_1_c4.jpg
     * test_1_c4.jpg JPEG 480x640 480x640+0+0 8-bit CMYK 11240B 0.000u 0:00.000
     */

    cvtest::TS& ts = *cvtest::TS::ptr();

    string  rgb_filename  = string(ts.get_data_path()) + "readwrite/test_1_c3.jpg";
    cv::Mat rgb_img       = cv::imread(rgb_filename, imread_flag);
    ASSERT_FALSE(rgb_img.empty());

    string  cmyk_filename = string(ts.get_data_path()) + "readwrite/test_1_c4.jpg";
    cv::Mat cmyk_img      = cv::imread(cmyk_filename, imread_flag);
    ASSERT_FALSE(cmyk_img.empty());

    EXPECT_EQ(rgb_img.size(), cmyk_img.size());
    EXPECT_EQ(rgb_img.type(), cmyk_img.type());

    // Jpeg is lossy compression.
    // There may be small differences in decoding results by environments.
    // -> 255 * 1% = 2.55 .
    EXPECT_LE(cvtest::norm(rgb_img, cmyk_img, NORM_INF), 3); // norm() <= 3
}

INSTANTIATE_TEST_CASE_P( /* nothing */,
                        Imgcodecs_Jpeg_decode_cmyk,
                        testing::Values(cv::IMREAD_COLOR,
                                        cv::IMREAD_GRAYSCALE,
                                        cv::IMREAD_ANYCOLOR));

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

static const uint32_t default_sampling_factor = static_cast<uint32_t>(0x221111);

static uint32_t test_jpeg_subsampling( const Mat src, const vector<int> param )
{
    vector<uint8_t> jpeg;

    if ( cv::imencode(".jpg", src, jpeg, param ) == false )
    {
        return 0;
    }

    if ( src.channels() != 3 )
    {
        return 0;
    }

    // Find SOF Marker(FFC0)
    int sof_offset = 0; // not found.
    int jpeg_size = static_cast<int>( jpeg.size() );
    for ( int i = 0 ; i < jpeg_size - 1; i++ )
    {
        if ( (jpeg[i] == 0xff ) && ( jpeg[i+1] == 0xC0 ) )
        {
            sof_offset = i;
            break;
        }
    }
    if ( sof_offset == 0 )
    {
        return 0;
    }

    // Extract Subsampling Factor from SOF.
    return ( jpeg[sof_offset + 0x0A + 3 * 0 + 1] << 16 ) +
           ( jpeg[sof_offset + 0x0A + 3 * 1 + 1] << 8  ) +
           ( jpeg[sof_offset + 0x0A + 3 * 2 + 1]       ) ;
}

TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_default)
{
    vector<int> param;
    Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
    EXPECT_EQ( default_sampling_factor, test_jpeg_subsampling(src, param) );
}

TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_usersetting_valid)
{
    Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
    const uint32_t sampling_factor_list[] = {
        IMWRITE_JPEG_SAMPLING_FACTOR_411,
        IMWRITE_JPEG_SAMPLING_FACTOR_420,
        IMWRITE_JPEG_SAMPLING_FACTOR_422,
        IMWRITE_JPEG_SAMPLING_FACTOR_440,
        IMWRITE_JPEG_SAMPLING_FACTOR_444,
    };
    const int sampling_factor_list_num = 5;

    for ( int i = 0 ; i < sampling_factor_list_num; i ++ )
    {
        vector<int> param;
        param.push_back( IMWRITE_JPEG_SAMPLING_FACTOR );
        param.push_back( sampling_factor_list[i] );
        EXPECT_EQ( sampling_factor_list[i], test_jpeg_subsampling(src, param) );
    }
}

TEST(Imgcodecs_Jpeg, encode_subsamplingfactor_usersetting_invalid)
{
    Mat src( 48, 64, CV_8UC3, cv::Scalar::all(0) );
    const uint32_t sampling_factor_list[] = { // Invalid list
        0x111112,
        0x000000,
        0x001111,
        0xFF1111,
        0x141111, // 1x4,1x1,1x1 - unknown
        0x241111, // 2x4,1x1,1x1 - unknown
        0x421111, // 4x2,1x1,1x1 - unknown
        0x441111, // 4x4,1x1,1x1 - 410(libjpeg cannot handle it)
    };
    const int sampling_factor_list_num = 8;

    for ( int i = 0 ; i < sampling_factor_list_num; i ++ )
    {
        vector<int> param;
        param.push_back( IMWRITE_JPEG_SAMPLING_FACTOR );
        param.push_back( sampling_factor_list[i] );
        EXPECT_EQ( default_sampling_factor, test_jpeg_subsampling(src, param) );
    }
}

#endif // HAVE_JPEG

}} // namespace