Yellowish color on color corrector with COLORCHECKER_Macbeth

[FrankEscobar]

System information (version)

• OpenCV => 4.10

• Operating System / Platform => Windows 64 Bit

• Compiler => Visual Studio 2022

• OpenCV => 4.10

• Operating System / Platform => Windows 64 Bit

• Compiler => Visual Studio 2022

Detailed description

Following the tutorial I manage to make color correction over the image and the result is not totally weird but for away from others like DaVinci Resolve implementation.

bool getRGBChartsFromImage(const string& imagePath,const TYPECHART chartType, Mat &mat)
{
    Mat imageWithCheck = imread(imagePath, IMREAD_COLOR);
    if (!imageWithCheck.data) {
        cout << "Invalid Image Check!" << endl;
        return false;
    }
    Ptr<CCheckerDetector> detector = CCheckerDetector::create();
    if (!detector->process(imageWithCheck, chartType, 1)) {
        printf("ChartColor not detected \n");
        return false;
    }
    vector<Ptr<mcc::CChecker>> checkers = detector->getListColorChecker();
    if (checkers.size() != 1)
    {
        printf("Invalid amount of charts %i\n", (int)checkers.size());
    }
    Ptr<mcc::CChecker> checker = checkers[0];
    Mat chartsRGB = checker->getChartsRGB();
    mat = chartsRGB.col(1).clone().reshape(3, chartsRGB.rows / 3);
    mat /= 255.0;
}
bool calibrateImage(const Mat& uncalibradedMat, const TYPECHART chartType, const Mat &chartMat, Mat& calibratedMat)
{
    CONST_COLOR destColor;
    switch (chartType) {
    case cv::mcc::MCC24:
        destColor = COLORCHECKER_Macbeth;
        break;
    case cv::mcc::SG140:
        destColor = COLORCHECKER_DigitalSG;
        break;
    case cv::mcc::VINYL18:
        destColor = COLORCHECKER_Vinyl;
        break;
    default:
        printf("Invalid chart type. Exiting.\n");
        return false;
    }
    ColorCorrectionModel model(chartMat, destColor);
    //model.setInitialMethod(INITIAL_METHOD_WHITE_BALANCE);
    model.setColorSpace(COLOR_SPACE_sRGB);
    model.setDistance(DISTANCE_CIE2000);
    model.setLinear(LINEARIZATION_GAMMA);
    model.setLinearGamma(2.0);
    model.setLinearDegree(3);
    model.setCCM_TYPE(CCM_3x3);
    model.setMaxCount(5000);
    model.setEpsilon(1e-7);
    model.setSaturatedThreshold(0, 0.98);
    model.run();
    Mat ccm = model.getCCM();
    std::cout << "ccm:\n" << ccm << std::endl;
    double loss = model.getLoss();
    std::cout << "loss: " << loss << std::endl;
    // Aplicar el modelo a imageMod
    Mat img_;
    cvtColor(uncalibradedMat, img_, COLOR_BGR2RGB);
    img_.convertTo(img_, CV_64F, 1.0 / 255.0);
    Mat calibratedImage = model.infer(img_);
    Mat out_ = calibratedImage * 255.0;
    out_.convertTo(out_, CV_8UC3);
    Mat img_out = min(max(out_, 0), 255);
    cvtColor(img_out, calibratedMat, COLOR_RGB2BGR);
    return true;
}

You can notice that the result is too warm.

Input

calibrated

Thank you in advance