Resize changes

arapaho-Detect-func.cpp

bool ArapahoV2::Detect(
    const cv::Mat & inputMat,
    float thresh,
    float hier_thresh,
    int & objectCount)
{
    int count = 0;

    objectCount = 0;
    threshold = thresh;

    // Early exits
    if (!bSetup)
    {
        EPRINTF("Not Setup!\n");
        return false;
    }
    if (inputMat.empty())
    {
        EPRINTF("Error in inputImage! [bgr = %d, w = %d, h = %d]\n",
            !inputMat.data, inputMat.cols != net->w,
            inputMat.rows != net->h);
        return false;
    }

    //Convert to rgb
    cv::Mat inputRgb;
    cvtColor(inputMat, inputRgb, CV_BGR2RGB);
    // Convert the bytes to float
    cv::Mat floatMat;
    inputRgb.convertTo(floatMat, CV_32FC3, 1 / 255.0);

    cv::Mat resizedFloatMat = floatMat;
    if (floatMat.rows != net->h || floatMat.cols != net->w)
    {
        DPRINTF("Detect: Resizing image to match network \n");
        resize(floatMat, resizedFloatMat, cv::Size(net->w, net->h));
    }

    if (resizedFloatMat.channels() != 3)
    {
        EPRINTF("Detect: channels = %d \n", resizedFloatMat.channels());
        return false;
    }
    // Get the image to suit darknet
    cv::Mat floatMatChannels[3];
    cv::Mat planarFloatMatTemp, planarFloatMat;
    cv::split(resizedFloatMat, floatMatChannels);
    vconcat(floatMatChannels[0], floatMatChannels[1], planarFloatMatTemp);
    vconcat(planarFloatMatTemp, floatMatChannels[2], planarFloatMat);

    __Detect((float*)planarFloatMat.data, thresh, hier_thresh, objectCount);

    return true;
}