float dist(const Indiv& ind)
{
cv::Mat tmp(ind.image());
assert(tmp.cols == _image.cols);
assert(tmp.rows == _image.rows);
float total_distance = 0;
// Change specific color of every pixel in the image
for (int x = 0; x < tmp.cols; ++x)
{
for (int y = 0; y < tmp.rows; ++y)
{
cv::Vec3b color_2 = _image.at<cv::Vec3b>(cv::Point(x,y));
//
cv::Vec3b color_1 = tmp.at<cv::Vec3b >(cv::Point(x,y));
// Three color values H, S, L
for (int c = 0; c < 3; c++)
{
float d = color_1[c] - color_2[c];
total_distance += d * d; // Add the square of this distance
}
}
}
return sqrtf(total_distance);
}
void eval(const Indiv& ind)
{
if (Params::image::color)
{
// Convert image to BGR before evaluating
cv::Mat output;
// Convert HLS into BGR because imwrite uses BGR color space
cv::cvtColor(ind.image(), output, CV_HLS2BGR);
// Create an empty list to store get 1000 probabilities
_setProbabilityList(output);
}
else // Grayscale
{
// Create an empty list to store get 1000 probabilities
_setProbabilityList(ind.image());
}
}