public float EvaluateFitness(int index, Program.Settings settings)
{
Convolve(index, settings);
Mat targetTmp = new Mat();
Mat dstTmp = new Mat();
targetImgs[index].ConvertTo(targetTmp, MatType.CV_32FC3);
dstImg.ConvertTo(dstTmp, MatType.CV_32FC3);
//targetTmp *= -1;
//Cv2.Add(dstImg, targetTmp, targetTmp, null, MatType.CV_32F);
Cv2.Absdiff(dstTmp, targetTmp, targetTmp);
dstTmp.Dispose();
return(-(float)targetTmp.Sum());
}
public void Convolve(int index, Program.Settings settings)
{
dstImg = srcImgs[index].Filter2D(-1, kernels[0]);
for (int i = 1; i < kernels.Length; i++)
{
//dstImg = dstImg.Filter2D(-1, kernels[i]);
if (inSize.Width != settings.midLayerRes || inSize.Width != settings.outLayerRes)//Assuming width and height are the same
{
//This could be slow...
float respos = ((i / ((float)kernels.Length - 1)) * 2);
int size = (int)Lerp(Lerp(inSize.Width, settings.midLayerRes, respos), settings.outLayerRes, respos - 1f);
size = ToNearestPowerOf2(size);
Size nSize = new Size(size, size);
Cv2.Resize(dstImg, dstImg, nSize);
}
Cv2.Filter2D(dstImg, dstImg, -1, kernels[i]);
}
//File.WriteAllBytes("tmpimg.png", dstImg.ToBytes());
}
