private static void optimize_picture(Network net, Image orig, int maxLayer, float scale, float rate, float thresh, bool norm)
{
net.N = maxLayer + 1;
int dx = Utils.Rand.Next() % 16 - 8;
int dy = Utils.Rand.Next() % 16 - 8;
bool flip = Utils.Rand.Next() % 2 != 0;
Image crop = LoadArgs.crop_image(orig, dx, dy, orig.W, orig.H);
Image im = LoadArgs.resize_image(crop, (int)(orig.W * scale), (int)(orig.H * scale));
if (flip)
{
LoadArgs.flip_image(im);
}
Network.resize_network(net, im.W, im.H);
Layer last = net.Layers[net.N - 1];
Image delta = new Image(im.W, im.H, im.C);
NetworkState state = new NetworkState();
state.Input = (float[])im.Data.Clone();
state.Delta = (float[])im.Data.Clone();
Network.forward_network_gpu(net, state);
Blas.copy_ongpu(last.Outputs, last.OutputGpu, last.DeltaGpu);
Array.Copy(last.DeltaGpu, last.Delta, last.Outputs);
calculate_loss(last.Delta, last.Delta, last.Outputs, thresh);
Array.Copy(last.Delta, last.DeltaGpu, last.Outputs);
Network.backward_network_gpu(net, state);
Array.Copy(state.Delta, delta.Data, im.W * im.H * im.C);
if (flip)
{
LoadArgs.flip_image(delta);
}
Image resized = LoadArgs.resize_image(delta, orig.W, orig.H);
Image outi = LoadArgs.crop_image(resized, -dx, -dy, orig.W, orig.H);
if (norm)
{
Utils.normalize_array(outi.Data, outi.W * outi.H * outi.C);
}
Blas.Axpy_cpu(orig.W * orig.H * orig.C, rate, outi.Data, orig.Data);
LoadArgs.constrain_image(orig);
}
