I have images from satellite data that has 6 channels. Usual RGB channels and 3 other channels. Now, I am trying to fine tune a pretrained resnet model. I understand how to change the first convolution layer to accommodate for 3 additional input channel (from this discussion post but I have other concern. So, in the new custom first layer, I want to set the kernel parameters for RGB channel to be same as the pretrained resnet model. But for the new 3 channel, i would like to initialize the kernel parameters as mean of (at corresponding coordinates). kernels of pretrained resnet RGB channels.
Not sure how I can do that. Any suggestion/example would be super helpful!