Hacky way to augment multichannel images in Keras

Question

I need to augment multichannel images and would like to use ImageDataGenerator Unfortunately, it supports 1,3 and 4 channel images only and I need much more. Would it be OK to directly edit site-packages/Keras/preprocessing/image.py adding necessary number of channels?

    if x.shape[self.channel_axis] not in {1, 3, 4, XXX}:
        raise ValueError(
            'Expected input to be images (as Numpy array) '
            'following the dimension ordering convention "' + self.dim_ordering + '" '
            '(channels on axis ' + str(self.channel_axis) + '), i.e. expected '
            'either 1, 3 or 4 channels on axis ' + str(self.channel_axis) + '. '
            'However, it was passed an array with shape ' + str(x.shape) +
            ' (' + str(x.shape[self.channel_axis]) + ' channels).')

where XXX - is a number of channels that I need. Would this break anything? Thanks!

Answer 1

I tried that anyway and it seems to work without too many side effects. I didn't explore every possible problem, though. So if you have multichannel data (like satellite imagery, etc) you can try this hack. There are couple of places where you need to augment the augmentation code :)