I tried using tf._files(), I had all my files but I did not found how to load my numpy array to feed my model. ![]() The problem i that ImageDataGenerator.flow_from_directory() only works with image type files (so a 256x256x3 image) and I would like to know if there is a way to do the same thing with numpy arrays. To have my image I then merge the input and output to have a LAB image (256, 256, 3). My targets are A and B components (256, 256, 2). ![]() ![]() I have found that it is possible to use ImageDataGenerator.flow_from_directory() but I use LAB images and I would like to feed my model with a numpy array of the L component (256, 256, 1). I have 5000 images (256x256x3) and would like not to load all data in my program (for memory reason).
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