![]() To get a new random rotation for each image we need to use a random function from Tensorflow itself. For this we can use the rot90 function of Tensorflow. One of the most simplest augmentations is rotating the image 90 degrees. Of course, there are many more augmentations that could be useful, but most of them follow the same approach. ![]() Nevertheless, I show them here as an example as they can be useful for tasks that are more orientation invariant. ![]() learning to detect flipped trucks is maybe not that beneficial for the task at hand. Not all of these augmentations are necessarily applicable to CIFAR10 e.g. Color augmentations (hue, saturation, brightness, contrast).With this basic recipe for an augmenter function we can implement the augmenters itself.
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