shivanference

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Training becomes very slow with these transforms.

Sure, following is the flow. ### Importing transforms ```from augraphy.augmentations import ShadowCast, ReflectedLight, Folding....``` ### Creating a wrapper around it ``` class GenericTransforms: def __init__(self, transform, prob): self.transform = transform...

Training becomes very slow with these transforms.

I did that, I only considered the augmentation, for which `Img/sec` was more than or around 1. But did not help much in speeding.

Training becomes very slow with these transforms.

Thanks. The image size is around `900x1100`.

Training becomes very slow with these transforms.

I have narrowed down the issue. As I mentioned, `load average` shoots up with these transforms. When I limit the threads used by Numpy and Opencv to 1, then the...

Training becomes very slow with these transforms.

A minor correction in the code: ### This is how the transforms are defined: ``` class Moire_: def __init__(self, prob=0.15): self.moire = Moire() self.prob = prob def __call__(self, img): if...