[1/2] Add Image Ops for Data Augmentation

[abhichou4]

Part 2: #1353

As part of #1226, relevant image ops need to be added to tfa.image. List of ops tracked in this issue (tick the op only once the corresponding PR is merged):

• Blend
• CutOut
• Identity
• Translate X, Y
• Shear X, Y
• Solarize Ops
• Posterize
• AutoContrast
• Equalize
• Invert
• Color
• Brightness
• Sharpness

Reference: https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/autoaugment.py

[vinayvr11]

Ok So these unchecked options are remaining. But what is PIL does it stands for Pillow or something else. And i have to implement these in autoaugment.py am i right.

[abhichou4]

Ok So these unchecked options are remaining. But what is PIL does it stands for Pillow or something else. And i have to implement these in autoaugment.py am i right.

That's right, but the appropriate namescapes and where to place these operations is something that can be discussed here or on your PR.
/cc @bhack @gabrieldemarmiesse

[vinayvr11]

Ok so for now i just need to make a script for these operations and after that we decide that where to put them all. So all these operations are have to be integrated in one script or i have to make a different scripts for all of them.
Thank you

[gabrieldemarmiesse]

Yeah, as long as the public API stays the same and is decided first, it's not critical how you name your files.

[vinayvr11]

@gabrieldemarmiesse : I have some doubts so we have to use the tensorflow for doing these operations or we are free to use any module.
And all these methods have to be made in different files. Please correct me if i am wrong.

[gabrieldemarmiesse]

You should always use tensorflow to make those ops (so they can run on tpu/cpu/cuda/ROCm and can be exported in a graph and have gradients and many other things... ) and where you put the ops is not critical (meaning we care more about the pull request being merged than about the name of the file, as it can be changed later without impacting the API). You can group ops together in the same file if you feel this is the right move.

Prefer using python only if possible.

[vinayvr11]

Ok and what about Tensorflow version shall i need to take care about the version also or i can use any version of Tensorflow.

[gabrieldemarmiesse]

We currently test with tensorflow 2.1.0 and 2.2.0rc0

[vinayvr11]

ok thank you

[vinayvr11]

@gabrieldemarmiesse : Do we have a pre defined gaussian filter in tensorflow or any similar to this or i just need to make a filter in order to blur the images.

[bhack]

Just to compare to this ops checkbox list with RemixMatch/FixMatch https://github.com/google-research/remixmatch/blob/master/libml/augment.py#L36-L41

[bhack]

Here the EfficientDet Autoaugment ops list https://github.com/google/automl/blob/master/efficientdet/aug/autoaugment.py#L43-L153

[vinayvr11]

@bhack
So do we have to make a new list of these ops or leave them out?

[bhack]

@vinayvr11 I think it could be interesting to make a new list expecially for BBox ops in EfficentDet in a new ticket and instead extend the list here for image ops. But you need to double check the overlapped ops for these lists.