Comments (6)
We have some interesting code to port into data augs libs like albumentations
and
Maybe we can try to build something like that here:
ComposeOps
- generalized
TransformPipeline
Certainly it wont support all your augs, only DALI ones, but this could help user to avoid copying common stuff.
@albu @ternaus what do you think ?
I can try to provide a draft PR if you are interested.
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From my perspective, most probably not. DALI has they own augmentation pipeline which is not compatible with albumentations API. Therefore support of DALI would require to introduce breaking changes in albumentations with doubtful outcome.
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I want to try it and figure it out if we can simplify DALI usage because it's really cool but really weird
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any progress @albu
from albumentations.
sorry, no progress here
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I have an additional example of the usage here - it really brings DALI usage inline with Albumentations/PyTorch Compose usage, so would be very cool to have integrated
Usability wise this code is a super handy way of dropping GPU acceleration as a nearly 'drop in' replacement to existing PyTorch/Albumentations workloads - we just need to find a home for it.
Take a look! Here is another Colab:
https://colab.research.google.com/drive/1XDRzDeIeteTPyzYbZp2XWjKtUWMLXqcg
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Related Issues (20)
- [it may be a bug but I am not sure] rotating and cropping adding in pixels HOT 4
- keypoint position shifting during image rotation HOT 3
- Data loading does not start when num_workers > 0 in 1.4.10 HOT 4
- [Benchmark] Add transforms from Kornia HOT 1
- [Tech Debt, Speedup] Move to_float to albucore
- ISONoise not working in 1.4.10 HOT 1
- [Bug] Issue in RandomCrop HOT 1
- Coarse Dropout ignores remove_invisible parameter
- [Feature request] Add LetterBox
- Affine rotate shear after the picture frame does not overlap the object HOT 4
- Yolo bbox conversion produces negative values HOT 3
- Too noisy upgrade warning HOT 12
- AttributeError: 'Compose' object has no attribute 'strict' HOT 5
- How is the pad_cval defined of CropAndPad? HOT 1
- Image and mask augmentations cause error when converting NumPy to PyTorch - [ValueError: At least one stride in the given numpy array is negative, and tensors with negative strides are not currently supported.] HOT 5
- [Benchmark] unable to test the given dataset ILSVRC2012_img_val or owndataset to test the image_benchmark.py with. HOT 2
- Grid-based Elastic Transformation HOT 1
- Root logger conflict with my custom logging structure HOT 2
- HistogramMatching returns wrong image HOT 3
- Mistyping in validation of `ColorJitter` transform HOT 1
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