Write text on images as an augmentation
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- Dominant language
- Python
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Description
🚀 Torchvision GPU compatible text writing on images
Hi.
Right now, I believe that if you wanna write text on a GPU Tensor, you're gonna have to do it in CPU memory.
This is unfortunate since text writing is a very good augmentation is some cases, where input data might have timestamps for example. Also, most efficient loading libraries make use of the GPU (for example Nvidia Dali, decord) for efficient loading, meaning that converting a tensor back to numpy array sacrifices this advantage they have for "large" training (when you don't have the whole dataset in RAM).
I think it'd be great if writing random text on an image was a torchvision feature :D
Alternatives
Convert the tensor it back to numpy array and use OpenCV.
cc @vfdev-5 @datumbox
Contributor guide
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Research direction
No file, test, or entry point is named. Start by locating torchvision's image augmentation and tensor-device handling, then define the supported GPU text-writing behavior and tests; done means random text can be written on GPU tensors without converting them to CPU memory.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100