ffcv integration
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 17.9k
- Forks
- 7.3k
- Avg merge
- 1d 15h
- Merged PRs (30d)
- 13
Description
🚀 The feature
Integrate https://github.com/libffcv/ffcv for accelerated image decoding, preprocessing and loading
Motivation, pitch
I maintain torchserve, we've recently had customers complain about slow image preprocessing decoding https://github.com/pytorch/serve/issues/1546 - the performance implications are large. It's possible for me to solve them locally in torchserve but solving them a level higher in torchvision means anyone can benefit from the improvements
Summarizing discussion with @NicolasHug
Alternatives
Some alternatives exist like DALI
There's also the do nothing alternative where we just provide a tutorial in ffcv instead of having a tight integration
Additional context
If this is a reasonable first issue to torch/vision I can pick this up
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not identify files, tests, or an entry point. Start by reviewing torchvision's dataset, transform, and image-loading components and the proposed ffcv integration, then define the integration boundary, supported workflows, and validation needed to demonstrate accelerated decoding and preprocessing.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100