Single channel support for optical flow
Open
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
Would love to be able to run black and white images through the new RAFT optical flow model! (Same goes for ResNet)
Motivation, pitch
I have a B+W dataset. Duplicating channels feels wasteful.
Alternatives
No response
Additional context
No response
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
Locate the RAFT optical flow and ResNet model entry points and inspect how they validate or consume image channels. Determine the expected behavior for black-and-white inputs without duplicating channels, then add coverage for both models and run the relevant model tests. Done means the models accept the stated single-channel dataset while existing multi-channel behavior remains intact.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100