DeepLabCut / DeepLabCut/DeepLabCut-live-GUI
Have multiple parallel processors - or inference on multiple cameras
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 72
- Forks
- 28
- Avg merge
- 1d 10h
- Merged PRs (30d)
- 2
Description
Currently the system is designed to have a single processor that works on a single camera stream.
It would be useful to have multiple processors running in parallel. Or as a step towards that: have the ability to run inference on multiple cameras.
Contributor guide
No contributing guide indexed for this repository
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 names no files, tests, or entry points. Start by tracing how the GUI connects one processor to one camera stream and how inference is scheduled. Define the intended behavior for multiple processors and multiple cameras before implementation, including what successful parallel processing should look like.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- desktop, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100