Lightning-AI / Lightning-AI/torchmetrics
Pose estimation metrics
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.5k
- Forks
- 526
- Avg merge
- 6d 11h
- Merged PRs (30d)
- 5
Description
## 🚀 Feature
### Motivation
Currently torchmetrics doesn't support any metrics for pose estimation, example AP for pose estimation which is used for COCO and reported in all pose estimation code/papers such as:
https://github.com/facebookresearch/sapiens
https://github.com/Tau-J/rtmlib
### Pitch
Let's add pose estimation metrics to torchmetrics to make it more feature rich
### Alternatives
One alternative for users is to write the metric themselves
I can work on this if agreed
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
No source file, test, or entry point is identified. Start by reviewing the existing torchmetrics metric structure and the pose-estimation AP use cases linked in the issue, then clarify which metrics and COCO behavior are required. Done should mean an agreed, implemented pose-estimation metric scope with corresponding validation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100