Lightning-AI / Lightning-AI/torchmetrics
F score over boundaries
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.5k
- Forks
- 526
- Avg merge
- 6d 11h
- Merged PRs (30d)
- 5
Description
## 🚀 Feature
An F score over the boundaries.
It will requires boundaries extraction on multiclass tensors.
### Motivation
It is used in many Video dataset and their related challenges (Davis, Yotube VOS, etc.).
### Pitch
Generally we have opencv/script/numpy implementations but it could be very useful to have a metrics directly to plug in the eval step.
### Alternatives
Implementing BoundaryIOU
https://bowenc0221.github.io/boundary-iou/
### Additional context
F-boundary Reference implementation:
https://github.com/davisvideochallenge/davis2017-evaluation/blob/master/davis2017/metrics.py
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
Start by reading the referenced DAVIS implementation in davis2017/metrics.py and compare it with the Boundary IoU alternative linked in the issue. Define the multiclass tensor boundary-extraction behavior and verify that the resulting F-boundary metric can be plugged into the evaluation step.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, opencv, python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100