weecology / weecology/DeepForest
Eliminate the custom eval code
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- Dominant language
- Python
- Stars
- 774
- Forks
- 265
- PR merge metrics
- No merged PRs in 30d
Description
Revisiting the pull request #504, torchmetrics wasn't quite ready to be swapped in for all our evaluation, see that thread and the corresponding issue. I think it can be re-evaluated after looking at the repo and answered from
https://github.com/Lightning-AI/torchmetrics/discussions/2152#discussioncomment-11918240
Torchmetrics is standardized, testing and scalable, our code is not. For a matcher example, see the torchvision matcher class used in MillionTrees.
Roadmap
- Implement IOU matcher and recall/precision score for a fixed threshold
- Assert that the two versions produce the same result
- Test timings of two versions
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 pull request #504, the corresponding issue, and the linked torchmetrics discussion. Use the MillionTrees torchvision matcher example as the comparison point; done means implementing the IOU matcher and fixed-threshold recall/precision, proving both versions match, and comparing their timings.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance, testing-qa
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100