weecology / weecology/DeepForest
Can't we do better than destroy the entire classification head when the annotations don't match?
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 774
- Forks
- 265
- PR merge metrics
- No merged PRs in 30d
Description
I think we can provide users with more insight than just a random instantiation of the backbone when we are running multi-class and retraining to add new labels.
https://deepforest.readthedocs.io/en/latest/advanced_features/multi_species.html
We could grab the classification head from the release model. We could get just the top layers. I think this was one of the workarounds we identified and then didn't return to.
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 with the multi-species retraining guidance at advanced_features/multi_species.html, then trace the code path used when annotations do not match during multi-class retraining. Determine the expected behavior for retaining useful portions of the release model, and define tests that show retraining no longer falls back to a random backbone in this case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100