weecology / weecology/DeepForest
Clarify that multi-class example isn't expected to yield predictions
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- Dominant language
- Python
- Stars
- 774
- Forks
- 265
- PR merge metrics
- No merged PRs in 30d
Description
Our current multi-class example in the docs trains on a single image for 1 epoch. It unsurprisingly doesn't learn anything and therefore predicts zero trees. This is confusing - see #773. We should clarify this in the docs and perhaps provide an idea of how many epochs the example would have to be trained for to show any results (~500 and then it only predicts dead trees).
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
Open the multi-class example at advanced_features/multi_species.html and review the section describing training for one epoch. Clarify that the single-image, one-epoch example is not expected to produce predictions, and include the approximate training context mentioned in the issue. Done means the documentation sets expectations clearly for the example’s zero-tree output.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 68/100