Project-MONAI / Project-MONAI/MONAILabel
Dropout and MC dropout for U-Net segmentation
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- Dominant language
- Python
- Stars
- 891
- Forks
- 269
- Avg merge
- 15h 41m
- Merged PRs (30d)
- 1
Description
If I create a Unet model and use an inferer, does this automatically turn off dropout at inference?
If so, what can I do to turn on dropout at inference? I want to quantify the uncertainty in predictions using this but didn't really finding anything related to this
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 tracing how the U-Net model and inferer handle dropout during inference, since the issue does not name a file or test. Determine the expected behavior for enabling Monte Carlo dropout and document or expose that behavior with coverage for repeated uncertainty-inference predictions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100