facebookresearch / facebookresearch/segment-anything
Using a mask prompt for boundary refinement
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Description
Hi, I have a roughly labeled dataset and trying to feed it's labels as a prompt into SAM. I want SAM to refine the segmentation labels and improve my dataset quality. In my case I don't use any additional prompt artifacts like points or boxes (though it works pretty good for such prompts). It seems to me that a pure mask prompt should be supported as well, according to the paper. But the results I obtain are kinda unreliable, an output mask mostly repeats an input one, even making it slightly worse. Is there a code snippet to build the prompts out of the foreign masks?
Thanks in advance!
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.
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Research direction
No specific file, test, or entry point is named. Start with the repository's example notebooks and the mask-prompt workflow described in the paper, then determine whether foreign masks can be used for reliable refinement without points or boxes. Done means a documented, reproducible mask-only workflow or a clarified limitation.
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Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100