Generalize masks_to_boxes op to support N-dimensional masks to bounding boxes conversion
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- Dominant language
- Python
- Stars
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Description
🚀 The feature
Ops to convert N-dimensional segmentation masks to N-dimensional bounding boxes.
Motivation, pitch
Build upon #3960 to support the conversion of N-dimensional asks to bounding boxes.
Use cases:
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I have 3D images (from medical imaging) and would like to convert segmentation masks (of tumors, aneurysms, etc.) to bounding boxes.
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Sometimes different sources of data are stacked together, giving me 4D images (3D images, stacked along a new dimension to make the image source clear). I would also like to convert these segmentation masks to bounding boxes, although I will admit, I would compute bounding boxes in 3D and then stack those as well.
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 reviewing the existing masks_to_boxes operation referenced through #3960. Define how N-dimensional segmentation masks should map to bounding boxes, including the 3D and 4D medical-imaging cases; done means the requested dimensional conversions are supported and covered by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100