Mask R-CNN with MobileNet v3 backbone
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- Dominant language
- Python
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Description
🚀 Feature
Add Mask R-CNN with MobileNet v3 backbone
Motivation
In the recent release torchvision added support for mobilenet v3 and extended it to work with instance segmentation models.
torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpn
However, support for Mask R-CNN with MobileNet v3 backbone is still missing and would be a worthy addition.
Pitch
- Similar module like
torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpnbut to work with Mask R-CNN like resnet hastorchvision.models.detection.maskrcnn_resnet50_fpn - MobileNet V3 would make inference much faster
- Mask R-CNN is widely used owing to its dual use of getting mask+bounding box
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 comparing the existing torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpn and torchvision.models.detection.maskrcnn_resnet50_fpn entry points and their surrounding implementation. Trace how the MobileNet V3 backbone is connected to the instance-segmentation components. Done means a Mask R-CNN entry point using MobileNet V3 supports both masks and bounding boxes with coverage comparable to the existing model.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100