More ResNet backbones for Faster R-CNN and Mask R-CNN
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- Dominant language
- Python
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Description
🚀 Feature
More ResNet backbones (e.g., resnet18, resnet34, and resnet101) for Object Detection and Instance Segmentation.
Motivation
Detectron2 provides a curated list of pre-trained detectors with having different backbones. However, I believe that the implementation of object detectors in torchvision is intriguingly easy to play around and plug into users' systems to solve their problems. Still, there is a limited choice of backbone for Faster R-CNN and Mask R-CNN.
Is there any reason behind not supporting pre-trained models with such backbones or any future plan?
Many thanks for making educationally understandable and clean codebases, and I'm really looking forward to your reply.
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
The issue names Faster R-CNN and Mask R-CNN but does not identify files, tests, or entry points. Start by locating their existing backbone and pretrained-model implementations, then compare how current backbones are registered and tested. Done means the requested ResNet variants are supported for the relevant detection and segmentation models with working pretrained weights.
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
- 32/100