|
|
--- |
|
|
license: mit |
|
|
--- |
|
|
|
|
|
Re-upload of the classic 2019 hit model, YOLACT, in case you wanted to relive real-time instance segmentation with a retro vibe. |
|
|
|
|
|
These are the initial weights files described in the readme of the YOLACT github. |
|
|
|
|
|
🔬 **Papers:** |
|
|
- [YOLACT: Real-time Instance Segmentation (2019)](https://arxiv.org/abs/1904.02689) |
|
|
- [YOLACT++: Better Real-time Instance Segmentation (2020)](https://arxiv.org/abs/1912.06218) |
|
|
|
|
|
💻 **Run the code:** [dbolya/yolact](https://github.com/dbolya/yolact) |
|
|
|
|
|
🚀 **Download this checkpoint:** |
|
|
- [resnet101_reducedfc.pth](https://huggingface.co/dbolya/yolact-initial-weights/resolve/main/resnet101_reducedfc.pth?download=true) |
|
|
- [resnet50-19c8e357.pth](https://huggingface.co/dbolya/yolact-initial-weights/resolve/main/resnet50-19c8e357.pth?download=true) |
|
|
- [darknet53.pth](https://huggingface.co/dbolya/yolact-initial-weights/resolve/main/darknet53.pth?download=true) |
