WisconsinAIVision/yolact_edge
A real-time instance segmentation model optimized to run on edge devices like Jetson AGX Xavier.
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YolactEdge is a competitive instance segmentation approach designed to run on small edge devices at real-time speeds. Built with PyTorch, it achieves up to 30.8 FPS on Jetson AGX Xavier and 172.7 FPS on RTX 2080 Ti using a ResNet-101 backbone at 550x550 resolution. The project provides model weights and inference code for deploying instance segmentation on resource-constrained hardware.
Frequently asked
- What is WisconsinAIVision/yolact_edge?
- A real-time instance segmentation model optimized to run on edge devices like Jetson AGX Xavier.
- Is yolact_edge open source?
- Yes — WisconsinAIVision/yolact_edge is open source, released under the MIT license.
- What language is yolact_edge written in?
- WisconsinAIVision/yolact_edge is primarily written in Python.
- How popular is yolact_edge?
- WisconsinAIVision/yolact_edge has 1.3k stars on GitHub.
- Where can I find yolact_edge?
- WisconsinAIVision/yolact_edge is on GitHub at https://github.com/WisconsinAIVision/yolact_edge.