WisconsinAIVision/yolact_edge

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1322 stars · 274 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

YolactEdge is a PyTorch implementation of a real-time instance segmentation model optimized for edge devices like the NVIDIA Jetson AGX Xavier. It provides pretrained weights, evaluation, and training code for COCO and YouTube VIS benchmarks.

Use cases

• run real-time instance segmentation on edge devices
• segment objects in video at high FPS on a Jetson
• evaluate pretrained instance segmentation models on COCO
• train a fast instance segmentation model with a ResNet backbone
• deploy computer vision on resource-constrained hardware

When to choose

• you need real-time instance segmentation on embedded GPUs like Jetson
• you want a PyTorch codebase with pretrained COCO/YouTube VIS weights
• you can leverage TensorRT for maximum edge inference speed

When to avoid

• you need a maintained library with frequent updates (last release 2022)
• you need panoptic or semantic segmentation rather than instance segmentation
• you only target CPU-only or non-NVIDIA hardware

Facets

library · maturity maintenance

machine-learning computer-vision image-processing computer-vision deep-learning machine-learning python embedded instance-segmentation real-time-inference edge-devices pytorch tensorrt yolact jetson linux gpu

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For agents

markdown · JSON · MCP: product_card(name="WisconsinAIVision/yolact_edge")