LSH9832/edgeyolo
EdgeYOLO is an anchor-free real-time object detector designed for edge devices, achieving 34-53 FPS on embedded hardware with decent accuracy.
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EdgeYOLO is a PyTorch-based anchor-free object detection model optimized for edge computing scenarios. It supports deployment on multiple platforms including Nvidia Jetson, Huawei Ascend, Rockchip RK3588, and various inference runtimes like TensorRT, ONNX, MNN, RKNN, and OpenVINO. The project provides training code and pre-trained models achieving 50.6% AP on COCO2017 at real-time speeds.
Frequently asked
- What is LSH9832/edgeyolo?
- EdgeYOLO is an anchor-free real-time object detector designed for edge devices, achieving 34-53 FPS on embedded hardware with decent accuracy.
- Is edgeyolo open source?
- Yes — LSH9832/edgeyolo is open source, released under the Apache-2.0 license.
- What language is edgeyolo written in?
- LSH9832/edgeyolo is primarily written in Python.
- How popular is edgeyolo?
- LSH9832/edgeyolo has 525 stars on GitHub.
- Where can I find edgeyolo?
- LSH9832/edgeyolo is on GitHub at https://github.com/LSH9832/edgeyolo.