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AIBA Backend for Standalone-Hardware

FastAPI-based AIBA Backend for Standalone-Hardware

Disclaimer

이 백엔드 Instance는 YOLO 및 Monocular Depth Estimation + TDoA 비디오 스트림을 위한 하드웨어용 백엔드입니다.

CUDA (엔비디아) 외 Apple Silicon (MPS) 또한 지원하나, Apple Silicon 환경에서의 YOLO-slowfast 구동은 CPU를 이용하니 (#1), CUDA 구동을 권장합니다.

Usage

실행 전, YOLO-slowfast 모델을 yolo/deep_sort/deep_sort/deep/checkpoint/ckpt.t7 에, Mono Depth Estimation 모델을 vision/weights/dpt_swin2_tiny_256.pt 에 넣어주세요.

Initial Run

conda create -n {your_env_name} python=3.9

pip install -r requirements.txt

Run

uvicorn --host=0.0.0.0 app:app

Troubleshooting

If CUDA or Pytorch doesn't work, try this

pip3 install —pre torch torchvision torchaudio —index-url https://download.pytorch.org/whl/nightly/cu121

When PyTorch Apple Silicon backend (MPS) doesn't work, add this variable

conda env config vars set PYTORCH_ENABLE_MPS_FALLBACK=1