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| # ByteTrack-TensorRT in Python | |
| ## Install TensorRT Toolkit | |
| Please follow the [TensorRT Installation Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html) and [torch2trt gitrepo](https://github.com/NVIDIA-AI-IOT/torch2trt) to install TensorRT (Version 7 recommended) and torch2trt. | |
| ## Convert model | |
| You can convert the Pytorch model “bytetrack_s_mot17” to TensorRT model by running: | |
| ```shell | |
| cd <ByteTrack_HOME> | |
| python3 tools/trt.py -f exps/example/mot/yolox_s_mix_det.py -c pretrained/bytetrack_s_mot17.pth.tar | |
| ``` | |
| ## Run TensorRT demo | |
| You can use the converted model_trt.pth to run TensorRT demo with **130 FPS**: | |
| ```shell | |
| cd <ByteTrack_HOME> | |
| python3 tools/demo_track.py video -f exps/example/mot/yolox_s_mix_det.py --trt --save_result | |
| ``` | |