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Car tracking and car counter implemented with YOLOX, ByteTrack and Pytorch.

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YOLOX-ByteTrack-Car-Counter

Car tracking and car counter implemented with YOLOX, ByteTrack and Pytorch. We can take the ouput of YOLOX feed these object detections into ByteTrack in order to create a highly accurate object tracker. I have created a custom function within the file detector.py that can be used to count and keep track of the number of cars detected at a given moment within each video. In can be used to count total cars found or can count number of cars detected.

Demo of Car Counter in Action

Getting started

Pip

pip install -r requirements.txt
cd YOLOX
pip install -v -e .

Nvidia Driver

Make sure to use CUDA Toolkit version 11.2 as it is the proper version for the Torch version used in this repository: https://developer.nvidia.com/cuda-11.2.0-download-archive

torch2trt

Clone this repository and install: https://github.com/NVIDIA-AI-IOT/torch2trt

Download a pretrained model

Download pretrained yolox_s.pth file: https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.pth

Copy and paste yolox_s.pth from your downloads folder into the 'YOLOX' folder of this repository.

Convert model to TensorRT

python tools/trt.py -n yolox-s -c yolox_s.pth

Runing Car Counter with YOLOX-s

In file detector.py you need to replace the file video name in line 131: .

Then run this command:

python detector.py

References