Using yolov5 and deepsort to detect project, which you can choose any class(any class in coco dateset)
- ubuntu 16.04
- python >=3.7
- cuda 10.0
- cudnn 7.6.5
- opencv-python 4.2.0.34
- pytorch 1.5.1
- torchvision 0.6.1
conda create -n yolov5 python=3.7
conda activate yolov5
git clone https://github.com/Eyren/Deepsort_Yolov5_Pytorch.git Deepsort_yolov5
cd Deepsort_Yolov5_Pytorch-master
pip install -r requirements.txt
- put the video or image sequence folder you want to test in demo folders.
python yolov5_deepsort.py demo/*.mp4(demo/img) --clsnum 2)
tips: clsnum default is car(2), you can check configs/coco.names to select class name, it count begin 0.(person is 0, bicycle is 1...)
dhpdong, eyren