docker (recommanded):
# create the docker container, you can change the share memory size if you have more.
nvidia-docker run --name yolov4 -it -v your_coco_path/:/coco/ -v your_code_path/:/yolo --shm-size=64g nvcr.io/nvidia/pytorch:20.11-py3
# apt install required packages
apt update
apt install -y zip htop screen libgl1-mesa-glx
# pip install required packages
pip install seaborn thop
# install mish-cuda if you want to use mish activation
# https://github.com/thomasbrandon/mish-cuda
# https://github.com/JunnYu/mish-cuda
cd /
git clone https://github.com/JunnYu/mish-cuda
cd mish-cuda
python setup.py build install
# go to code folder
cd /yolo
local:
pip install -r requirements.txt
※ For running Mish models, please install https://github.com/thomasbrandon/mish-cuda
python train.py --device 0 --batch-size 16 --img 640 640 --data coco.yaml --cfg cfg/yolov4-pacsp.cfg --weights '' --name yolov4-pacsp
python test.py --img 640 --conf 0.001 --batch 8 --device 0 --data coco.yaml --cfg cfg/yolov4-pacsp.cfg --weights weights/yolov4-pacsp.pt