Docker
内容
Docker¶
To get started with YOLOv5 🚀 in a Docker image follow the instructions below. Other quickstart options for YOLOv5 include our Colab Notebook 
and a GCP Deep Learning VM.
1. Install Docker and Nvidia-Docker¶
Docker images come with all dependencies preinstalled, however Docker itself requires installation, and relies of nvidia driver installations in order to interact properly with local GPU resources. The requirements are:
Nvidia Driver >= 455.23 https://www.nvidia.com/Download/index.aspx
Nvidia-Docker https://github.com/NVIDIA/nvidia-docker
Docker Engine - CE >= 19.03 https://docs.docker.com/install/
2. Pull Image¶
The Ultralytics YOLOv5 DockerHub is https://hub.docker.com/r/ultralytics/yolov5 
ultralytics/yolov5:latest image hosted on the DockerHub will always be in sync with the most recent repository commit. To pull this image:
sudo docker pull ultralytics/yolov5:latest
3. Run Container¶
Run an interactive instance of this image (called a “container”) using -it:
sudo docker run --ipc=host -it ultralytics/yolov5:latest
Run a container with local file access (like COCO training data in /coco) using -v:
sudo docker run --ipc=host -it -v "$(pwd)"/coco:/usr/src/coco ultralytics/yolov5:latest
Run a container with GPU access using --gpus all:
sudo docker run --ipc=host --gpus all -it ultralytics/yolov5:latest
4. Run Commands¶
Run commands from within the running Docker container, i.e.:
$ python train.py # train a model
$ python test.py --weights yolov5s.pt # test a model for Precision, Recall and mAP
$ python detect.py --weights yolov5s.pt --source path/to/images # run inference on images and videos