Docker Quickstart

To get started using this repo quickly using our latest Docker Image follow the instructions below. Other quickstart options for this repo include our Jupyter 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 >= 440.44
• Nvidia-Docker https://github.com/NVIDIA/nvidia-docker
• Docker Engine - CE >= 19.03 https://docs.docker.com/install/

2. Pull Image

The Ultralytics YOLOv3 dockerhub is https://hub.docker.com/r/ultralytics/yolov3 . The most recent image available is always ultralytics/yolov3:latest. To pull this image:

sudo docker pull ultralytics/yolov3:latest

3. Run Container

Run an interactive instance of this image (called a "container"):

sudo docker run --gpus all --ipc=host -it ultralytics/yolov3:latest

4. Run Container with Local Directory Access

To run a container with access to local files (like COCO training data in /coco) run:

sudo docker run --gpus all --ipc=host -it -v "$(pwd)"/coco:/usr/src/coco ultralytics/yolov3:latest

5. Run Commands

Once the container is launched and you are inside it, you will have a terminal window in which you can run all regular bash commands, such as:

• ls .
• ls ../coco
• python train.py
• python test.py
• python detect.py