- This image builds a multi-modal environment for use in jupyter-lab
- The multimodality in question is mostly diffusion architectures.
- The image builds opencv from source code to have cuda support.
- You can then run the cv algorithms using the GPU for faster processing.
- This will serve you well if you can deploy the container to a remote server.
.
└── computer-vision-docker-image
├── dependecies
│ ├── mm-requirements.txt
│ ├── ubuntu-deps.sh
│ └── opencv.sh
├── test-code
│ ├── controlnet.ipynb
│ └── stable-diffusion.ipynb
├── Dockerfile
├── docker-compose.yml
└── ReadME.md
docker-compose build
If you need to make updates to the content of the container, e.g. installing new packages with pip- you can specify these in the cv-requirements.txt file in the dependencies folder.
docker-compose up