Dockerfile to run mask RCNN with GPU Support

Matterport's Mask RCNN library points to a docker image with CPU only support. Here I create a Dockerfile that supports the tensorflow backend with Mask RCNN, with Nvidia GPU support.

Acknowledgements: The keras team provides a great image at their repo, however it doesn't have opencv-python and a few other libraries. Compiling OpenCV in a docker image. Building OpenCV from source times out Docker Hub since it requires a high number of threads to complete in a reasonable time -- so instead I choose cv2 and opencv-python rather than heavyweight build OpenCV 3.

The Dockerfile also adds a new /workspace directory to work out of, and some developer tools (courtesy of waleedka at his image.

Running the image and mounting current directory to /workspace

To run combined docker container with nvidia gpu support (assuming nvidia-docker): docker run -it --runtime=nvidia --net=host --env KERAS_BACKEND=tensorflow -v .:/workspace ketkar/ml-docker:latest /bin/bash To run jupyter notebook only in the container: docker run -it --runtime=nvidia --net=host --env KERAS_BACKEND=tensorflow -v .:/workspace ketkar/ml-docker:latest jupyter notebook --NotebookApp.token=

To run jupyter notebook in container after it has started (with flags to avoid password prompt) jupyter notebook --NotebookApp.token=