tunnm/caffe repository overview

⁠Running an official image

You can run one of the automatic builds⁠. E.g. for the CPU version:

docker run -ti tunnm/caffe:cpu caffe --version

or for GPU support (You need a CUDA 8.0 capable driver and nvidia-docker⁠):

nvidia-docker run -ti tunnm/caffe:gpu caffe --version

You might see an error about libdc1394, ignore it.

⁠Docker run options

By default caffe runs as root, thus any output files, e.g. snapshots, will be owned by root. It also runs by default in a container-private folder.

You can change this using flags, like user (-u), current directory, and volumes (-w and -v). E.g. this behaves like the usual caffe executable:

docker run --rm -u $(id -u):$(id -g) -v $(pwd):$(pwd) -w $(pwd) tunnm/caffe:cpu caffe train --solver=example_solver.prototxt

Containers can also be used interactively, specifying e.g. bash or ipython instead of caffe.

docker run -ti tunnm/caffe:cpu ipython
import caffe
...

The caffe build requirements are included in the container, so this can be used to build and run custom versions of caffe. Also, caffe/python is in PATH, so python utilities can be used directly, e.g. draw_net.py, classify.py, or detect.py.

⁠Building images yourself

Examples:

docker build -t caffe:cpu cpu

docker build -t caffe:gpu gpu

You can also build Caffe and run the tests in the image:

docker run -ti caffe:cpu bash -c "cd /opt/caffe/build; make runtest"