This is a tool to run a model reviewer in a docker container, to decouple model reviewing from the VOTT application, in order to keep the application light-weight
> docker pull user1m/vott-reviewer-cntk:cpu
> git clone https://github.com/User1m/vott-reviewer-ext.git
> cd vott-reviewer-ext
> export MODEL_PATH=/absolute/path/to/cntk/model/
> ./docker/scripts/run.prod.sh cpu (or gpu)
- NOTE: Your cntk model path must be mapped to the container's
/workdir/model/
path - In the
/workdir/model/
should be a.model
file AND aclass_map.txt
file from your training - This will expose an endpoint on
127.0.0.1:3000/cntk
. Plug this endpoint into VOTT and review.
NOTE - If you have a GPU machine w/ nvidia installed you might run into an issue w/ nvidia-docker
& creating the container. This is due to the fact that the host already contains nvidia-cuda-toolkit
binaries, found in ls -la /usr/bin/nvidia-*
, and the container tries to mount it's nvidia
binaries over the existing ones.
A current workaround is to rename some of the host nvidia
files found in /usr/bin/nvidia-*
so that the container can be created, then you can rename them back after container is created.
!! See run.prod.sh for an example of this.
> curl \
-F "image=@/home/user1/Desktop/test.jpg" \
localhost:3000/cntk