Docker Python3-Tensorflow-OpenCV3

A docker version with python3, tensorflow:lastest and opencv 3 for compile and test everything Tensorflow-OpenCV based application

Execute scripts

The following script will execute the scripts /script/to/run; /or/set/of/them as if they were run on your machine.

In order to see what is going inside the docker we need to sync the displays with:

--env DISPLAY=$DISPLAY --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" if you use Linux based systems.

-e DISPLAY=${HOST_IP}:0 if you use OSX systems.

Also, we will share the source code directories -v=$(pwd)/..:$(pwd)/.. (this assumes you are doing an out-of-source build and you have a parent directory with the build and src as children). And we set the current directory as our working directory -w=$(pwd).

CPU version:

docker run -it --rm \
  --env DISPLAY=$DISPLAY --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
  -v=$(pwd)/..:$(pwd)/.. -w=$(pwd) \
  tensorflow-opencv-cpu-py3 \
  /script/to/run; /or/set/of/them

GPU version:

nvidia-docker run -it --rm \
  --env DISPLAY=$DISPLAY --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
  -v=$(pwd)/..:$(pwd)/.. -w=$(pwd) \
  tensorflow-opencv-gpu-py3 \
  /script/to/run; /or/set/of/them

or if you want enter in the image use the Makefile commands:

Enter cpu version

make run-cpu

Enter cpu version

make run-gpu

Build the image locally

You can build the image locally by executing the Makefile

Creating cpu version

make build-cpu

Creating gpu version

make build-gpu

Based on this repo