magic4wei/dearpygui repository overview

⁠Usage

⁠Explore DearPyGui Base Images

DearPyGui base images are built from Miniconda base image magic4wei/miniconda:*-gui. A new conda environment is created to install required Python version and DearPyGui package. By default, the name of the new conda environment is gui_dev.

Everything else is identical to the Miniconda base image magic4wei/miniconda:miniconda3-latest-ubuntu<XX>.04-gui (see magic4wei/miniconda⁠).

Explore DearPyGui base images by running

docker run -it --rm magic4wei/dearpygui:base-py3.9-ubuntu18.04
docker run -it --rm magic4wei/dearpygui:base-py3.9-ubuntu20.04

⁠Work with OpenGL Rendering

DearPyGui requires OpenGL rendering.

Before you go through this tutorial, make sure that

• at least one GPU is mounted on your machine
• GPU driver is installed correctly
• You can run glxgears in terminal without any error (package mesa-utils is needed)

Firstly, you need to run xhost + on your host machine to enable X client display.

For Intel GPU, simply run

docker run -it --rm \
-e DISPLAY=$DISPLAY \
-v /tmp/.X11-unix:/tmp/.X11-unix:rw \
--privileged \
--device=/dev/dri:/dev/dri \
magic4wei/dearpygui:base-py3.9-ubuntu18.04

For Nvidia GPU, it is a little bit more complicated. We need to connect Nvidia driver volume when docker image runs, and add Nvidia OpenGL library path to LD_LIBRARY_PATH inside the container. If you want to run Nvidia executable tools like nvidia-smi, you also need to add their path to PATH inside the container.

For example, I have installed Nvidia driver nvidia-430 at /usr/lib/nvidia-430 and /usr/lib32/nvidia-430 (32-bit compatible libraries), and all my Nvidia tools are located at /usr/lib/nvidia-430/bin. Two steps to enable OpenGL rendering in container:

1. Run image with Nvidia driver volume bindings

docker run -it --rm \
-e DISPLAY=$DISPLAY \
-v /tmp/.X11-unix:/tmp/.X11-unix:rw \
--privileged \
-v /usr/lib/nvidia-430:/usr/hostLib/lib/nvidia \
-v /usr/lib32/nvidia-430:/usr/hostLib/lib32/nvidia \
magic4wei/dearpygui:base-py3.9-ubuntu18.04

1. Add Nvidia OpenGL library path in the container

export LD_LIBRARY_PATH=/usr/hostLib/lib/nvidia:/usr/hostLib/lib32/nvidia:${LD_LIBRARY_PATH} # required for OpenGL rendering
export PATH=/usr/hostLib/lib/nvidia/bin:${PATH} # optional, add this if you want to run tools like nvidia-smi

Then you are able to run DearPyGui or other GUI applications that requires OpenGL rendering in the container. For example,

# Example: Run glxgears (needs `mesa-utils`, already installed in GUI base images)
glxgears