clara-viz-widgets

A toolkit to provide GPU accelerated visualization of medical data.


Keywords
ipython, jupyter, widgets
License
Apache-2.0
Install
pip install clara-viz-widgets==0.3.2

Documentation

Clara Viz

NVIDIA Clara Viz is a platform for visualization of 2D/3D medical imaging data. It enables building applications that leverage powerful volumetric visualization using CUDA-based ray tracing. It also allows viewing of multi resolution images used in digital pathology.

Volume Rendering
Pathology

Clara Viz offers a Python Wrapper for rapid experimentation. It also includes a collection of visual widgets for performing interactive medical image visualization in Jupyter Lab notebooks.

Known issues

On Windows, starting with Chrome version 91 (also with Microsoft Edge) the interactive Jupyter widget is not working correctly. There is a delay in the interactive view after starting interaction. This is an issue with the default (D3D11) rendering backend of the browser. To fix this open chrome://flags/#use-angle and switch the backend to OpenGL.

Requirements

  • OS: Linux x86_64 or aarch64
  • NVIDIA GPU: Pascal or newer, including Pascal, Volta, Turing and Ampere families
  • NVIDIA driver: 450.36.06+

Documentation

https://docs.nvidia.com/clara-viz/index.html

Build

With docker file

This is using a docker file to build the binaries. First build the docker file used to compile the code:

docker build -t clara_viz_builder_$(uname -m) -f Dockerfile_$(uname -m).build .

Then start the build process inside the build docker image. Build results are written to the 'build' directory.

docker run --network host --rm -it -u $(id -u):$(id -g) -v $PWD:/ClaraViz \
    -w /ClaraViz clara_viz_builder_$(uname -m) ./build.sh -o build_$(uname -m)

From command line

Dependencies

git git-lfs nasm CMake 3.24.0 python3-dev python3-distutils

Build

./build.sh -o build_$(uname -m)

Use within a Docker container

Clara Viz requires CUDA, use a base container from https://hub.docker.com/r/nvidia/cuda for example nvidia/cuda:11.4.2-base-ubuntu20.04. By default the CUDA container exposes the compute and utility capabilities only. Clara Viz additionally needs the graphics and video capabilities. Therefore the docker container needs to be run with the NVIDIA_DRIVER_CAPABILITIES env variable set:

$ docker run -it --rm -e NVIDIA_DRIVER_CAPABILITIES=graphics,video,compute,utility nvidia/cuda:11.4.2-base-ubuntu20.04

or add:

ENV NVIDIA_DRIVER_CAPABILITIES graphics,video,compute,utility

to your docker build file. See https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/user-guide.html#driver-capabilities for more information.

WSL (Windows Subsystem for Linux)

Currently Clara Viz won't run under WSL because OptiX is not supported in that environment.

Acknowledgments

Without awesome third-party open source software, this project wouldn't exist.

Please find LICENSE-3rdparty.md to see which third-party open source software is used in this project.

License

Apache-2.0 License (see LICENSE file).

Copyright (c) 2020-2023, NVIDIA CORPORATION.