Hyperspectral Image Segmentation

Authors: Lars Doorenbos (NVIDIA)
Supported platforms: x86_64, aarch64
Language: Python
Last modified: May 13, 2025
Latest version: 1.0
Minimum Holoscan SDK version: 0.6.0
Tested Holoscan SDK versions: 0.6.0
Contribution metric: Level 2 - Trusted

This application segments endoscopic hyperspectral cubes into 20 organ classes. It visualizes the result together with the RGB image corresponding to the cube.

Data and Models

The data is a subset of the HeiPorSPECTRAL dataset. The application loops over the 84 cubes selected. The model is the 2022-02-03_22-58-44_generated_default_model_comparison checkpoint from this repository, converted to ONNX with the script in utils/convert_to_onnx.py.

📦️ (NGC) App Data and Model for Hyperspectral Segmentation. This resource is automatically downloaded when building the application.

Run Instructions

This application requires some python modules to be installed. You can simply use Holohub CLI to build and run the application.

./holohub run hyperspectral_segmentation

This single command builds and runs a Docker container, then inside that container, it builds and runs the application.

To build and run the container without building the application, you can use the following command:

./holohub run-container hyperspectral_segmentation

Viewing Results

With the default settings, the results of this application are saved to result.png file in the hyperspectral segmentation app directory. Each time a new image is processed, it overwrites result.png. By opening this image while the application is running, you can see the results as the updates are made (may depend on your image viewer).