VascX models
This repository contains the instructions for using the VascX models from the paper VascX Models: Model Ensembles for Retinal Vascular Analysis from Color Fundus Images.
The model weights are in huggingface.
Installation
To install the entire fundus analysis pipeline including fundus preprocessing, model inference code and vascular biomarker extraction:
Create a conda or virtualenv virtual environment, or otherwise ensure a clean environment.
Install the rtnls_inference package.
Usage
To speed up re-execution of vascx we recommend to run the preprocessing and segmentation steps separately:
Preprocessing. See this notebook. This step is CPU-heavy and benefits from parallelization (see notebook).
Inference. See this notebook. All models can be ran in a single GPU with >10GB VRAM.