Installation

Simply clone and install the package as follows:

git clone https://github.com/mahmoodlab/HEST.git
cd HEST
conda create -n "hest" python=3.11
conda activate hest
pip install -e .

Optional: HEST-Benchmark dependencies

To run HEST-Benchmark (including TRIDENT patch encoders), install benchmark extras:

pip install -e ".[benchmark]"

Many benchmark encoders are hosted on Hugging Face and may be gated. Request access where needed and authenticate in your environment:

huggingface-cli login

Additional dependencies (for WSI manipulation):

sudo apt install libvips libvips-dev openslide-tools

Install CuImage for GPU acceleration

For CuImage support (GPU accelerated library), follow the instructions provided by Nvidia.

Example for Cuda 12.1:

pip install \
    --extra-index-url=https://pypi.nvidia.com \
    cudf-cu12==24.6.* dask-cudf-cu12==24.6.* cucim-cu12==24.6.* \
    raft-dask-cu12==24.6.*

NOTE: HEST-Library was only tested on Linux/macOS machines, please report any bugs in the GitHub issues.