QuPath for Python programmers 🐍

These are the notebooks and associated files for the i2k 2024 QuPath for Python programmers workshop.

This is a brief introduction to QuBaLab and the QuPath Py4J extension, a new way to quickly link Python and QuPath.

Running the notebooks

1. Download the latest QuPath v0.6.0 release candidate from the github releases page.
2. Download the QuPath project for this workshop.
3. Unzip the project in the i2k-qupath-for-python-programmers directory
4. Create a conda environment (bash):
   1. conda create -n i2k-qupath-python python=3.10
   2. conda activate i2k-qupath-python
   3. Install the requirements, either by
      • pip install -r requirements.txt, or
      • pip install instanseg-torch git+https://github.com/qupath/qubalab.git jupyter ipython leidenalg igraph umap-learn.
5. Open QuPath v0.6.0
6. Start a py4j gateway with default parameters
7. Open the i2k-qupath-python-project in QuPath
8. Open HE_Hamamatsu.tiff in QuPath
9. Start a jupyter session using the virtual environment from earlier
10. Run the qupath-for-python-programmers.ipynb notebook
11. Open patient_test_2.ome.tiff in QuPath and select the annotation
12. Run the clustering-objects.ipynb notebook