SGP 2025 Graduate School

Deep learning on meshes and point clouds

Ruben Wiersma

Instructions

Skip to instructions for Visual Studio Code

For this tutorial, you'll need to install Jupyter in your Python environment. We will install the rest of the required packages from the notebook, so you can also run the code on online services like Google Colab.

Option 1 (separate environment with conda)

If you have conda installed (instructions on how to install Miniconda), you can run the following command in your terminal to create the right environment and install Jupyter:

conda create -n sgp_dl python=3.12 jupyter

To run the notebook:

cd [root_folder]
conda activate sgp_dl
jupyter notebook

Option 2 (only pip)

If you don't like to use conda or use a different environment manager, you can also just use pip to install Jupyter and proceed with the tutorial. Install Jupyter:

pip install jupyter

To run the notebook:

cd [root_folder]
jupyter notebook

Starting the tutorial

The jupyter notebook command starts the Jupyter server and opens the Jupyter interface in your browser. If you don't see it, check your terminal for instructions on where to go. It's often located at http://localhost:8889

Then click on sgp_dl_tutorial.ipynb in the Jupyter file browser and follow the instructions in the notebook.

Alternative in Visual Studio Code

You can also run the notebook within Visual Studio Code. First, create the conda environment with the right Python version and Jupyter:

conda create -n sgp_dl python=3.12 jupyter

Then, open sgp_dl_tutorial.ipynb in Visual Studio Code, select the sgp_dl environment in the top-right corner ("Select Kernel" $\rightarrow$ "Python Environments") and go through the notebook step-by-step. If you didn't use conda, but installed Jupyter in your default Python installation, you can select that environment (if you don't know where it's installed, run which python in your terminal).