For tutorials that are marked to use either Anaconda or Jupyter Notebook, using Anaconda is recommended.
Anaconda can be used on Linux (inc. on ChromeOS), Windows and MacOS. Please follow the official installation instructions for individual machines.
After installing Anaconda, one needs to set up the environment with additional libraries. The simplest way to install the useful packages is to use the Anaconda Prompt for Windows, or in a terminal window for macOS or Linux. Create a new mphy0043
environment:
conda create --name mphy0043 tensorflow==2.9
In the activated mphy0043
, install other useful libraries:
conda activate mphy0043
pip install notebook matplotlib av "monai[nibabel, gdown, ignite]" # monai includes PyTorch
Installation of TensorFlow and PyTorch can be OS-dependent, especially for GPU-enbaled versions. Please refer to their official documentations if any issue on individual machines.
Some tutorials are written in Python scripts, which can be run at the Anaconda Prompt for Windows or in a terminal window for macOS or Linux with the activated mphy0043
, by typing the command line commands, e.g.:
python video_classification.py
After installing Anaconda and setting up the conda environment, there are different ways to start the Jupyter Notebook in mphy0043
, for example:
- Start Anaconda Navigator;
- Select the created
mphy0043
in the drop-down menu "Applications on ..."; - Launch the Jupyter Notebook in the below tab;
- Select to open the notebook files with .ipynb extension, using the browser-based interface.
The links to upload the notebooks to Colab may be provided but not technically supported in this module. Stable internet connection is required.
For those experienced, direct use of miniconda and Jupyter Notebook should also work for those materials that are marked with Anaconda and Jupyter Notebook, respectively. However, technical support may not be available from this module.