R2PA

Setup

The easiest way to setup an environment is to use Miniconda.

Using Miniconda

1. Install Miniconda (make sure to use a Python 3 version)
2. After setting up miniconda you can make use of the conda command in your command line (Powershell, CMD, Bash)
3. We suggest that you set up a dedicated environment for this project by running conda env create -f environment.yml
   • This will setup a virtual conda environment with all necessary dependencies.
   • If your device does have a GPU replace tensorflow with tensorflow-gpu in the environement.yml
4. Depending on your operating system you can activate the virtual environment with conda activate r2pa.
5. If you want to make use of a GPU, you must install the CUDA Toolkit. To install the CUDA Toolkit on your computer refer to the TensorFlow installation guide.
6. If you want to quickly install the r2pa package, run pip install -e . inside the root directory.
7. Now you can start the notebook server by jupyter lab notebooks.

Note: To use the graph plotting methods, you will have to install Graphviz.

IDE

We recommend you use PyCharm Community Edition as your IDE. There is a free version of PyCharm Professional for students.

Jupyter Lab Notebooks

Check the notebooks directory for example Jupyter Lab Notebooks. Make sure to install the 'ipywidgets' extension (https://ipywidgets.readthedocs.io/en/latest/user_install.html) for Jupyter Lab.

References