centaur-recipes: Centaur's public repository for data pre-processing code recipes

Summary

This repository contains code snippets you may integrate with your scripts to process your data before sending it to Centaur Labs. Some recipes might need to be used sequentially.

The code recipes currently available are:

• abs_to_wkt
• add_tracking_line_to_plot
• audio_to_mel_spectrogram
• audio_to_video
• cocojson_to_csv
• coordinate_converter
• dicom_to_image
• entity_highlights
• mask_to_wkt
• multi_paragraph_text
• video_to_image
• wkt_to_mask

Installation

The recipes in this repository require Python 3.9+ to run. You may install python from: https://www.python.org/downloads/. Generally, each recipe folder will contain specific instructions on how to install and use the recipe. Below you can find instructions on how to set up a virtual environment as well as how to use one with a Jupyter notebook.

Virtual environment

After you've downloaded a recipe and any associated files, it is highly recommended creating a new virtual environment for the script you will write.

To create a virtual environment using the default python virtual environment manger:

1. Open up a terminal or command prompt and navigate to the directory containing the notebook.
2. Then create a virtual environment using python -m venv env_name where env_name can be changed as desired.
3. Activate the virtual environment by using one of the following commands depending on your operating system:
   • Unix/macOS: source env_name/bin/activate
   • Windows: .\env_name\Scripts\activate
4. To deactivate the virtual environment you can type deactivate in the terminal or command prompt

Installing Requirements and Running a Notebook

For recipes that are Jupyter notebooks, or if you are just working in one perform these additional steps to ensure the notebook is using the correct virtual environment and installed packages. Some IDEs may handle selecting the correct virtual environment for you, in which case you only need to do step 1.

1. With the environment activated, run pip install -r requirements.txt from the terminal or command prompt. This should install jupyter as well as the other required packages.
2. Run python -m ipykernel install --user --name env_name where env_name is the name of the currently activated virtual environment.
3. Now start the Jupyter notebook with jupyter notebook path/to/notebook.ipynb The notebook should open in your default browser.
4. In the top toolbar click on Kernel and then select Change kernel.
5. Select the kernel that has the same name as your virtual environment.
6. Now you may follow any remaining instructions in the notebook.