CoralNet is a website which serves as a repository and resource for benthic image analysis.

Website home: https://coralnet.ucsd.edu

Read more about us: https://coralnet.ucsd.edu/about/

CoralNet's machine-learning processes are powered by PySpacer: https://github.com/beijbom/pyspacer

• Download or git clone this repository's code.
• Install Python and Sphinx. You can do this by either following the installation steps (docs/installation.rst in this repo) until Sphinx is installed, or you can use some other Python environment which already has Sphinx installed.
• Open a terminal/command line, cd to the docs directory, and run make html. (This command is cross platform, since there's a Makefile as well as a make.bat.)
• Open docs/_build/html/index.html in a web browser to start browsing the documentation.
• It's also possible to output in formats other than HTML, if you use make <format> with a different format. See Sphinx's docs.