This is the documentation repository for leafmachine2, a suite of computer vision and machine learning algorithms that enables efficient identification, location, and measurement of vegetative, reproductive, and archival components from digital plant datasets.
This documentation uses the pydata sphinx theme. To download the repository and run locally, follow the instructions below.
git clone "https://github.com/Gene-Weaver/docs-LM2"
cd docs-LM2To avoid duplication and to ensure that the installation details are accurate, please refer to the sphinx documentation for installing sphinx. There is a comprehensive list of operating systems and package managers supported.
The documentation is written according to the reStructured text format. These files are contained within /source. The directories are the top level categories to which the individual documents belong, enabling easier navigation of the site.
If you make a change to one of the source files and would like to see what it will look like, run the following from the root of the docs-LM2 respository
sphinx-build -M html .\source\ .\build -aThis will create a directory called build which will contain html files that can be served through the web browser. Navigate to this folder (either through the command line or through your file explorer) and open index.html. You should now be able to navigate a copy of the documentation site in your browser. This build directory is ignored by git.
Coming soon!