Here we give a very quick rundown of the basic links and information sources for the project.
In the Menpo Team, we strongly advocate the usage of conda for scientific Python, as it makes installation of compiled binaries much more simple. In particular, if you wish to use any of the related Menpo projects such as menpofit, menpo3d or menpodetect, you will not be able to easily do so without using conda. The installation of MenpoFit using conda is as easy as
$ conda install -c menpo menpofit
Conda is able to work out all the requirements/dependencies of MenpoFit. You may for example notice that menpo is one of them. Please see the thorough installation instructions for each platform on the Menpo website.
MenpoFit is extensively documented on a per-method/class level and much of this documentation is reflected in the API Documentation. If any functions or classes are missing, please bring it to the attention of the developers on Github.
For a more thorough set of examples, we provide a set of Jupyter notebooks that demonstrate common use cases of MenpoFit. The notebooks include extensive examples regarding all the state-of-the-art deformable models that we provide. You may need to have a look at the Menpo notebooks in order to get an overview of the basic functionalities required by MenpoFit.
User Group and Issues¶
If you wish to get in contact with the Menpo developers, you can do so via various channels. If you have found a bug, or if any part of MenpoFit behaves in a way you do not expect, please raise an issue on Github.
If you want to ask a theoretical question, or are having problems installing or setting up MenpoFit, please visit the user group.