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Image, Shape and User Guide Docs
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jabooth committed Feb 5, 2015
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4 changes: 2 additions & 2 deletions docs/source/_static/rtd_hack.css
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5 changes: 5 additions & 0 deletions docs/source/api/index.rst
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The Menpo API
#############
This section attempts to provide a simple browsing experience for the Menpo
documentation. In Menpo, we use legible docstrings, and therefore, all
documentation should be easily accessible in any sensible IDE (or IPython)
via tab completion. However, this section should make most of the core
classes available for viewing online.

.. toctree::
:maxdepth: 1
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:members:
:inherited-members:
:show-inheritance:

.. automethod:: _view_2d
.. automethod:: _view_landmarks_2d
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.. _menpo-shape-Shape:

.. currentmodule:: menpo.shape.base

Shape
=====
.. autoclass:: Shape
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:mod:`menpo.shape`
==================


Base Classes
------------

.. toctree::
:maxdepth: 1

Shape


PointCloud
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Welcome
=======
**Welcome to the Menpo documentation!**

Welcome to Menpo's documentation.
Menpo is a Python package designed to make manipulating annotated data more
simple. In particular, sparse locations on either images or meshes, referred
to as **landmarks** within Menpo, are tightly coupled with their reference
objects. For areas such as Computer Vision that involve learning models
based on prior knowledge of object location (such as object detection
and landmark localisation), Menpo is a very powerful toolkit.

If you are new to Menpo, we strongly recommend you check out the
:ref:`User Guide <ug-introduction>`, which provides a broad overview of the project. After
that you may wish to explore the
`Menpo Notebooks <http://www.menpo.io/notebooks.html>`_, which give detailed
examples for all aspects of Menpo that you can execute for yourself.
A short example is often more illustrative than a verbose explanation. Let's
assume that you want to load a set of images that have been annotated with
bounding boxes, and that these bounding box locations live in text files
next to the images. Here's how we would load the images and extract the
areas within the bounding boxes using Menpo:

Finally, Menpo's source is extensively documented. If you have a question about
the behaviour of a particular class or function you should head to the the
:ref:`api-index`.
.. code-block:: python
Contents
========
import menpo.io as mio
images = []
for image in mio.import_images('./images_folder'):
image.crop_to_landmarks_inplace()
images.append(image)
Where :map:`import_images` yields a generator to keep memory usage low.

Although the above is a very simple example, we believe that being able
to easily manipulate and couple landmarks with images *and* meshes, is an
important problem for building powerful models in areas such as facial
point localisation.

To get started, check out the User Guide for instructions on installation
and some of the core concepts within Menpo.

.. toctree::
:maxdepth: 1
:maxdepth: 2
:hidden:

userguide/index
api/index

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