A library inside the Menpo Project that makes manipulating 3D mesh data a simple task. In particular, this project provides the ability to import, visualize and rasterize 3D meshes. Although 3D meshes can be created within the main Menpo project, this package adds the real functionality for working with 3D data.
Here in the Menpo team, we are firm believers in making installation as simple as possible. Unfortunately, we are a complex project that relies on satisfying a number of complex 3rd party library dependencies. The default Python packing environment does not make this an easy task. Therefore, we evangelise the use of the conda ecosystem, provided by Anaconda. In order to make things as simple as possible, we suggest that you use conda too! To try and persuade you, go to the Menpo website to find installation instructions for all major platforms.
menpo3d adds support for viewing 3D objects through
Mayavi, which is based on VTK.
One of the main reasons menpo3d is a seperate project to the menpo core
library is to isolate the more complex dependencies that this brings to the
project. 3D visualization is not yet supported in the browser, so we rely on
platform-specific viewing mechanisms like QT or WX. In addition, menpo3d
supports 3D visualization in the browser using K3D Jupyter library which is a
Jupyter notebook extension for 3D visualization.
In order to view 3D items through mayavi you will need to first use the %matplotlib qt
IPython magic command to set up QT for rendering (you do this instead of
%matplotlib inline
which is what is needed for rendering directly
in Jupyter/Ipython notebooks). As a complete example, to view a
mesh in IPython you would run something like:
import menpo3d
mesh = menpo3d.io.import_builtin_asset('james.obj')
%matplotlib qt
mesh.view()
In the case of K3D Jupyter visualization to view a mesh in Jupyter cell you would run something like:
import menpo3d
mesh = menpo3d.io.import_builtin_asset('james.obj')
mesh.view(inline=True)