Gallery of examples

The examples below shows functionalities of scikit-shapes.

Data

The data classes are designed to store geometric data and associated features for shape analysis.

PolyData conversion from and to PyVista or Vedo

PolyData conversion from and to PyVista or Vedo

The PolyData class: point cloud, wireframe and triangle meshes

The PolyData class: point cloud, wireframe and triangle meshes

Multiscaling

Representing data at various scale is a core feature of scikit-shapes: in addition to data compression, we provide tools for preserving features across scales.

Multiscaling (triangle mesh)

Multiscaling (triangle mesh)

Multiscaling and landmarks

Multiscaling and landmarks

Multiscaling and signal propagation

Multiscaling and signal propagation

Registration

The registration class allows to express various registration algorithm within the same framework.

Intrinsic vs Extrinsic deformation

Intrinsic vs Extrinsic deformation

Rigid alignment in 2D

Rigid alignment in 2D

Rigid alignment in 3D with landmarks

Rigid alignment in 3D with landmarks

Registration with LDDMM

Registration with LDDMM

LDDMM with normalized kernel

LDDMM with normalized kernel

Elastic metric and multiscale strategy

Elastic metric and multiscale strategy

Applications

The application module contains small applications, written with Vedo that can be helpful for geometric data processing.

Browse a sequence of shapes

Browse a sequence of shapes

Set landmarks

Set landmarks

Custom model or loss function

In addition to the built-in models and loss functions, you can write custom ones.

Write a custom deformation model for PolyData.

Write a custom deformation model for PolyData.