notebooks.rst

Python notebooks

The following python notebooks contain examples demonstrating Higra usage. Data can be points, images, or meshes, or anything that can be transformed into a graph.

Component trees

These examples deal with upper and lower treshold set of vertex-weighted graphs.

Connected image filtering with component trees	👁_	💾_	_
Filtering with non-increasing criterion - The shaping framework	👁_	💾_	_
Pattern spectra - granulometry based on connected filters	👁_	💾_	_

Hierarchical segmentation

These examples deal with images, weights are on edges of the associated graph.

Visualizing hierarchical image segmentation	👁_	💾_	_
Watershed hierarchies	👁_	💾_	_
Hierarchy filtering	👁_	💾_	_
Computing a saliency map with the shaping framework	👁_	💾_	_
Multiscale Hierarchy Alignment and Combination	👁_	💾_	_

Triangular meshes

We provide two examples.

1. The first one uses trimesh, a simple, pure-python. It can be slow, and not-memory efficient.
2. The second one uses igl, an efficient C++ geometry processing library, with python bindings.

Hierarchical mesh segmentation -- trimesh	👁_	💾_	_
Hierarchical mesh segmentation -- igl	👁_	💾_	_

Useful tools

Region Adjacency Graph	👁_	💾_	_
Interactive object segmentation	👁_	💾_	_
Contour Simplification	👁_	💾_	_

Illustrative applications from scientific papers

Points and Images - Illustrations of SoftwareX 2019 article	👁_	💾_	_
Non-relevant node removal, on both point and images. PRL 2019	👁_	💾_	_
Fuzzy-marker-based interactive object segmentation - DGMM 2021	👁_	💾_	_
Astronomical object detection with the Max-Tree - MMTA 2016	👁_	💾_	_