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 |
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Filtering with non-increasing criterion - The shaping framework |
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Pattern spectra - granulometry based on connected filters |
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Hierarchical segmentation¶
These examples deal with images, weights are on edges of the associated graph.
Visualizing hierarchical image segmentation |
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Watershed hierarchies |
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Hierarchy filtering |
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Computing a saliency map with the shaping framework |
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Multiscale Hierarchy Alignment and Combination |
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Triangular meshes¶
We provide two examples.
The first one uses trimesh, a simple, pure-python. It can be slow, and not-memory efficient.
The second one uses igl, an efficient C++ geometry processing library, with python bindings.
Hierarchical mesh segmentation – trimesh |
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Hierarchical mesh segmentation – igl |
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Useful tools¶
Region Adjacency Graph |
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Interactive object segmentation |
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Contour Simplification |
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Illustrative applications from scientific papers¶
Points and Images - Illustrations of SoftwareX 2019 article |
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Non-relevant node removal, on both point and images. PRL 2019 |
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Fuzzy-marker-based interactive object segmentation - DGMM 2021 |
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Astronomical object detection with the Max-Tree - MMTA 2016 |
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