mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-02 09:21:20 +08:00
Vighnesh Birodkar
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
import networkx as nx
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import numpy as np
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def threshold_cut(label, rag, thresh):
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"""Combines regions seperated by weight less than threshold.
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Given an image's labels and its RAG, outputs new labels by
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combining regions whose nodes are seperated by a weight less
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than the given threshold.
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Parameters
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----------
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label : (width, height) or (width, height, 3) ndarray
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The array of labels.
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rag : RAG
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The region adjacency graph.
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thresh : float
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The threshold, regions with edge weights less than this
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are combined.
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Returns
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-------
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out : (width, height, 3) or (width, height, depth, 3) ndarray
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The new labelled array.
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Examples
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--------
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>>> from skimage import data,graph,segmentation
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>>> img = data.lena()
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>>> labels = segmentation.slic(img)
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>>> rag = graph.rag_meancolor(img, labels)
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>>> new_labels = graph.threshold_cut(labels, rag, 10)
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"""
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to_remove = [(x, y) for x, y, d in rag.edges_iter(data=True)
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if d['weight'] >= thresh]
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rag.remove_edges_from(to_remove)
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comps = nx.connected_components(rag)
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out = np.copy(label)
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for i, nodes in enumerate(comps):
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for node in nodes:
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for l in rag.node[node]['labels']:
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out[label == l] = i
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return out
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