mirror of
https://github.com/wassname/scikit-image.git
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Vighnesh Birodkar
105 lines
3.2 KiB
Python
105 lines
3.2 KiB
Python
"""
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===========
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RAG Merging
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===========
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This example constructs a Region Adjacency Graph (RAG) and progressively merges
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regions that are similar in color. Merging two adjacent regions produces
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a new region with all the pixels from the merged regions. Regions are merged
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until no highly similar region pairs remain.
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"""
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from skimage import graph, data, io, segmentation, color
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import numpy as np
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def _weight_mean_color(graph, src, dst, n):
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"""Callback to handle merging nodes by recomputing mean color.
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The method expects that the mean color of `dst` is already computed.
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Parameters
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----------
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graph : RAG
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The graph under consideration.
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src, dst : int
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The vertices in `graph` to be merged.
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n : int
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A neighbor of `src` or `dst` or both.
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Returns
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-------
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weight : float
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The absolute difference of the mean color between node `dst` and `n`.
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"""
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#print 'merging
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diff = graph.node[dst]['mean color'] - graph.node[n]['mean color']
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diff = np.linalg.norm(diff)
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return diff
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def _pre_merge_mean_color(graph, src, dst):
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"""Callback called before merging two nodes of a mean color distance graph.
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This method computes the mean color of `dst`.
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Parameters
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----------
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graph : RAG
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The graph under consideration.
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src, dst : int
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The vertices in `graph` to be merged.
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"""
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graph.node[dst]['total color'] += graph.node[src]['total color']
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graph.node[dst]['pixel count'] += graph.node[src]['pixel count']
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graph.node[dst]['mean color'] = (graph.node[dst]['total color'] /
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graph.node[dst]['pixel count'])
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def merge_hierarchical_mean_color(labels, rag, thresh, rag_copy=True,
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in_place_merge=False):
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"""Perform hierarchical merging of a color distance RAG.
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Greedily merges the most similar pair of nodes until no edges lower than
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`thresh` remain.
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Parameters
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----------
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labels : 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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Regions connected by an edge with weight smaller than `thresh` are
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merged.
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rag_copy : bool, optional
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If set, the RAG copied before modifying.
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in_place_merge : bool, optional
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If set, the nodes are merged in place. Otherwise, a new node is
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created for each merge.
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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.coffee()
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>>> labels = segmentation.slic(img)
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>>> rag = graph.rag_mean_color(img, labels)
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>>> new_labels = graph.merge_hierarchical_mean_color(labels, rag, 40)
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"""
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return graph.merge_hierarchical(labels, rag, thresh, rag_copy,
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in_place_merge, _pre_merge_mean_color,
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_weight_mean_color)
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img = data.coffee()
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labels = segmentation.slic(img, compactness=30, n_segments=400)
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g = graph.rag_mean_color(img, labels)
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labels2 = merge_hierarchical_mean_color(labels, g, 40)
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g2 = graph.rag_mean_color(img, labels2)
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out = color.label2rgb(labels2, img, kind='avg')
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out = segmentation.mark_boundaries(out, labels2, (0, 0, 0))
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io.imshow(out)
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io.show()
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