skimage2.graph.show_rag#

skimage2.graph.show_rag(labels, rag, image, border_color='black', edge_width=1.5, edge_cmap='magma', img_cmap='bone', in_place=True, ax=None)[source]#

Show a Region Adjacency Graph on an image.

Given a labelled image and its corresponding RAG, show the nodes and edges of the RAG on the image with the specified colors. Edges are displayed between the centroid of the 2 adjacent regions in the image.

Parameters:

labelsndarray, shape (M, N): The labelled image.
ragRAG: The Region Adjacency Graph.
imagendarray, shape (M, N[, 3]): Input image. If colormap is None, the image should be in RGB format.
border_colorcolor spec, optional: Color with which the borders between regions are drawn.
edge_widthfloat, optional: The thickness with which the RAG edges are drawn.
edge_cmapmatplotlib.colors.Colormap, optional: Any matplotlib colormap with which the edges are drawn.
img_cmapmatplotlib.colors.Colormap, optional: Any matplotlib colormap with which the image is draw. If set to None the image is drawn as it is.
in_placebool, optional: If set, the RAG is modified in place. For each node n the function will set a new attribute rag.nodes[n]['centroid'].
axmatplotlib.axes.Axes, optional: The axes to draw on. If not specified, new axes are created and drawn on.

Returns:

lcmatplotlib.collections.LineCollection: A collection of lines that represent the edges of the graph. It can be passed to the matplotlib.figure.Figure.colorbar() function.

Examples

>>> from _skimage2 import data, segmentation, graph
>>> import matplotlib.pyplot as plt
>>>
>>> img = data.coffee()
>>> labels = segmentation.slic(img)
>>> g =  graph.rag_mean_color(img, labels)
>>> lc = graph.show_rag(labels, g, img)
>>> cbar = plt.colorbar(lc)