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.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/segmentation/plot_boundary_merge.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_segmentation_plot_boundary_merge.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_segmentation_plot_boundary_merge.py:


============================================
Hierarchical Merging of Region Boundary RAGs
============================================

This example demonstrates how to perform hierarchical merging on region
boundary Region Adjacency Graphs (RAGs). Region boundary RAGs can be
constructed with the :py:func:`skimage.future.graph.rag_boundary` function.
The regions with the lowest edge weights are successively merged until there
is no edge with weight less than ``thresh``. The hierarchical merging is done
through the :py:func:`skimage.future.graph.merge_hierarchical` function.
For an example of how to construct region boundary based RAGs, see
:any:`plot_rag_boundary`.

.. GENERATED FROM PYTHON SOURCE LINES 16-91



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_001.png
         :alt: Initial RAG
         :srcset: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_002.png
         :alt: RAG after hierarchical merging
         :srcset: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_003.png
         :alt: Final segmentation
         :srcset: /auto_examples/segmentation/images/sphx_glr_plot_boundary_merge_003.png
         :class: sphx-glr-multi-img





.. code-block:: default


    from skimage import data, segmentation, filters, color
    from skimage.future import graph
    from matplotlib import pyplot as plt


    def weight_boundary(graph, src, dst, n):
        """
        Handle merging of nodes of a region boundary region adjacency graph.

        This function computes the `"weight"` and the count `"count"`
        attributes of the edge between `n` and the node formed after
        merging `src` and `dst`.


        Parameters
        ----------
        graph : RAG
            The graph under consideration.
        src, dst : int
            The vertices in `graph` to be merged.
        n : int
            A neighbor of `src` or `dst` or both.

        Returns
        -------
        data : dict
            A dictionary with the "weight" and "count" attributes to be
            assigned for the merged node.

        """
        default = {'weight': 0.0, 'count': 0}

        count_src = graph[src].get(n, default)['count']
        count_dst = graph[dst].get(n, default)['count']

        weight_src = graph[src].get(n, default)['weight']
        weight_dst = graph[dst].get(n, default)['weight']

        count = count_src + count_dst
        return {
            'count': count,
            'weight': (count_src * weight_src + count_dst * weight_dst)/count
        }


    def merge_boundary(graph, src, dst):
        """Call back called before merging 2 nodes.

        In this case we don't need to do any computation here.
        """
        pass

    img = data.coffee()
    edges = filters.sobel(color.rgb2gray(img))
    labels = segmentation.slic(img, compactness=30, n_segments=400, start_label=1)
    g = graph.rag_boundary(labels, edges)

    graph.show_rag(labels, g, img)
    plt.title('Initial RAG')

    labels2 = graph.merge_hierarchical(labels, g, thresh=0.08, rag_copy=False,
                                       in_place_merge=True,
                                       merge_func=merge_boundary,
                                       weight_func=weight_boundary)

    graph.show_rag(labels, g, img)
    plt.title('RAG after hierarchical merging')

    plt.figure()
    out = color.label2rgb(labels2, img, kind='avg', bg_label=0)
    plt.imshow(out)
    plt.title('Final segmentation')

    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.857 seconds)


.. _sphx_glr_download_auto_examples_segmentation_plot_boundary_merge.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_boundary_merge.py <plot_boundary_merge.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_boundary_merge.ipynb <plot_boundary_merge.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_
