.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/segmentation/plot_ncut.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_segmentation_plot_ncut.py: ============== Normalized Cut ============== This example constructs a Region Adjacency Graph (RAG) and recursively performs a Normalized Cut on it [1]_. References ---------- .. [1] Shi, J.; Malik, J., "Normalized cuts and image segmentation", Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 22, no. 8, pp. 888-905, August 2000. .. GENERATED FROM PYTHON SOURCE LINES 15-40 .. image-sg:: /auto_examples/segmentation/images/sphx_glr_plot_ncut_001.png :alt: plot ncut :srcset: /auto_examples/segmentation/images/sphx_glr_plot_ncut_001.png :class: sphx-glr-single-img .. code-block:: default from skimage import data, segmentation, color from skimage import graph from matplotlib import pyplot as plt img = data.coffee() labels1 = segmentation.slic(img, compactness=30, n_segments=400, start_label=1) out1 = color.label2rgb(labels1, img, kind='avg', bg_label=0) g = graph.rag_mean_color(img, labels1, mode='similarity') labels2 = graph.cut_normalized(labels1, g) out2 = color.label2rgb(labels2, img, kind='avg', bg_label=0) fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True, figsize=(6, 8)) ax[0].imshow(out1) ax[1].imshow(out2) for a in ax: a.axis('off') plt.tight_layout() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 2.970 seconds) .. _sphx_glr_download_auto_examples_segmentation_plot_ncut.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/scikit-image/scikit-image/v0.22.x?filepath=notebooks/auto_examples/segmentation/plot_ncut.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_ncut.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_ncut.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_