.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorials/2d_tv_segmentation.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_tutorials_2d_tv_segmentation.py>`
        to download the full example code

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

.. _sphx_glr_tutorials_2d_tv_segmentation.py:


07. Segmentation
================
This example shows the interface usage for class-based segmentation
of a 2D image. First, depending on the size of the weighting lambda,
a piecewise constant image is generated before the assignment to certain classes is done.

.. GENERATED FROM PYTHON SOURCE LINES 10-12

TV based segmentation


.. GENERATED FROM PYTHON SOURCE LINES 12-45

.. code-block:: default


    import skimage.data as skd
    import numpy as np
    import matplotlib.pyplot as plt

    from recon.interfaces import Segmentation


    def rgb2gray(rgb):
        r, g, b = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
        gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
        return gray


    gt = rgb2gray(skd.coffee())[:, 80:481]
    gt = gt/np.max(gt)
    gt = gt/np.max(gt)

    classes = [0, 50/255, 120/255, 190/255, 220/255]

    segmentation = Segmentation(gt.shape, classes=classes, lam=5, tau='calc')
    result, _ = segmentation.solve(gt, max_iter=4000)

    f = plt.figure(figsize=(8, 4))
    f.add_subplot(1, 2, 1)
    plt.axis('off')
    plt.imshow(gt)
    plt.title("GT")
    f.add_subplot(1, 2, 2)
    plt.imshow(result)
    plt.title("TV-based segmentation")
    plt.axis('off')
    plt.show(block=False)



.. image:: /tutorials/images/sphx_glr_2d_tv_segmentation_001.png
    :alt: GT, TV-based segmentation
    :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

     Early stopping.





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

   **Total running time of the script:** ( 0 minutes  40.695 seconds)


.. _sphx_glr_download_tutorials_2d_tv_segmentation.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: 2d_tv_segmentation.py <2d_tv_segmentation.py>`



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

     :download:`Download Jupyter notebook: 2d_tv_segmentation.ipynb <2d_tv_segmentation.ipynb>`


.. only:: html

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

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