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

    Click :ref:`here <sphx_glr_download_auto_examples_transform_plot_seam_carving.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_transform_plot_seam_carving.py:


============
Seam Carving
============

This example demonstrates how images can be resized using seam carving [1]_.
Resizing to a new aspect ratio distorts image contents. Seam carving attempts
to resize *without* distortion, by removing regions of an image which are less
important. In this example we are using the Sobel filter to signify the
importance of each pixel.

.. [1] Shai Avidan and Ariel Shamir
       "Seam Carving for Content-Aware Image Resizing"
       http://www.cs.jhu.edu/~misha/ReadingSeminar/Papers/Avidan07.pdf




.. code-block:: python

    from skimage import data, draw
    from skimage import transform, util
    import numpy as np
    from skimage import filters, color
    from matplotlib import pyplot as plt


    hl_color = np.array([0, 1, 0])

    img = data.rocket()
    img = util.img_as_float(img)
    eimg = filters.sobel(color.rgb2gray(img))

    plt.title('Original Image')
    plt.imshow(img)




.. image:: /auto_examples/transform/images/sphx_glr_plot_seam_carving_001.png
    :class: sphx-glr-single-img





.. code-block:: python


    resized = transform.resize(img, (img.shape[0], img.shape[1] - 200),
                               mode='reflect')
    plt.figure()
    plt.title('Resized Image')
    plt.imshow(resized)




.. image:: /auto_examples/transform/images/sphx_glr_plot_seam_carving_002.png
    :class: sphx-glr-single-img





.. code-block:: python


    out = transform.seam_carve(img, eimg, 'vertical', 200)
    plt.figure()
    plt.title('Resized using Seam Carving')
    plt.imshow(out)




.. image:: /auto_examples/transform/images/sphx_glr_plot_seam_carving_003.png
    :class: sphx-glr-single-img




Resizing distorts the rocket and surrounding objects, whereas seam carving
removes empty spaces and preserves object proportions.

Object Removal
--------------

Seam carving can also be used to remove artifacts from images. This
requires weighting the artifact with low values. Recall lower weights are
preferentially removed in seam carving. The following code masks the
rocket's region with low weights, indicating it should be removed.



.. code-block:: python


    masked_img = img.copy()

    poly = [(404, 281), (404, 360), (359, 364), (338, 337), (145, 337), (120, 322),
            (145, 304), (340, 306), (362, 284)]
    pr = np.array([p[0] for p in poly])
    pc = np.array([p[1] for p in poly])
    rr, cc = draw.polygon(pr, pc)

    masked_img[rr, cc, :] = masked_img[rr, cc, :]*0.5 + hl_color*.5
    plt.figure()
    plt.title('Object Marked')

    plt.imshow(masked_img)




.. image:: /auto_examples/transform/images/sphx_glr_plot_seam_carving_004.png
    :class: sphx-glr-single-img





.. code-block:: python


    eimg[rr, cc] -= 1000

    plt.figure()
    plt.title('Object Removed')
    out = transform.seam_carve(img, eimg, 'vertical', 90)
    resized = transform.resize(img, out.shape, mode='reflect')
    plt.imshow(out)
    plt.show()




.. image:: /auto_examples/transform/images/sphx_glr_plot_seam_carving_005.png
    :class: sphx-glr-single-img




**Total running time of the script:** ( 0 minutes  3.098 seconds)


.. _sphx_glr_download_auto_examples_transform_plot_seam_carving.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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