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

    Click :ref:`here <sphx_glr_download_auto_examples_plot_2_frame_selection.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_2_frame_selection.py:


Frame selection, resizing, and grayscale conversion
===================================================

* We want to resize each frame to be 720 pixels in width and 480 pixels
  in height.

  * Set ``target_size`` to (720, 480)

* All the frames are not required. Let’s just capture exactly 12  random
  frames from the video.

  * Set ``mode`` to ``"random"``

* And finally, visualize the captured frames using :func:`mydia.make_grid`



.. code-block:: python


    # Imports
    import matplotlib.pyplot as plt
    from mydia import Videos, make_grid

    # Initialize video path
    video_path = r"./sample_video/bigbuckbunny.mp4"

    # Configuring the parameters
    # For other paramaters available, view the code documentation.
    reader = Videos(target_size=(720, 480), num_frames=12, mode="random")

    # Call the 'read()' function to get the required video tensor
    # which will be of shape (1, 12, 480, 720, 3)
    video = reader.read(video_path)
    print("The shape of the tensor:", video.shape)

    # Plot the video frames in a grid
    grid = make_grid(video[0])
    plt.imshow(grid)




.. image:: /auto_examples/images/sphx_glr_plot_2_frame_selection_001.png
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    The shape of the tensor: (1, 12, 480, 720, 3)


.. note:: The number of channels for a RGB video is 3
 (indicated by the last value in the tuple).


* Now let's read the video with the same configuration, but in
  **grayscale**

  * For this, set ``to_gray`` to `True`

* Also, the function `make_grid()` takes certain arguments to construct
  the grid of frames of the video.
  For more info, view :func:`mydia.make_grid`.



.. code-block:: python


    # Imports
    import matplotlib.pyplot as plt
    from mydia import Videos, make_grid

    # Initialize video path
    video_path = r"./sample_video/bigbuckbunny.mp4"

    # Configuring the parameters
    reader = Videos(target_size=(720, 480), to_gray=True, num_frames=12, mode="random")

    # Call the 'read()' function to get the required video tensor
    # which will be of shape (1, 12, 480, 720, 1)
    video = reader.read(video_path)
    print("The shape of the tensor:", video.shape)

    # Plot the video frames in a grid
    grid = make_grid(video[0], num_col=2)
    plt.imshow(grid, cmap="gray")




.. image:: /auto_examples/images/sphx_glr_plot_2_frame_selection_002.png
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    The shape of the tensor: (1, 12, 480, 720, 1)


.. note:: The number of channels for a video in gray scale is 1
 (indicated by the last value in the tuple).


**Total running time of the script:** ( 0 minutes  1.137 seconds)


.. _sphx_glr_download_auto_examples_plot_2_frame_selection.py:


.. only :: html

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



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_2_frame_selection.py <plot_2_frame_selection.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_2_frame_selection.ipynb <plot_2_frame_selection.ipynb>`


.. only:: html

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

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