.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "build/examples_datasets/ade20k.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_build_examples_datasets_ade20k.py>`
        to download the full example code

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

.. _sphx_glr_build_examples_datasets_ade20k.py:

Prepare ADE20K dataset.
========================

`ADE20K <http://sceneparsing.csail.mit.edu/>`_ is a scene-centric containing
20 thousands images annotated with 150 object categories.
This tutorial help you to download ADE20K and set it up for later experiments.

.. image:: http://groups.csail.mit.edu/vision/datasets/ADE20K/assets/images/examples.png
   :width: 600 px

.. hint::

   You need 2.3 GB free disk space to download and extract this dataset.
   SSD harddrives are recommended for faster speed.
   The time it takes to prepare the dataset depends on your Internet connection
   and disk speed. For example, it takes around 25 mins on an AWS EC2 instance
   with EBS.

Prepare the dataset
-------------------

We will download and unzip the following files:

+-------------------------------------------------------------------------------------------------------+--------+
| File name                                                                                             | Size   |
+=======================================================================================================+========+
| `ADEChallengeData2016.zip <http://data.csail.mit.edu/places/ADEchallenge/ADEChallengeData2016.zip>`_  | 923 MB |
+-------------------------------------------------------------------------------------------------------+--------+
| `release_test.zip <http://data.csail.mit.edu/places/ADEchallenge/release_test.zip>`_                  | 202 MB |
+-------------------------------------------------------------------------------------------------------+--------+

The easiest way is to run this script:

 :download:`Download script: ade20k.py<../../../scripts/datasets/ade20k.py>`

.. code-block:: bash

   python ade20k.py

If you have already downloaded the above files and unzipped them,
you can set the folder name through ``--download-dir`` to avoid
downloading them again. For example

.. code-block:: python

   python ade20k.py --download-dir ~/ade_downloads


.. GENERATED FROM PYTHON SOURCE LINES 51-56

How to load the dataset
-----------------------

Loading images and labels from ADE20K is straight-forward
with GluonCV's dataset utility:

.. GENERATED FROM PYTHON SOURCE LINES 56-64

.. code-block:: default


    from gluoncv.data import ADE20KSegmentation
    train_dataset = ADE20KSegmentation(split='train')
    val_dataset = ADE20KSegmentation(split='val')
    print('Training images:', len(train_dataset))
    print('Validation images:', len(val_dataset))






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

 Out:

 .. code-block:: none

    Training images: 20210
    Validation images: 2000




.. GENERATED FROM PYTHON SOURCE LINES 65-68

Get the first sample
--------------------


.. GENERATED FROM PYTHON SOURCE LINES 68-76

.. code-block:: default

    import numpy as np
    img, mask = val_dataset[0]
    # get pallete for the mask
    from gluoncv.utils.viz import get_color_pallete
    mask = get_color_pallete(mask.asnumpy(), dataset='ade20k')
    mask.save('mask.png')









.. GENERATED FROM PYTHON SOURCE LINES 77-80

Visualize data and label
------------------------


.. GENERATED FROM PYTHON SOURCE LINES 80-92

.. code-block:: default

    from matplotlib import pyplot as plt
    import matplotlib.image as mpimg
    # subplot 1 for img
    fig = plt.figure()
    fig.add_subplot(1,2,1)
    plt.imshow(img.asnumpy().astype('uint8'))
    # subplot 2 for the mask
    mmask = mpimg.imread('mask.png')
    fig.add_subplot(1,2,2)
    plt.imshow(mmask)
    # display
    plt.show()



.. image-sg:: /build/examples_datasets/images/sphx_glr_ade20k_001.png
   :alt: ade20k
   :srcset: /build/examples_datasets/images/sphx_glr_ade20k_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  43.456 seconds)


.. _sphx_glr_download_build_examples_datasets_ade20k.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: ade20k.py <ade20k.py>`



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

     :download:`Download Jupyter notebook: ade20k.ipynb <ade20k.ipynb>`


.. only:: html

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

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