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

.. only:: html

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

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

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

.. _sphx_glr_build_examples_segmentation_demo_icnet.py:

7. Test with ICNet Pre-trained Models for Multi-Human Parsing
======================================

This is a quick demo of using GluonCV ICNet model for multi-human parsing on real-world images.
Please follow the `installation guide <../../index.html#installation>`__
to install MXNet and GluonCV if not yet.

.. GENERATED FROM PYTHON SOURCE LINES 8-16

.. code-block:: default

    import mxnet as mx
    from mxnet import image
    from mxnet.gluon.data.vision import transforms
    import gluoncv
    # using cpu
    ctx = mx.cpu(0)









.. GENERATED FROM PYTHON SOURCE LINES 17-21

Prepare the image
-----------------

Let's first download the example image,

.. GENERATED FROM PYTHON SOURCE LINES 21-27

.. code-block:: default


    url = 'https://raw.githubusercontent.com/dmlc/web-data/master/gluoncv/segmentation/mhpv1_examples/1.jpg'
    filename = 'mhp_v1_example.jpg'
    gluoncv.utils.download(url, filename, True)






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

 Out:

 .. code-block:: none

    Downloading mhp_v1_example.jpg from https://raw.githubusercontent.com/dmlc/web-data/master/gluoncv/segmentation/mhpv1_examples/1.jpg...

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Then we load the image and visualize it,

.. GENERATED FROM PYTHON SOURCE LINES 29-36

.. code-block:: default


    img = image.imread(filename)

    from matplotlib import pyplot as plt
    plt.imshow(img.asnumpy())
    plt.show()




.. image-sg:: /build/examples_segmentation/images/sphx_glr_demo_icnet_001.png
   :alt: demo icnet
   :srcset: /build/examples_segmentation/images/sphx_glr_demo_icnet_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 37-38

We normalize the image using dataset mean and standard deviation,

.. GENERATED FROM PYTHON SOURCE LINES 38-42

.. code-block:: default


    from gluoncv.data.transforms.presets.segmentation import test_transform
    img = test_transform(img, ctx)








.. GENERATED FROM PYTHON SOURCE LINES 43-47

Load the pre-trained model and make prediction
----------------------------------------------

Next, we get a pre-trained model from our model zoo,

.. GENERATED FROM PYTHON SOURCE LINES 47-50

.. code-block:: default


    model = gluoncv.model_zoo.get_model('icnet_resnet50_mhpv1', pretrained=True)





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

 Out:

 .. code-block:: none

    Downloading /root/.mxnet/models/icnet_resnet50_mhpv1-873d381a.zip from https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/models/icnet_resnet50_mhpv1-873d381a.zip...

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.. GENERATED FROM PYTHON SOURCE LINES 51-52

We directly make semantic predictions on the image,

.. GENERATED FROM PYTHON SOURCE LINES 52-56

.. code-block:: default


    output = model.predict(img)
    predict = mx.nd.squeeze(mx.nd.argmax(output, 1)).asnumpy()








.. GENERATED FROM PYTHON SOURCE LINES 57-58

In the end, we add color pallete for visualizing the predicted mask,

.. GENERATED FROM PYTHON SOURCE LINES 58-66

.. code-block:: default


    from gluoncv.utils.viz import get_color_pallete
    import matplotlib.image as mpimg
    mask = get_color_pallete(predict, 'mhpv1')
    mask.save('output.png')
    mmask = mpimg.imread('output.png')
    plt.imshow(mmask)
    plt.show()



.. image-sg:: /build/examples_segmentation/images/sphx_glr_demo_icnet_002.png
   :alt: demo icnet
   :srcset: /build/examples_segmentation/images/sphx_glr_demo_icnet_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  6.650 seconds)


.. _sphx_glr_download_build_examples_segmentation_demo_icnet.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: demo_icnet.py <demo_icnet.py>`



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

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


.. only:: html

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

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