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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_model_inference.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_plot_model_inference.py:


Model Inference
===============

This example demonstrates how to detect structures with a CNN using ``discopat``.

.. GENERATED FROM PYTHON SOURCE LINES 9-11

Imports
-------

.. GENERATED FROM PYTHON SOURCE LINES 11-18

.. code-block:: Python

    from tqdm import tqdm

    from discopat.core import Movie
    from discopat.display import plot_frame
    from discopat.repositories import repository_factory
    from discopat.nn_models import FasterRCNNModel








.. GENERATED FROM PYTHON SOURCE LINES 19-21

Definitions
-----------

.. GENERATED FROM PYTHON SOURCE LINES 21-29

.. code-block:: Python

    movie_name = "blob_i/density"
    model_name = "faster_rcnn_241113_131447"

    computing_device = "cpu"
    data_source = "osf"
    framework = "torch"









.. GENERATED FROM PYTHON SOURCE LINES 30-32

Load the images
---------------

.. GENERATED FROM PYTHON SOURCE LINES 32-39

.. code-block:: Python

    movie_repository = repository_factory(data_source, "input_movies")
    movie = movie_repository.read(movie_name)

    for frame in movie.frames:
        plot_frame(frame)






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

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    Figure(640x480)
    Figure(640x480)
    Figure(640x480)




.. GENERATED FROM PYTHON SOURCE LINES 40-42

Load the model
--------------

.. GENERATED FROM PYTHON SOURCE LINES 42-48

.. code-block:: Python

    model_repository = repository_factory(data_source, "models")

    raw_model = model_repository.read(model_name)
    model = FasterRCNNModel.from_dict(raw_model)
    model.set_device(computing_device)





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

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    Downloading: "https://download.pytorch.org/models/resnet50-0676ba61.pth" to /home/docs/.cache/torch/hub/checkpoints/resnet50-0676ba61.pth

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.. GENERATED FROM PYTHON SOURCE LINES 49-51

Compute predictions
-------------------

.. GENERATED FROM PYTHON SOURCE LINES 51-54

.. code-block:: Python

    analysed_frames = [model.predict(frame) for frame in tqdm(movie.frames)]
    analysed_movie = Movie(name=movie.name, frames=analysed_frames, tracks=[])





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

 .. code-block:: none


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    Consider using tensor.detach() first. (Triggered internally at /pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:836.)
      self.score = float(score)

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.. GENERATED FROM PYTHON SOURCE LINES 55-57

Display predictions
-------------------

.. GENERATED FROM PYTHON SOURCE LINES 57-59

.. code-block:: Python

    for frame in analysed_movie.frames:
        plot_frame(frame)




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

 .. code-block:: none

    Figure(640x480)
    Figure(640x480)
    Figure(640x480)





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

   **Total running time of the script:** (3 minutes 41.766 seconds)


.. _sphx_glr_download_auto_examples_plot_model_inference.py:

.. only:: html

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-python

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_model_inference.zip <plot_model_inference.zip>`


.. only:: html

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

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