.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/20_stream/viz_interaction.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_20_stream_viz_interaction.py>`
to download the full example code
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_auto_examples_20_stream_viz_interaction.py:
====================================
Streaming FURY with user interaction
====================================
In this tutorial, we show how to use the FURY Streaming system to
serve an interactive visualization through a web browser.
You can choose between two different encodings: WebRTC or MJPEG.
WebRTC is a more robust option and can be used to perform
a live streaming with a low-latency connection for example using
ngrok. However, to use webRTC you need to install the aiortc library.
.. code-block:: bash
pip install aiortc
Notes
-----
If you don't have ffmpeg installed, you need to install it to use WebRTC
Linux
`apt install libavdevice-dev libavfilter-dev libopus-dev libvpx-dev pkg-config`
OS X
`brew install ffmpeg opus libvpx pkg-config`
.. GENERATED FROM PYTHON SOURCE LINES 33-147
.. image-sg:: /auto_examples/20_stream/images/sphx_glr_viz_interaction_001.png
:alt: viz interaction
:srcset: /auto_examples/20_stream/images/sphx_glr_viz_interaction_001.png
:class: sphx-glr-single-img
.. code-block:: Python
import multiprocessing
import sys
import numpy as np
import fury
# if this example it's not working for you and you're using MacOs
# uncomment the following line
# multiprocessing.set_start_method('spawn')
if __name__ == "__main__":
interactive = False
# `use_raw_array` is a flag to tell the server to use python RawArray
# instead of SharedMemory which is a new feature in python 3.8
# https://docs.python.org/3/library/multiprocessing.html#multiprocessing.Array
# https://docs.python.org/3/library/multiprocessing.html#shared-memory-objects
use_raw_array = sys.version_info < (3, 8)
window_size = (300, 300)
# `max_window_size` are the maximum size of the window that will be
# allowed to be sent to the browser. For example, if you set
# `max_window_size=(800, 800)` then the browser will be limited to
# a window of size (800, 800).
max_window_size = (400, 400)
# 0 ms_stream means that the frame will be sent to the server
# right after the rendering
# `ms_interaction` is the time in milliseconds that the user will have
# to interact with the visualization
ms_interaction = 1
# `ms_stream` is the number of milliseconds that the server will
# wait before sending a new frame to the browser. If `ms_stream=0`
# then the server will send the frame right after the rendering.
ms_stream = 0
# max number of interactions to be stored inside the queue
max_queue_size = 17
######################################################################
centers = np.array([[0, 0, 0], [-1, 0, 0], [1, 0, 0]])
colors = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
actors = fury.actor.sphere(centers, opacity=0.5, radii=0.4, colors=colors)
scene = fury.window.Scene()
scene.add(actors)
showm = fury.window.ShowManager(scene=scene, size=(window_size[0], window_size[1]))
stream = fury.stream.FuryStreamClient(
showm, max_window_size=max_window_size, use_raw_array=use_raw_array
)
stream_interaction = fury.stream.client.FuryStreamInteraction(
showm, max_queue_size=max_queue_size, use_raw_array=use_raw_array
)
if use_raw_array:
p = multiprocessing.Process(
target=fury.stream.server.web_server_raw_array,
args=(
stream.img_manager.image_buffers,
stream.img_manager.info_buffer,
stream_interaction.circular_queue.head_tail_buffer,
stream_interaction.circular_queue.buffer._buffer,
8000,
"localhost",
True,
fury.stream.server.main.WEBRTC_AVAILABLE,
),
)
else:
p = multiprocessing.Process(
target=fury.stream.server.web_server,
args=(
stream.img_manager.image_buffer_names,
stream.img_manager.info_buffer_name,
stream_interaction.circular_queue.head_tail_buffer_name,
stream_interaction.circular_queue.buffer.buffer_name,
8000,
"localhost",
True,
fury.stream.server.main.WEBRTC_AVAILABLE,
),
)
p.start()
stream_interaction.start(ms=ms_interaction)
stream.start(
ms=ms_stream,
)
###########################################################################
# If you have aiortc in your system, you can see your live streaming
# through the following url: htttp://localhost:8000/?encoding=webrtc
# Other wise, you can use the following url:
# http://localhost:8000/?encoding=mjpeg
if interactive:
showm.start()
# We need to close the server after the show is over
p.kill()
###########################################################################
# We release the resources and stop the interactive mode
stream.stop()
stream_interaction.stop()
stream.cleanup()
stream_interaction.cleanup()
fury.window.record(
scene=showm.scene, size=window_size, out_path="viz_interaction.png"
)
.. rst-class:: sphx-glr-timing
**Total running time of the script:** (0 minutes 0.107 seconds)
.. _sphx_glr_download_auto_examples_20_stream_viz_interaction.py:
.. only:: html
.. container:: sphx-glr-footer sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: viz_interaction.ipynb <viz_interaction.ipynb>`
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: viz_interaction.py <viz_interaction.py>`
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_