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Reading/Writing images and videos
=================================
.. currentmodule:: torchvision.io
The :mod:`torchvision.io` package provides functions for performing IO
operations. They are currently specific to reading and writing video and
images.
Video
-----
.. autosummary::
:toctree: generated/
:template: function.rst
read_video
read_video_timestamps
write_video
Fine-grained video API
----------------------
In addition to the :mod:`read_video` function, we provide a high-performance
lower-level API for more fine-grained control compared to the :mod:`read_video` function.
It does all this whilst fully supporting torchscript.
.. betastatus:: fine-grained video API
.. autosummary::
:toctree: generated/
:template: class.rst
VideoReader
Example of inspecting a video:
.. code:: python
import torchvision
video_path = "path to a test video"
# Constructor allocates memory and a threaded decoder
# instance per video. At the moment it takes two arguments:
# path to the video file, and a wanted stream.
reader = torchvision.io.VideoReader(video_path, "video")
# The information about the video can be retrieved using the
# `get_metadata()` method. It returns a dictionary for every stream, with
# duration and other relevant metadata (often frame rate)
reader_md = reader.get_metadata()
# metadata is structured as a dict of dicts with following structure
# {"stream_type": {"attribute": [attribute per stream]}}
#
# following would print out the list of frame rates for every present video stream
print(reader_md["video"]["fps"])
# we explicitly select the stream we would like to operate on. In
# the constructor we select a default video stream, but
# in practice, we can set whichever stream we would like
video.set_current_stream("video:0")
Image
-----
.. autosummary::
:toctree: generated/
:template: class.rst
ImageReadMode
.. autosummary::
:toctree: generated/
:template: function.rst
read_image
decode_image
encode_jpeg
decode_jpeg
write_jpeg
encode_png
decode_png
write_png
read_file
write_file
|
