.. 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.
.. autofunction:: read_video
.. autofunction:: read_video_timestamps
.. autofunction:: write_video
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.
.. autoclass:: VideoReader
:members: __next__, get_metadata, set_current_stream, seek
Example of inspecting a video:
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").. autoclass:: ImageReadMode
.. autofunction:: read_image
.. autofunction:: decode_image
.. autofunction:: encode_jpeg
.. autofunction:: decode_jpeg
.. autofunction:: write_jpeg
.. autofunction:: encode_png
.. autofunction:: decode_png
.. autofunction:: write_png
.. autofunction:: read_file
.. autofunction:: write_file