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. .. 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