mindspore.dataset.vision.read_video
- mindspore.dataset.vision.read_video(filename, start_pts=0, end_pts=None, pts_unit='pts')[source]
Read the video, audio, metadata from a video file.
It supports AVI, H264, H265, MOV, MP4, WMV file formats.
- Parameters
filename (str) – The path to the video file to be read.
start_pts (Union[float, Fraction, int], optional) – The start presentation timestamp of the video. Default: 0.
end_pts (Union[float, Fraction, int], optional) – The end presentation timestamp of the video. Default: None. The None is represented by 2147483647.
pts_unit (str, optional) – The unit of the timestamps. It can be any of ["pts", "sec"]. Default: "pts".
- Returns
numpy.ndarray, four dimensions uint8 data for video. The format is [T, H, W, C]. T is the number of frames, H is the height, W is the width, C is the channel for RGB.
numpy.ndarray, two dimensions float for audio. The format is [C, L]. C is the number of channels. L is the length of the points in one channel.
dict, metadata for the video and audio. It contains video_fps data of type float and audio_fps data of type int.
- Raises
TypeError – If filename is not of type str.
TypeError – If start_pts is not of type [float, Fraction, int].
TypeError – If end_pts is not of type [float, Fraction, int].
TypeError – If pts_unit is not of type str.
RuntimeError – If filename does not exist, or not a regular file, or not a supported video file.
ValueError – If start_pts is less than 0.
ValueError – If end_pts is less than start_pts.
ValueError – If pts_unit is not in ["pts", "sec"].
- Supported Platforms:
CPU
Examples
>>> import mindspore.dataset.vision as vision >>> video_output, audio_output, metadata_output = vision.read_video("/path/to/file")