Skip to main content

Extract metadata from video.

Project description

Extract meta data from video file

Metadata is text inside the video file that references the video. The Meta information of a video shows that what is included in the video and what type of content is available in the video.

Before getting into extraction, first you need to install ffmpeg.

- Ubuntu

sudo apt-get install ffmpeg

- Windows

Download ffmpeg software from FFMPEG official website. Unzip the file and add the bin folder to environment path.

Using MediaInfo class

	media_obj = Mediainfo()
	or
	media_obj = Mediainfo(VIDEO_PATH) # VIDEO_PATH must be string

Set video path if not passed

	media_obj.video_path = 'video_path'

Get video path

	VIDEO_PATH = media_obj.video_path

Extract metadata

	metadata = media_obj.getVideoDetail()

Sample of Metadata of video

{'DISPOSITION': {'default': '1', 'dub': '0', 'original': '0', 'comment': '0', 'lyrics': '0', 'karaoke': '0', 'forced': '0', 'hearing_impaired': '0', 'visual_impaired': '0', 'clean_effects': '0', 'attached_pic': '0', 'timed_thumbnails': '0'}, 'TAG': {'rotate': '90', 'creation_time': '2020-01-15T10:35:59.000000Z', 'language': 'eng', 'handler_name': 'VideoHandle'}, 'index': '0', 'codec_name': 'h264', 'codec_long_name': 'H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10', 'profile': 'High', 'codec_type': 'video', 'codec_time_base': '133393/3870000', 'codec_tag_string': 'avc1', 'codec_tag': '0x31637661', 'width': '1440', 'height': '1080', 'coded_width': '1440', 'coded_height': '1088', 'has_b_frames': '0', 'sample_aspect_ratio': '1:1', 'display_aspect_ratio': '4:3', 'pix_fmt': 'yuv420p', 'level': '40', 'color_range': 'tv', 'color_space': 'bt709', 'color_transfer': 'bt709', 'color_primaries': 'bt709', 'chroma_location': 'left', 'field_order': 'unknown', 'timecode': 'N/A', 'refs': '1', 'is_avc': 'true', 'nal_length_size': '4', 'id': 'N/A', 'r_frame_rate': '30/1', 'avg_frame_rate': '1935000/133393', 'time_base': '1/90000', 'start_pts': '0', 'start_time': '0.000000', 'duration_ts': '266786', 'duration': '2.964289', 'bit_rate': '11845320', 'max_bit_rate': 'N/A', 'bits_per_raw_sample': '8', 'nb_frames': '43', 'nb_read_frames': 'N/A', 'nb_read_packets': 'N/A', 'side_data_type': 'Display Matrix', 'displaymatrix': '', 'rotation': '-90'}

Extract frame from video

	frame = Extractframes(VIDEO_PATH)
	frame.extract_frames() # frame_path='', index=0 as optional arguments.

Project details


Release history Release notifications | RSS feed

This version

1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

VMData-1.0.tar.gz (3.9 kB view details)

Uploaded Source

File details

Details for the file VMData-1.0.tar.gz.

File metadata

  • Download URL: VMData-1.0.tar.gz
  • Upload date:
  • Size: 3.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.5

File hashes

Hashes for VMData-1.0.tar.gz
Algorithm Hash digest
SHA256 a7df42e0a43e1ec06a03aa417394a1902648fa30dca3ebac3a817f54a15f3d71
MD5 b433f8cd7e64b26e8c60ccdce752c191
BLAKE2b-256 410ecdc1c0bf62125bff119307e1d1c67fd7df1906e3501e72165d0b571bf76d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page