Video

Format specification

There are many kinds of video extensions as listed up here.

Datumaro can import a video into video frames by adjusting the start frame, end frame, and step size. Furthermore, with a video_keyframes format, Datumaro can extract keyframes by comparing zero-mean normalized cross correlation (ZNCC) metric between successive frames as following here. Plus, Datumaro provides the options for choosing image extension and name patterns for efficient data management from multiple videos.

Convert video

A Datumaro dataset can be converted from video in the following way:

datum convert -if video_frames -i <path_to_video> -o <output/dir>

Load video through the Python API:

import datumaro as dm

dataset = dm.Dataset.import_from('<path_to_video>', format='video_frames')

Datumaro has few import options for video_frames format, to apply them use the -- after the main command argument. Note that a video has a closed interval of [start-frame, end-frame].

video_frames import options:

• --subset (string) - The name of the subset for the produced dataset items (default: none)

• -p, --name-pattern (string) - Name pattern for the produced images (default: %06d)

• -s, --step (integer) - Frame step (default: 1)

• -b, --start-frame (integer) - Starting frame (default: 0)

• -e, --end-frame (integer) - Finishing frame (default: none)

• -h, --help - Print the help message and exit

Usage:

datum convert -if video_frames [-h] [-i INPUT] [-o OUTPUT]
  [--step STEP] [--start-frame START_FRAME] [--end-frame END_FRAME]

Example: convert a video into frames, use each 30th frame:

datum convert -if video_frames -i video.mp4 -o video-frames -- --step 30

Example: convert a video into frames, save as ‘frame_xxxxxx.png’ files:

datum convert -if video_frames -i video.mp4 -o video-frames -- --image-ext=.png --name-pattern='frame_%%06d'

Example: convert a video into keyframes:

datum convert -if video_keyframes -i video.mp4 -o video-frames