Util

Utilities

Split video into frames

Splits a video into separate frames and saves them in a directory. After the splitting, the images can be added into a project using the import command and the image_dir format.

This command is useful for making a dataset from a video file. Unlike direct video reading during model training, which can produce different results if the system environment changes, this command allows to split the video into frames and use them instead, making the dataset reproducible and stable.

This command provides different options like setting the frame step (the -s/--step option), file name pattern (-n/--name-pattern), starting (-b/--start-frame) and finishing (-e/--end-frame) frame etc.

Note that this command is equivalent to the following commands:

datum project create -o proj
datum project import -p proj -f video_frames video.mp4 -- <params>
datum project export -p proj -f image_dir -- <params>

Usage:

datum util split_video [-h] -i SRC_PATH [-o DST_DIR] [--overwrite]
  [-n NAME_PATTERN] [-s STEP] [-b START_FRAME] [-e END_FRAME] [-x IMAGE_EXT]

Parameters:

• -i, --input-path (string) - Path to the video file

• -o, --output-dir (string) - Output directory. By default, a subdirectory in the current directory is used

• --overwrite - Allows overwriting existing files in the output directory, when it is not empty

• -n, --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)

• -x, --image-ext (string) Output image extension (default: .jpg)

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

Example: split a video into frames, use each 30-rd frame:

datum util split_video -i video.mp4 -o video.mp4-frames --step 30

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

datum util split_video -i video.mp4 --image-ext=.png --name-pattern='frame_%%06d'

Example: split a video, add frames and annotations into dataset, export as YOLO:

datum util split_video -i video.avi -o video-frames
datum project create -o proj
datum project import -p proj -f image_dir video-frames
datum project import -p proj -f coco_instances annotations.json
datum project export -p proj -f yolo -- --save-images