Skip to content

Latest commit

 

History

History
63 lines (47 loc) · 2.66 KB

README.md

File metadata and controls

63 lines (47 loc) · 2.66 KB

Scene Detection and Video Splitting

In many cases, raw videos contain several scenes and are too long for training. Thus, it is essential to split them into shorter clips based on scenes. Here, we provide code for scene detection and video splitting.

Prepare Meta Files

At this step, you should have a raw video dataset prepared. A meta file of the dataset information is needed for data processing. To create a meta file from a folder, run:

python -m tools.datasets.convert video /path/to/video/folder --output /path/to/save/meta.csv

This should output a .csv file with column path.

If you already have a meta file for the videos and want to keep the information. Make sure the meta file has column id, which is the id for each video, and the video is named as {id}.mp4. The following command will add a new column path to the meta file.

python tools/scene_cut/convert_id_to_path.py /path/to/meta.csv --folder_path /path/to/video/folder

This should output

  • {prefix}_path-filtered.csv with column path (broken videos filtered)
  • {prefix}_path_intact.csv with column path and intact (intact indicating a video is intact or not)

Scene Detection

Install the required dependancies by following our installation instructions's "Data Dependencies" and "Scene Detection" sections.

Make sure the input meta file has column path, which is the path of a video.

python tools/scene_cut/scene_detect.py /path/to/meta.csv

The output is {prefix}_timestamp.csv with column timestamp. Each cell in column timestamp is a list of tuples, with each tuple indicating the start and end timestamp of a scene (e.g., [('00:00:01.234', '00:00:02.345'), ('00:00:03.456', '00:00:04.567')]).

Video Splitting

After obtaining timestamps for scenes, we conduct video splitting (cutting). Make sure the meta file contains column timestamp.

python tools/scene_cut/cut.py /path/to/meta.csv --save_dir /path/to/output/dir

This will save video clips to /path/to/output/dir. The video clips are named as {video_id}_scene-{scene_id}.mp4

To create a new meta file for the generated clips, run:

python -m tools.datasets.convert video /path/to/video/folder --output /path/to/save/meta.csv