Overview of Features

  Content-Aware Scene Detection

    Detects breaks in-between content, not only when the video fades to black (although a threshold mode is available as well for those cases).

  Compatible With Many External Tools

    The detected scene boundaries/cuts can be exported in a variety of formats, with the default type (comma-separated HH:MM:SS.nnn values) being ready to copy-and-paste directly into other tools (such as ffmpeg, mkvmerge, etc...) for splitting and/or re-encoding the video.

  Statistical Video Analysis

    Can output a spreadsheet-compatible file for analyzing trends in a particular video file, to determine the optimal threshold values to use with specific scene detection methods/algorithms.

  Extendible and Embeddable

    Written in Python, and designed with an easy-to-use and extendable API, PySceneDetect is ideal for embedding into other programs, or to implement custom methods/algorithms of scene detection for specific applications (e.g. analyzing security camera footage).

Features in Current Release

  • exports list of scenes to .CSV file and terminal (both timecodes and frame numbers) with list-scenes command
  • exports timecodes in standard format (HH:MM:SS.nnn), comma-separated for easy copy-and-paste into external tools and analysis with spreadsheet software
  • statistics/analysis mode to export frame-by-frame video metrics via the -s [FILE]/--stats [FILE] argument (e.g. --stats metrics.csv)
  • output-suppression (quiet) mode for better automation with external scripts/programs (-q/--quiet)
  • save an image of the first and last frame of each detected scene via the save-images command
  • split the input video automatically if ffmpeg or mkvmerge is available via the split-video command

Scene Detection Methods

  • threshold scene detection (detect-threshold): analyzes video for changes in average frame intensity/brightness
  • content-aware scene detection (detect-content): based on changes between frames in the HSV color space
  • adaptive content scene detection (detect-adaptive): based on detect-content but handles fast camera movement better in some cases

For a detailed explanation of how a particular scene detection method/algorithm works, see the Scene Detection Method Details Section in the Documentation & Reference.

Version Roadmap

Future version roadmaps are now tracked as milestones (link). Specific issues/features that are queued up for the very next release will have the backlog tag, and issues/features being worked on will have the status: in progress tag. Also note that bug reports as well as additional feature requests can be submitted via the issue tracker; read the Bug Reports and Contributing page for details.

Planned Features for Future Releases

The following features are under consideration for future releases of PySceneDetect. Feel free to jump in and help out!

  • automatic threshold detection for the current scene detection methods (can simply be an ouptut message indicating "Predicted Best Threshold: X")
  • optional suppression of short-length flashes/bursts of light [#35]
  • colour histogram-based scene detection algorithm in the HSV/HSL colourspace [#53]
  • perceptual hash based scene detection
  • improve robustness of content-aware detection by combining with edge detection (similar to MATLAB-based scene change detector)
  • adaptive bias for fade in/out interpolation
  • multithreaded implementation of detection algorithms for improved performance
  • GUI for easier previewing and threshold setting (will be GTK+ 3 based via PyGObject)
  • export scenes in chapter/XML format
  • additional timecode formats