The complete PySceneDetect Python API reference can be found here [PySceneDetect Manual]


Creating a new scene detection method is intuitive if you are familiar with Python and OpenCV already. A SceneDetector is an object implementing the following class & methods (only prototypes are shown as an example):

from scenedetect.scene_detector import SceneDetector

class CustomDetector(SceneDetector):
    """CustomDetector class to implement a scene detection algorithm."""
    def __init__(self):
        pass

    def process_frame(self, frame_num, frame_img, frame_metrics, scene_list):
        """Computes/stores metrics and detects any scene changes.

        Prototype method, no actual detection.
        """
        return

    def post_process(self, scene_list):
        pass

See the actual scenedetect/scene_detector.py source file for specific details. Alternatively, you can call help(SceneDetector) from a Python REPL. For examples of actual detection algorithm implementations, see the source files in the scenedetect/detectors/ directory (e.g. threshold_detector.py, content_detector.py).

Processing is done by calling the process_frame(...) function for all frames in the video, followed by post_process(...) (optional) after the final frame. Scene cuts are detected and added to the passed list object in both cases.

process_frame(...) is called for each frame in sequence, passing the following arguments:

  • frame_num: the number of the current frame being processed
  • frame_img: frame returned video file or stream (accessible as NumPy array)
  • frame_metrics: dictionary for memoizing results of detection algorithm calculations for quicker subsequent analyses (if possible)
  • scene_list: List containing the frame numbers where all scene cuts/breaks occur in the video.

post_process(...) is called after the final frame has been processed, to allow for any stored scene cuts to be written if required (e.g. in the case of the ThresholdDetector).

You may also want to look into the implementation of current detectors to understand how frame metrics are saved/loaded to/from a StatsManager for caching and allowing values to be written to a stats file for users to graph and find trends in to tweak detector options. Also see the section on the SceneManager in the Python API Reference for details.