How to use the scenedetect.stats_manager.StatsManager function in scenedetect

def test_save_load_from_video(test_video_file):
    """ Test generating and saving some frame metrics from TEST_VIDEO_FILE to a file on disk, and
    loading the file back to ensure the loaded frame metrics agree with those that were saved.
    """
    video_manager = VideoManager([test_video_file])
    stats_manager = StatsManager()
    scene_manager = SceneManager(stats_manager)

    base_timecode = video_manager.get_base_timecode()

    scene_manager.add_detector(ContentDetector())

    try:
        video_fps = video_manager.get_framerate()
        start_time = FrameTimecode('00:00:00', video_fps)
        duration = FrameTimecode('00:00:20', video_fps)

        video_manager.set_duration(start_time=start_time, end_time=duration)
        video_manager.set_downscale_factor()
        video_manager.start()
        scene_manager.detect_scenes(frame_source=video_manager)

def test_detector_metrics(test_video_file):
    """ Test passing StatsManager to a SceneManager and using it for storing the frame metrics
    from a ContentDetector.
    """
    video_manager = VideoManager([test_video_file])
    stats_manager = StatsManager()
    scene_manager = SceneManager(stats_manager)
    #base_timecode = video_manager.get_base_timecode()

    assert not stats_manager._registered_metrics
    scene_manager.add_detector(ContentDetector())
    # add_detector should trigger register_metrics in the StatsManager.
    assert stats_manager._registered_metrics

    try:
        video_fps = video_manager.get_framerate()
        start_time = FrameTimecode('00:00:00', video_fps)
        duration = FrameTimecode('00:00:20', video_fps)

        video_manager.set_duration(start_time=start_time, end_time=duration)
        video_manager.set_downscale_factor()
        video_manager.start()

def test_load_hardcoded_file(test_video_file):
    """ Test loading a stats file with some hard-coded data generated by this test case. """
    from scenedetect.stats_manager import COLUMN_NAME_FPS
    from scenedetect.stats_manager import COLUMN_NAME_FRAME_NUMBER
    from scenedetect.stats_manager import COLUMN_NAME_TIMECODE

    stats_manager = StatsManager()
    stats_file = open(TEST_STATS_FILES[0], 'w')

    try:
        stats_writer = get_csv_writer(stats_file)

        some_metric_key = 'some_metric'
        some_metric_value = 1.2
        some_frame_key = 100
        base_timecode = FrameTimecode(0, 29.97)
        some_frame_timecode = base_timecode + some_frame_key

        # Write out a valid file.
        stats_writer.writerow([COLUMN_NAME_FPS, '%.10f' % base_timecode.get_framerate()])
        stats_writer.writerow(
            [COLUMN_NAME_FRAME_NUMBER, COLUMN_NAME_TIMECODE, some_metric_key])
        stats_writer.writerow(

def test_load_corrupt_stats(test_video_file):
    """ Test loading a corrupted stats file created by outputting data in the wrong format. """
    from scenedetect.stats_manager import COLUMN_NAME_FPS
    from scenedetect.stats_manager import COLUMN_NAME_FRAME_NUMBER
    from scenedetect.stats_manager import COLUMN_NAME_TIMECODE

    stats_manager = StatsManager()

    stats_files = [open(stats_file, 'wt') for stats_file in TEST_STATS_FILES]
    try:

        stats_writers = [get_csv_writer(stats_file) for stats_file in stats_files]

        some_metric_key = 'some_metric'
        some_metric_value = str(1.2)
        some_frame_key = 100
        base_timecode = FrameTimecode(0, 29.97)
        some_frame_timecode = base_timecode + some_frame_key

        # Write out some invalid files.
        # File 0: Blank FPS [StatsFileCorrupt]
        stats_writers[0].writerow([COLUMN_NAME_FPS])
        stats_writers[0].writerow(

def test_metrics():
    """ Test StatsManager metric registration/setting/getting with a set of pre-defined
    key-value pairs (metric_dict).
    """
    metric_dict = {'some_metric': 1.2345, 'another_metric': 6.7890}
    metric_keys = list(metric_dict.keys())

    stats = StatsManager()
    frame_key = 100
    assert not stats.is_save_required()

    stats.register_metrics(metric_keys)

    assert not stats.is_save_required()
    with pytest.raises(FrameMetricRegistered):
        stats.register_metrics(metric_keys)

    assert not stats.metrics_exist(frame_key, metric_keys)
    assert stats.get_metrics(frame_key, metric_keys) == [None] * len(metric_keys)

    stats.set_metrics(frame_key, metric_dict)

    assert stats.is_save_required()

def scene_detect(opt):

  video_manager = VideoManager([os.path.join(opt.avi_dir,opt.reference,'video.avi')])
  stats_manager = StatsManager()
  scene_manager = SceneManager(stats_manager)
  # Add ContentDetector algorithm (constructor takes detector options like threshold).
  scene_manager.add_detector(ContentDetector())
  base_timecode = video_manager.get_base_timecode()

  video_manager.set_downscale_factor()

  video_manager.start()

  scene_manager.detect_scenes(frame_source=video_manager)

  scene_list = scene_manager.get_scene_list(base_timecode)

  savepath = os.path.join(opt.work_dir,opt.reference,'scene.pckl')

  if scene_list == []:

def scene_detect(opt):

  video_manager = VideoManager([os.path.join(opt.avi_dir,opt.reference,'video.avi')])
  stats_manager = StatsManager()
  scene_manager = SceneManager(stats_manager)
  # Add ContentDetector algorithm (constructor takes detector options like threshold).
  scene_manager.add_detector(ContentDetector())
  base_timecode = video_manager.get_base_timecode()

  video_manager.set_downscale_factor()

  video_manager.start()

  scene_manager.detect_scenes(frame_source=video_manager)

  scene_list = scene_manager.get_scene_list(base_timecode)

  savepath = os.path.join(opt.work_dir,'scene.pckl')

  if scene_list == []:

def _open_stats_file(self):

        if self.stats_manager is None:
            self.stats_manager = StatsManager()

        if self.stats_file_path is not None:
            if os.path.exists(self.stats_file_path):
                logging.info('Loading frame metrics from stats file: %s',
                             os.path.basename(self.stats_file_path))
                try:
                    with open(self.stats_file_path, 'rt') as stats_file:
                        self.stats_manager.load_from_csv(stats_file, self.base_timecode)
                except StatsFileCorrupt:
                    error_strs = [
                        'Could not load stats file.', 'Failed to parse stats file:',
                        'Could not load frame metrics from stats file - file is corrupt or not a'
                        ' valid PySceneDetect stats file. If the file exists, ensure that it is'
                        ' a valid stats file CSV, otherwise delete it and run PySceneDetect again'
                        ' to re-generate the stats file.']
                    logging.error('\n'.join(error_strs))

def find_scenes(video_path):
    start_time = time.time()
    print("Analyzing video "+video_path)

    # type: (str) -> List[Tuple[FrameTimecode, FrameTimecode]]
    video_manager = VideoManager([video_path])
    stats_manager = StatsManager()

    # Pass StatsManager to SceneManager to accelerate computing time
    scene_manager = SceneManager(stats_manager)

    # Add ContentDetector algorithm (each detector's constructor
    # takes detector options, e.g. threshold).
    scene_manager.add_detector(ContentDetector())
    base_timecode = video_manager.get_base_timecode()

    # We save our stats file to {VIDEO_PATH}.stats.csv.
    stats_file_path = '%s.stats.csv' % (video_path)

    scene_list = []

    folder = os.path.splitext(video_path)[0]