def run(self):
try:
stats = scenedetect.stats_manager.StatsManager()
scenemgr = scenedetect.SceneManager(stats)
scenemgr.add_detector(scenedetect.ContentDetector())
scenemgr.detect_scenes(frame_source=self)
if self.scenes.stats is None:
self.scenes.stats = numpy.nan * \
numpy.zeros((self.scenes.source.framecount - 1, 4))
H, W = self.scenes.stats.shape
if H < self.scenes.prev.framecount - 1 or W < 4:
newstats = numpy.nan * \
numpy.zeros((self.scenes.source.framecount - 1, 4))
newstats[:H, :W] = self.scenes.stats
self.scenes.stats = newstats
if isinstance(self.scenes.prev, BaseFilter):
start = self.scenes.prev.cumulativeIndexReverseMap[self._start
+ 1]
else:
start = self._start
if (self._end >= self.scenes.prev.framecount
or not isinstance(self.scenes.prev, BaseFilter)):
end = self.scenes.source.framecount
else:
end = self.scenes.prev.cumulativeIndexReverseMap[self._end]
for m in range(start, end):
if isinstance(self.scenes.prev, BaseFilter):
n = self.scenes.prev.cumulativeIndexMap[m]
else:
n = m
if n > 0:
self.scenes.stats[m - 1] = stats.get_metrics(
n - self._start,
["content_val", "delta_hue", "delta_sat", "delta_lum"])
else:
self.scenes.stats[m - 1] = numpy.nan
finally:
if callable(self.notify_complete):
self.notify_complete()
def analyze_video(video_file,
threshold=30,
min_scene_len=10,
downscale_factor=1):
# First, load into a video manager
video_mgr = sd.VideoManager([video_file])
stats_mgr = sd.stats_manager.StatsManager()
scene_mgr = sd.SceneManager(stats_mgr)
# Add a content detector
scene_mgr.add_detector(
sd.ContentDetector(threshold=threshold, min_scene_len=min_scene_len))
# Start the video manager
video_mgr.set_downscale_factor(downscale_factor)
video_mgr.start()
# Detect the scenes
scene_mgr.detect_scenes(frame_source=video_mgr, show_progress=True)
# Retrieve scene list
scene_mgr_list = scene_mgr.get_scene_list(base_timecode)
# Initialize scene list for analysis
scene_list = []
# Build our list from the frame_timecode objects
for scene in scene_mgr_list:
start_frame, end_frame = scene
start_frame = start_frame.frame_num
scene_list.append(start_frame)
# Extract some info
video_fps = end_frame.framerate
frames_read = end_frame.frame_num
# Release the video manager
video_mgr.release()
return (video_fps, frames_read, scene_list)
import gc
import scenedetect as sd
from moviepy.editor import *
if __name__ == '__main__':
# Specify video location here
video_file = '/media/unraid/Datasets/QuantitativeEditing/To Analyze/Bad Lip Reading_2018_Sample of My Pasta.mkv'
outfile_dir = '/media/unraid/Datasets/QuantitativeEditing/Parameter Screen/'
outfile_prefix = 'Bad Lip Reading_2018_Sample of My Pasta_'
# First, load into a video manager
video_mgr = sd.VideoManager([video_file])
stats_mgr = sd.stats_manager.StatsManager()
scene_mgr = sd.SceneManager(stats_mgr)
# Specify range to vary for threshold value
for threshold in range(22, 41):
# Try a couple different minimum scene lengths for each threshold
for min_scene_len in [5, 10, 15]:
# Add a content detector
scene_mgr.add_detector(
sd.ContentDetector(threshold=threshold,
min_scene_len=min_scene_len))
# Get the starting timecode
base_timecode = video_mgr.get_base_timecode()
print("Analyzig file {} with params:".format(fn))
print(" * Threshold = {}".format(thr))
print(" * Min length = {}".format(minlen))
print(" * Max length = {}".format(maxlen))
with open(fn) as json_file:
VL = json.load(json_file)
vfile = VL["Filename"]
print("Processing {}".format(vfile))
video_manager = sc.VideoManager([vfile])
stats_manager = sc.stats_manager.StatsManager()
scene_manager = sc.SceneManager(stats_manager)
scene_manager.add_detector(sc.ContentDetector(threshold=thr))
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)
if categ_name not in VL["Categories"]:
VL["Categories"].append(categ_name)
scenez = []
print(name)
yt.register_on_progress_callback(progress_fn)
fps = stream.fps
name = yt.title.replace(" ", "_")
stream.download(output_path="./data", filename=name + " 30")
# In[44]:
scene_list = []
path = "data/47_Taco_Vs_1_Taco 30.mp4"
video_mgr = scenedetect.VideoManager([path]) #put your filename in this line
stats_mgr = scenedetect.stats_manager.StatsManager()
scene_mgr = scenedetect.SceneManager(stats_mgr)
# Now add the content detector
scene_mgr.add_detector(
scenedetect.ContentDetector(threshold=60, min_scene_len=5 * 30))
# Start the video manager
downscale_factor = 1
video_mgr.set_downscale_factor(downscale_factor)
video_mgr.start()
# Detect the scenes
scene_mgr.detect_scenes(frame_source=video_mgr, show_progress=True)
# In[46]: