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import argparse
import copy
import json
import os
import shutil
from multiprocessing import Pool
from scenedetect import SceneManager, open_video
from scenedetect.detectors import ContentDetector
from scenedetect.video_splitter import split_video_ffmpeg
from tqdm import tqdm
from utils.video_utils import download_video, get_video_path_list
tmp_file_dir = "./tmp"
DEFAULT_FFMPEG_ARGS = '-c:v libx264 -preset veryfast -crf 22 -c:a aac'
def parse_args():
parser = argparse.ArgumentParser(
description = '''Cut video by PySceneDetect''')
parser.add_argument(
'video',
type = str,
help = '''Input format:
1. Local video file path.
2. Video URL.
3. Local root dir path of videos.
4. Local txt file of video urls/local file path, line by line.
''')
parser.add_argument(
'--threshold',
type = float,
nargs='+',
default = [10, 20, 30],
help = 'Threshold list the average change in pixel intensity must exceed to trigger a cut, one-to-one with frame_skip.')
parser.add_argument(
'--frame_skip',
type = int,
nargs='+',
default = [0, 1, 2],
help = 'Number list of frames to skip, coordinate with threshold \
(i.e. process every 1 in N+1 frames, where N is frame_skip, \
processing only 1/N+1 percent of the video, \
speeding up the detection time at the expense of accuracy). One-to-one with threshold.')
parser.add_argument(
'--min_seconds',
type = int,
default = 3,
help = 'Video cut must be longer then min_seconds.')
parser.add_argument(
'--max_seconds',
type = int,
default = 12,
help = 'Video cut must be longer then min_seconds.')
parser.add_argument(
'--save_dir',
type = str,
default = "",
help = 'Video scene cuts save dir, default value means reusing input video dir.')
parser.add_argument(
'--name_template',
type = str,
default = "$VIDEO_NAME-Scene-$SCENE_NUMBER.mp4",
help = 'Video scene cuts save name template.')
parser.add_argument(
'--num_processes',
type = int,
default = os.cpu_count() // 2,
help = 'Number of CPU cores to process the video scene cut.')
parser.add_argument(
"--save_json", action="store_true", help="Whether save json in datasets."
)
args = parser.parse_args()
return args
def split_video_into_scenes(
video_path: str,
threshold: list[float] = [27.0],
frame_skip: list[int] = [0],
min_seconds: int = 3,
max_seconds: int = 8,
save_dir: str = "",
name_template: str = "$VIDEO_NAME-Scene-$SCENE_NUMBER.mp4",
save_json: bool = False ):
# SceneDetect video through casceded (threshold, FPS)
frame_points = []
frame_timecode = {}
fps = 25.0
for thre, f_skip in zip(threshold, frame_skip):
# Open our video, create a scene manager, and add a detector.
video = open_video(video_path, backend='pyav')
scene_manager = SceneManager()
scene_manager.add_detector(
# [ContentDetector, ThresholdDetector, AdaptiveDetector]
ContentDetector(threshold=thre, min_scene_len=10)
)
scene_manager.detect_scenes(video, frame_skip=f_skip, show_progress=False)
scene_list = scene_manager.get_scene_list()
for scene in scene_list:
for frame_time_code in scene:
frame_index = frame_time_code.get_frames()
if frame_index not in frame_points:
frame_points.append(frame_index)
frame_timecode[frame_index] = frame_time_code
fps = frame_time_code.get_framerate()
del video, scene_manager
frame_points = sorted(frame_points)
output_scene_list = []
# Detect No Scene Change
if len(frame_points) == 0:
video = open_video(video_path, backend='pyav')
frame_points = [0, video.duration.get_frames() - 1]
frame_timecode = {
frame_points[0]: video.base_timecode,
frame_points[-1]: video.base_timecode + video.base_timecode + video.duration
}
del video
for idx in range(len(frame_points) - 1):
# Limit save out min seconds
if frame_points[idx+1] - frame_points[idx] < fps * min_seconds:
continue
# Limit save out max seconds
elif frame_points[idx+1] - frame_points[idx] > fps * max_seconds:
tmp_start_timecode = copy.deepcopy(frame_timecode[frame_points[idx]])
tmp_end_timecode = copy.deepcopy(frame_timecode[frame_points[idx]]) + int(max_seconds * fps)
# Average cut by max seconds
while tmp_end_timecode.get_frames() <= frame_points[idx+1]:
output_scene_list.append((
copy.deepcopy(tmp_start_timecode),
copy.deepcopy(tmp_end_timecode)))
tmp_start_timecode += int(max_seconds * fps)
tmp_end_timecode += int(max_seconds * fps)
if tmp_end_timecode.get_frames() > frame_points[idx+1] and frame_points[idx+1] - tmp_start_timecode.get_frames() > fps * min_seconds:
output_scene_list.append((
copy.deepcopy(tmp_start_timecode),
frame_timecode[frame_points[idx+1]]))
del tmp_start_timecode, tmp_end_timecode
continue
output_scene_list.append((
frame_timecode[frame_points[idx]],
frame_timecode[frame_points[idx+1]]))
# Reuse video dir
if save_dir == "":
save_dir = os.path.dirname(video_path)
# Ensure save dir exists
elif not os.path.isdir(save_dir):
os.makedirs(save_dir)
clip_info_path = os.path.join(save_dir, os.path.splitext(os.path.basename(video_path))[0] + '.json')
output_file_template = os.path.join(save_dir, name_template)
split_video_ffmpeg(
video_path,
output_scene_list,
arg_override=DEFAULT_FFMPEG_ARGS,
output_file_template=output_file_template,
show_progress=False,
show_output=False) # ffmpeg print
if save_json:
# Save clip info
json.dump(
[(frame_timecode_tuple[0].get_timecode(), frame_timecode_tuple[1].get_timecode()) for frame_timecode_tuple in output_scene_list],
open(clip_info_path, 'w'),
indent=2
)
return clip_info_path
def process_single_video(args):
video, threshold, frame_skip, min_seconds, max_seconds, save_dir, name_template, save_json = args
basename = os.path.splitext(os.path.basename(video))[0]
# Video URL
if video.startswith("http"):
save_path = os.path.join(tmp_file_dir, f"{basename}.mp4")
download_success = download_video(video, save_path)
if not download_success:
return
video = save_path
# Local video path
else:
if not os.path.isfile(video):
print(f"Video not exists: {video}")
return
# SceneDetect video cut
try:
split_video_into_scenes(
video_path=video,
threshold=threshold,
frame_skip=frame_skip,
min_seconds=min_seconds,
max_seconds=max_seconds,
save_dir=save_dir,
name_template=name_template,
save_json=save_json
)
except Exception as e:
print(e, video)
def main():
# Args
args = parse_args()
video_input = args.video
threshold = args.threshold
frame_skip = args.frame_skip
min_seconds = args.min_seconds
max_seconds = args.max_seconds
save_dir = args.save_dir
name_template = args.name_template
num_processes = args.num_processes
save_json = args.save_json
assert len(threshold) == len(frame_skip), \
"Threshold must one-to-one match frame_skip."
video_list = get_video_path_list(video_input)
args_list = [
(video, threshold, frame_skip, min_seconds, max_seconds, save_dir, name_template, save_json)
for video in video_list
]
with Pool(processes=num_processes) as pool:
with tqdm(total=len(video_list)) as progress_bar:
for _ in pool.imap_unordered(process_single_video, args_list):
progress_bar.update(1)
if __name__ == "__main__":
main()
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