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import json
import numpy as np
import os
from tqdm import tqdm
import subprocess
from glob import glob
import argparse
import time
from utils import crop_video, crop_face, write_video, crop_and_save_audio
from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor, as_completed
import sys
'''
Crop the untrimmed videos into multiple clips using corresponding start and end times, bounding boxes and face landmarks.
Usage:
python crop_videos.py --video_dir /path/to/25-fps-videos --save_path /path/to/save/the/clips --json /path/to/json/file
To save videos using ffmpeg, add "--use_ffmpeg True". This takes additional time but saves disk space.
To additionally save audio as separate wav files, add "--save_audio True"
To merge audio with video and save as a single mp4, add "--merge_audio True"
'''
def write_clip(metadata, vid_p, args):
'''
param metadata: dict containing start, end, bounding boxes, landmarks
param vid_p: path to original untrimmed video at 25fps
param args: main args
'''
for k, clip in enumerate(metadata):
# get the clip frames and corresponding landmarks
video, landmarks = crop_video(vid_p, clip)
# get the cropped sequence around the mouth using the landmarks
crop_seq = crop_face(video, landmarks)
save_video_path = os.path.join(args.save_path, 'videos', vid_p.split('/')[-1][:-4], f'{str(k).zfill(5)}.mp4')
save_audio_path = save_video_path.replace('.mp4','.wav')
# get the audio part of the clip
if args.save_audio or args.merge_audio:
crop_and_save_audio(vid_p, save_audio_path, clip['start'], clip['end'])
# write clip to disk
write_video(save_video_path, crop_seq, save_audio_path, merge_audio=args.merge_audio, use_ffmpeg=args.use_ffmpeg)
return
def main(args):
savepath = args.save_path
json_path = args.json
vid_dir = args.video_dir
video_list = glob(os.path.join(vid_dir, '25_fps_videos*', '*.mp4'))
print(f'Loading json file {json_path}')
data = json.load(open(json_path,'r'))
print(f'Total number of videos {len(video_list)}. Json length {len(data)}')
video_ids = list(data.keys())
count_clips = 0
futures = []
writer_str = 'Ffmpeg' if args.use_ffmpeg else 'cv2.VideoWriter'
print(f'Using {writer_str} to save the cropped clips.')
with tqdm(total=len(video_ids), file=sys.stdout) as progress:
with ProcessPoolExecutor() as executor:
for z in video_ids:
idx = [k for k, i in enumerate(video_list) if z in i]
metadata = data[z]
vid_p = video_list[idx[0]]
os.makedirs(os.path.join(savepath, 'videos', vid_p.split('/')[-1][:-4]), exist_ok=True)
future = executor.submit(write_clip, metadata, vid_p, args)
futures.append(future)
for _ in as_completed(futures):
progress.update()
print(f'Cropping videos completed.')
print(f'Getting the labels.')
labels = {}
for z in tqdm(video_ids):
metadata = data[z]
for k, clip in enumerate(metadata):
labk = clip['label']
fi = os.path.join('videos', vid_p.split('/')[-1][:-4], f'{str(k).zfill(5)}.mp4')
labels[fi] = labk
label_file = f'{args.save_path}/labels.json'
with open(label_file, 'w', encoding='utf-8') as f:
json.dump(labels, f)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Vhisper crop videos')
parser.add_argument('--save_path', type=str, default='', help='Path for saving.')
parser.add_argument('--json', type=str, default='', help='Json path')
parser.add_argument('--video_dir', type=str, default='', help='Path to directory where original videos are stored.')
parser.add_argument('--save_audio', type=bool, default=False, help='Whether to save audio info.')
parser.add_argument('--merge_audio', type=bool, default=False, help='Whether to merge audio with the video when saving.')
parser.add_argument('--use_ffmpeg', type=bool, default=False, help='Whether to use ffmpeg instead of cv2 for saving the video.')
args = parser.parse_args()
tic = time.time()
main(args)
print(f'Elpased total time for processing: {time.time()-tic} seconds')
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