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"""
# Copyright 2020 Adobe
# All Rights Reserved.
# NOTICE: Adobe permits you to use, modify, and distribute this file in
# accordance with the terms of the Adobe license agreement accompanying
# it.
"""
import os, glob, time, sys
from src.dataset.utils.Av2Flau_Convertor import Av2Flau_Convertor
out_dir = r'/mnt/nfs/scratch1/yangzhou/PreprocessedVox_imagetranslation'
src_dir = r'/mnt/nfs/scratch1/yangzhou/vox_p3/train'
''' Step 1. Data preparation '''
# landmark extraction
# landmark_extraction(int(sys.argv[1]), int(sys.argv[2]))
def landmark_extraction(si, ei):
'''
:param si: start index
:param ei: end index
:return: save extracted landmarks to out_dir
'''
for folder_name in ['raw_wav', 'raw_fl3d', 'register_fl3d', 'dump', 'tmp_v', 'nn_result', 'ckpt', 'log']:
try:
os.mkdir(os.path.join(out_dir, folder_name))
except:
pass
if(not os.path.isfile(os.path.join(out_dir, 'filename_index.txt'))):
# generate all file list
files = glob.glob1(src_dir, '*.mp4')
with open(os.path.join(out_dir, 'filename_index.txt'), 'w') as f:
for i, file in enumerate(files):
f.write('{} {}\n'.format(i, file))
else:
with open(os.path.join(out_dir, 'filename_index.txt'), 'r') as f:
lines = f.readlines()
print(sys.argv)
for line in lines[si:ei]:
st = time.time()
idx, file = int(line.split(' ')[0]), line.split(' ')[1][:-1]
c = Av2Flau_Convertor(video_dir=os.path.join(src_dir, file),
out_dir=out_dir, idx=idx)
c.convert(show=False) # (save_audio=False, register=False, show=False)
print('Idx: {}, Processed time (min): {}'.format(idx, (time.time() - st) / 60.0))
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