| import torch |
| import time |
| import os |
|
|
| path_id = "" |
| checkpoint_path="wav2lip/wav2lip_gan.pth" |
| outfile="out.mp4" |
| audiofile="tmp.wav" |
| imgfile="avatar.png" |
| driverfile="face_vid2vid/assets/driver06.mp4" |
| animatedfile="animated.mp4" |
| static=False |
| fps=25 |
| pads=[0, 10, 0, 0] |
| face_det_batch_size=16 |
| wav2lip_batch_size=128 |
| resize_factor=0.5 |
| crop=[0, -1, 0, -1] |
| box=[-1, -1, -1, -1] |
| img_size = 96 |
| rotate=False |
| nosmooth=False |
| mel_step_size = 16 |
| device = 'cuda' if torch.cuda.is_available() else 'cpu' |
| print('Using {} for inference.'.format(device)) |
|
|
| import warnings |
| warnings.filterwarnings('ignore') |
|
|
| def init_path_id(): |
| path_id = str(int(time.time())) |
| path = os.path.join("temp", path_id) |
| os.makedirs(path, exist_ok=True) |
| return path_id, path |
|
|
|
|
|
|
