This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020. For HD commercial model, please try out Sync Labs
function
python3 inference.py --checkpoint_path color_sync/checkpoint_step000030000.pth --face DVD/1.PNG --audio DVD/2.wav
I add HD network 192 settings, which is why 192 has this error
Traceback (most recent call last):
File "inference.py", line 78, in face_detect
predictions.extend(detector.get_detections_for_batch(np.array(images[i:i + batch_size])))
File "/home/mist/Wav2Lip-master/face_detection/api.py", line 66, in get_detections_for_batch
detected_faces = self.face_detector.detect_from_batch(images.copy())
File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/sfd_detector.py", line 42, in detect_from_batch
bboxlists = batch_detect(self.face_detector, images, device=self.device)
File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/detect.py", line 68, in batch_detect
olist = net(imgs)
File "/mistgpu/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, *kwargs)
File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/net_s3fd.py", line 71, in forward
h = F.relu(self.conv1_1(x))
File "/mistgpu/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(input, **kwargs)
File "/mistgpu/site-packages/torch/nn/modules/conv.py", line 423, in forward
return self._conv_forward(input, self.weight)
File "/mistgpu/site-packages/torch/nn/modules/conv.py", line 420, in _conv_forward
self.padding, self.dilation, self.groups)
RuntimeError: CUDA error: no kernel image is available for execution on the device
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "inference.py", line 280, in
main()
File "inference.py", line 250, in main
total=int(np.ceil(float(len(mel_chunks))/batch_size)))):
File "/mistgpu/site-packages/tqdm/std.py", line 1127, in iter
for obj in iterable:
File "inference.py", line 113, in datagen
face_det_results = face_detect(frames) # BGR2RGB for CNN face detection
File "inference.py", line 81, in face_detect
raise RuntimeError('Image too big to run face detection on GPU. Please use the --resize_factor argument')
RuntimeError: Image too big to run face detection on GPU. Please use the --resize_factor argument
function python3 inference.py --checkpoint_path color_sync/checkpoint_step000030000.pth --face DVD/1.PNG --audio DVD/2.wav I add HD network 192 settings, which is why 192 has this error
Traceback (most recent call last): File "inference.py", line 78, in face_detect predictions.extend(detector.get_detections_for_batch(np.array(images[i:i + batch_size]))) File "/home/mist/Wav2Lip-master/face_detection/api.py", line 66, in get_detections_for_batch detected_faces = self.face_detector.detect_from_batch(images.copy()) File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/sfd_detector.py", line 42, in detect_from_batch bboxlists = batch_detect(self.face_detector, images, device=self.device) File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/detect.py", line 68, in batch_detect olist = net(imgs) File "/mistgpu/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, *kwargs) File "/home/mist/Wav2Lip-master/face_detection/detection/sfd/net_s3fd.py", line 71, in forward h = F.relu(self.conv1_1(x)) File "/mistgpu/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(input, **kwargs) File "/mistgpu/site-packages/torch/nn/modules/conv.py", line 423, in forward return self._conv_forward(input, self.weight) File "/mistgpu/site-packages/torch/nn/modules/conv.py", line 420, in _conv_forward self.padding, self.dilation, self.groups) RuntimeError: CUDA error: no kernel image is available for execution on the device
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "inference.py", line 280, in
main()
File "inference.py", line 250, in main
total=int(np.ceil(float(len(mel_chunks))/batch_size)))):
File "/mistgpu/site-packages/tqdm/std.py", line 1127, in iter
for obj in iterable:
File "inference.py", line 113, in datagen
face_det_results = face_detect(frames) # BGR2RGB for CNN face detection
File "inference.py", line 81, in face_detect
raise RuntimeError('Image too big to run face detection on GPU. Please use the --resize_factor argument')
RuntimeError: Image too big to run face detection on GPU. Please use the --resize_factor argument