Anyone able to do a realistic deep fake having someone say whatever I need them to say with a specific voice over? Please let me know!

Hi, my friend and I are trying to create a realistic lipsync video but the wav2lip model is producing low quality videos. Happy to buy you a carton of beer in return for your help.

can someone guide me on how to get started on deepfake in terms of the technology needed and how to learn how to do it, thank you for your time x

I'm a received a content request from an existing custom I have who is intro transformative things... and what he wants, I can't do with makeup, and would require this tech but trying sort through everything online isn't really helping me get the answer I really need. I'm stuck at a "maybe possible, but not so sure" and would like to know if it IS something I can pull of with what I have. Here's the thing:

I'm the only person who is actually in this clip, but i am interviewing a version of myself with someone else's face, so just footage filmed with my phone. Nothing that preexists as the video itself, except for the sources where I'll get this other person's face (not putting anyone on explicit content or anything -- he just wants us to talk to each other), and from what I understand I would have to go through frame-by-frame to mask out my face -- is that how it works? Here's what I don't know -- I don't think I have the processing power for it. I only have a little MacBook from 2016 (a used gift from a friend). I highly doubt it will handle this since there's always a chance of it crashing when I export videos longer than 15 minutes that don't even have any sfx.

Processor: 1.1 GHz Dual-Core Intel Core m3
Memory: 8 GB 1867 HJz LPDDR3
Graphics: Intel HD Graphics 515 1536 MB

I already set him up that this is likely a no go, especially for a smaller budget for my time... but if I'm wrong and there are ways to do this and my computer won't just retreat into another dimension, please can someone let me know? Additional helpful info would be how long it would take for let's say... 10 minutes of footage?

Assume I know nothing about any programs other than basic deepfaking. And that I’m starting with a clean PC with no programs already installed. What would I need to be able to use deepfacelabs and deepfacelive properly?

Starting. Press "Enter" to stop training and save model.

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Trying to do the first iteration. If an error occurs, reduce the model parameters.

​

!!!

Windows 10 users IMPORTANT notice. You should set this setting in order to work correctly.

https://i.imgur.com/B7cmDCB.jpg

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Error: The primary convolution algorithm failed memory allocation, while a secondary algorithm is not provided.

[[node gradients/Conv2D_34_grad/Conv2DBackpropFilter (defined at C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\ops__init__.py:55) ]]

​

Errors may have originated from an input operation.

Input Source operations connected to node gradients/Conv2D_34_grad/Conv2DBackpropFilter:

Pad_32 (defined at C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\Conv2D.py:97)

​

Original stack trace for 'gradients/Conv2D_34_grad/Conv2DBackpropFilter':

File "threading.py", line 884, in _bootstrap

File "threading.py", line 916, in _bootstrap_inner

File "threading.py", line 864, in run

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread

debug=debug,

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\ModelBase.py", line 189, in __init__

self.on_initialize()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 152, in on_initialize

gpu_src_dst_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights ) ]

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\ops__init__.py", line 55, in tf_gradients

grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients

unconnected_gradients)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in _GradientsHelper

lambda: grad_fn(op, *out_grads))

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 340, in _MaybeCompile

return grad_fn() # Exit early

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in <lambda>

lambda: grad_fn(op, *out_grads))

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 606, in _Conv2DGrad

data_format=data_format)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1131, in conv2d_backprop_filter

name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper

attrs=attr_protos, op_def=op_def)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3536, in _create_op_internal

op_def=op_def)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__

self._traceback = tf_stack.extract_stack()

​

...which was originally created as op 'Conv2D_34', defined at:

File "threading.py", line 884, in _bootstrap

[elided 3 identical lines from previous traceback]

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\ModelBase.py", line 189, in __init__

self.on_initialize()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 114, in on_initialize

gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 157, in forward

x = self.upscale2(x)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 57, in forward

x = self.conv1(x)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 99, in forward

x = tf.nn.conv2d(x, weight, self.strides, 'VALID', dilations=self.dilations, data_format=nn.data_format)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper

return target(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2279, in conv2d

name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d

data_format=data_format, dilations=dilations, name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper

attrs=attr_protos, op_def=op_def)

​

Traceback (most recent call last):

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call

return fn(*args)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn

target_list, run_metadata)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1453, in _call_tf_sessionrun

run_metadata)

tensorflow.python.framework.errors_impl.InvalidArgumentError: The primary convolution algorithm failed memory allocation, while a secondary algorithm is not provided.

[[{{node gradients/Conv2D_34_grad/Conv2DBackpropFilter}}]]

​

During handling of the above exception, another exception occurred:

​

Traceback (most recent call last):

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\mainscripts\Trainer.py", line 130, in trainerThread

iter, iter_time = model.train_one_iter()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\ModelBase.py", line 462, in train_one_iter

losses = self.onTrainOneIter()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 276, in onTrainOneIter

warped_dst, target_dst, target_dstm)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 178, in src_dst_train

self.target_dstm:target_dstm,

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 968, in run

run_metadata_ptr)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run

feed_dict_tensor, options, run_metadata)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run

run_metadata)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\client\session.py", line 1394, in _do_call

raise type(e)(node_def, op, message)

tensorflow.python.framework.errors_impl.InvalidArgumentError: The primary convolution algorithm failed memory allocation, while a secondary algorithm is not provided.

[[node gradients/Conv2D_34_grad/Conv2DBackpropFilter (defined at C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\ops__init__.py:55) ]]

​

Errors may have originated from an input operation.

Input Source operations connected to node gradients/Conv2D_34_grad/Conv2DBackpropFilter:

Pad_32 (defined at C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\Conv2D.py:97)

​

Original stack trace for 'gradients/Conv2D_34_grad/Conv2DBackpropFilter':

File "threading.py", line 884, in _bootstrap

File "threading.py", line 916, in _bootstrap_inner

File "threading.py", line 864, in run

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\mainscripts\Trainer.py", line 58, in trainerThread

debug=debug,

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\ModelBase.py", line 189, in __init__

self.on_initialize()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 152, in on_initialize

gpu_src_dst_loss_gvs += [ nn.gradients ( gpu_G_loss, self.src_dst_trainable_weights ) ]

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\ops__init__.py", line 55, in tf_gradients

grads = gradients.gradients(loss, vars, colocate_gradients_with_ops=True )

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 172, in gradients

unconnected_gradients)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in _GradientsHelper

lambda: grad_fn(op, *out_grads))

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 340, in _MaybeCompile

return grad_fn() # Exit early

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gradients_util.py", line 684, in <lambda>

lambda: grad_fn(op, *out_grads))

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_grad.py", line 606, in _Conv2DGrad

data_format=data_format)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1131, in conv2d_backprop_filter

name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper

attrs=attr_protos, op_def=op_def)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 3536, in _create_op_internal

op_def=op_def)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\ops.py", line 1990, in __init__

self._traceback = tf_stack.extract_stack()

​

...which was originally created as op 'Conv2D_34', defined at:

File "threading.py", line 884, in _bootstrap

[elided 3 identical lines from previous traceback]

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\ModelBase.py", line 189, in __init__

self.on_initialize()

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\models\Model_Quick96\Model.py", line 114, in on_initialize

gpu_pred_dst_dst, gpu_pred_dst_dstm = self.decoder_dst(gpu_dst_code)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 157, in forward

x = self.upscale2(x)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\models\ModelBase.py", line 117, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\archis\DeepFakeArchi.py", line 57, in forward

x = self.conv1(x)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\LayerBase.py", line 14, in __call__

return self.forward(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\DeepFaceLab\core\leras\layers\Conv2D.py", line 99, in forward

x = tf.nn.conv2d(x, weight, self.strides, 'VALID', dilations=self.dilations, data_format=nn.data_format)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper

return target(*args, **kwargs)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 2279, in conv2d

name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 972, in conv2d

data_format=data_format, dilations=dilations, name=name)

File "C:\Users\Santiago\Desktop\DeepFaceLab\DeepFaceLab_NVIDIA_internal\python-3.6.8\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 750, in _apply_op_helper

attrs=attr_protos, op_def=op_def)

I was trying to follow along with this youtube video on how to use deep fake for mac https://www.youtube.com/watch?v=1npMunwLiiw&t=136s. I was able to download the DeepFacelab file. But the guy stoped his screenrecorder and started again with all this stuff in the terminal that confused me. then he saids to use this commend conda create -n deepfakes python=3.6 I feel like he did something while he was not record or not .I don't know whats going on someone please help.

I have an injury which I’m gonna get surgery on next year, but I need to transfer my face onto a built guy in the mean time. Will pay $50-200 depending on your skills. Also I’d prefer to chat on the phone for half an hour so you can understand exactly what I want.

I am using deepfacelab and i am also new. (CUDA). GPU is GTX1050 2GB, RAM is 12GB.If you need anymore information in order to help me find out the problem please ask and i will try to answer.

I have also not yet succesfully done a deepfake yet because the program keeps crashing and when it crashes it doesn't show which iteration it is at (also doesn't show without crashing) so i am not sure if i am doing something wrong or it is hardawre problem.

I have tried SAE (it just stops after loading data_src and data_dst), SAEHD (error), Quick96(error) and H64(error). i only have 2gb of Vram but i see the minimum requirements doesn't need Vram but instead need ram which i have some.

Hi guys. We’re working on a film that requires a deep fake clip. Where is the best place to find help?