Closed Crazyjoedevola closed 3 years ago
the filelist should be a list of video filenames without the extension.
In your case, 1/00001
would be one line. Similarly other lines for more videos.
Thanks
Should both of them contain the same values?
No....one should contain training set videos, the other the validation set videos.
hmm. I will probably figure it out :) So
I am getting to this point (sorry - i am a REAL NOOB when it comes to this)
Starting Epoch: 0
0it [00:02, ?it/s]
Traceback (most recent call last):
File "hq_wav2lip_train.py", line 443, in
Please specify this as your checkpoint_dir: /content/Wav2Lip/models/
So i think i got it started now. By the way, really cool stuff and I really want to try it, so appreciate you taking the time to answer
I run this, using my own dataset (which is very small to start with, in order to test it). Is this the correct syntax to train for a custom person?
!python hq_wav2lip_train.py --data_root lrs2_preprocessed/ --checkpoint_dir /content/Wav2Lip/models --syncnet_checkpoint_path /content/Wav2Lip/models/lipsync_expert.pth
So far so good. I get something like this as output:
L1: 0.16577447950839996, Sync: 0.0, Percep: 0.6806370615959167 | Fake: 0.7058212161064148, Real: 0.6555213928222656: : 1it [00:02, 3.00s/it]
Starting Epoch: 38
What does the different paremeters mean? L1: Sync: Percep: Fake: Real:
For how may epochs should i train approximately?
I am also curious to know what the different models do
/content/Wav2Lip/models/checkpoint_step000000001.pth
/content/Wav2Lip/models/disc_checkpoint_step000000001.pth
Are any of these the ones i should use when running inference.py?
At around 3000 my values are starting to look odd
L1: 0.025442134588956833, Sync: 0.0, Percep: 27.63102149963379 | Fake: 0.0, Real: 27.63102149963379: : 1it [00:03, 3.38s/it] Starting Epoch: 3003
Can you please help me explain this, or is there something wrong with my training?
What does the different paremeters mean? L1: Sync: Percep: Fake: Real:
I am also curious to know what the different models do
Please check the paper linked in the README.
is there something wrong with my training?
Yes, we cannot really help you if you are training on a single video. You would need lots of training data, such as the LRS2 dataset.
Ok, i can collect many more videos, but what would you say is the least amount in terms of numbers of videos and length?
The released models are trained on 29 hours of video data containing several thousands of identities.
Hi
This is not really what i am thinking about. I thought it would be possible to fine-tune the model with own data that would be much less than the originally trained video. The intention of this would be to achieve better results for the intended "target actor", but maybe that is not possible?
I thought it would be possible to fine-tune the model with own data that would be much less than the originally trained video.
Yes, that is a good idea. It can work, but we have not tried it. So, we are not sure how much data is required, or will plain fine-tuning work, etc.
Thanks for the response. I will close this for now. Great project by the way
@prajwalkr How long have you trained on the LRS2 dataset? And the number and version of GPUs you used.
Hi
What should the train.txt and val.txt contain?
I have preprocessed a mp4 file which generates the individual images into /lrs2_preprocessed/1/00001
When I run the following command:' !python color_syncnet_train.py --data_root /lrs2_preprocessed --checkpoint_dir /content/Wav2Lip/checkpoints
I get the following error if i put empty txt files in the folder ValueError: num_samples should be a positive integer value, but got num_samples=0
If the text files are not present i get this FileNotFoundError: [Errno 2] No such file or directory: 'filelists/train.txt'