Tutorials

[chilinvilin]

Awesome!! I'm glad it worked! The multi-genre model I uploaded is much better than the original base model. However, I'm going to be coming out with an even better one this week. So far the new one I'm making now is outperforming the one I posted.

I'm looking forward to the update...

[chilinvilin]

One more for tonight..

Ozzy Osbourne - Believer (Source Track 96.0 kHz Sample Rate FLAC) https://www.mediafire.com/file/cwc2w.../Believer.flac
Ozzy Osbourne - Believer (Instrumental) https://www.mediafire.com/file/lv2o0...strumental.mp3
Ozzy Osbourne - Believer (Acapella) https://www.mediafire.com/file/v06jh...ever_Vocal.mp3

[rkeane]

i downloaded the new baseline.....how do u get it to activate or batch process or using a genre process or does it recognize what type of music it is....im lost lol

[rkeane]

tried to train but got this error at the end

1 +- 03_bill_mix.mp3 +- 03_bill_inst.mp3
2 +- 04_fasc_mix.mp3 +- 04_fasc_inst.mp3
3 +- 01_amd_mix.mp3 +- 01_amd_inst.mp3
4 +- 02_beat_mix.mp3 +- 02_beat_inst.mp3
0%| | 0/4 [00:00 warnings.warn('PySoundFile failed. Trying audioread instead.')
C:\Users\Robert\AppData\Local\Programs\Python\Pyth on37\lib\site-packages\librosa\core\audio.py:161: UserWarning: PySoundFile failed. Trying audioread instead.
warnings.warn('PySoundFile failed. Trying audioread instead.')
100%|█████████████████████████████████████████████ ███████████████████████████████████████| 4/4 [01:53<00:00, 28.25s/it]
0it [00:00, ?it/s]
# epoch 0
* inner epoch 0
Traceback (most recent call last):
File "train.py", line 223, in
main()
File "train.py", line 194, in main
X_train, y_train, model, optimizer, args.batchsize, instance_loss)
File "train.py", line 75, in train_inner_epoch
return sum_loss / len(X_train)
ZeroDivisionError: division by zero

[Anjok]

tried to train but got this error at the end

1 +- 03_bill_mix.mp3 +- 03_bill_inst.mp3
2 +- 04_fasc_mix.mp3 +- 04_fasc_inst.mp3
3 +- 01_amd_mix.mp3 +- 01_amd_inst.mp3
4 +- 02_beat_mix.mp3 +- 02_beat_inst.mp3
0%| | 0/4 [00:00 warnings.warn('PySoundFile failed. Trying audioread instead.')
C:\Users\Robert\AppData\Local\Programs\Python\Pyth on37\lib\site-packages\librosa\core\audio.py:161: UserWarning: PySoundFile failed. Trying audioread instead.
warnings.warn('PySoundFile failed. Trying audioread instead.')
100%|█████████████████████████████████████████████ ███████████████████████████████████████| 4/4 [01:53<00:00, 28.25s/it]
0it [00:00, ?it/s]
# epoch 0
* inner epoch 0
Traceback (most recent call last):
File "train.py", line 223, in
main()
File "train.py", line 194, in main
X_train, y_train, model, optimizer, args.batchsize, instance_loss)
File "train.py", line 75, in train_inner_epoch
return sum_loss / len(X_train)
ZeroDivisionError: division by zero

This error is due to your training set being too small. You need a bare minimum of 15 pairs in order to start training. Also, if you're training from scratch like this you'll need at LEAST 50-75 pairs for it to be effective at all. Your training/validation numbers won't move with sets any lower than 50; You'll end up wasting your system resources and being sorely disappointed with your models' performance.

If you choose to train with a set between 15-50 pairs, just finetune one of the baseline models (commands in the main thread). I figured out how to train effectively with a GPU, so train with your GPU if you have one.

[Anjok]

A new model has been posted to the main page! Please make sure to use it with the new A.I. provided as it won't work with the old one.

[halofan253]

Hey Anjok! First of all thank you for this awesome AI, it works really well and does a great job separating the tracks.
But now I have a problem with the new model uploaded.
When I tried to run using GPU I get the following error:

Traceback (most recent call last):
File "inference.py", line 104, in
main()
File "inference.py", line 64, in main
pred = model.predict(X_window)
File "C:\Users\KennA\Documents\vocal-removerV2\lib\nets.py", line 79, in predict
h = self.full_band_net(self.bridge(h))
File "C:\Users\KennA\Documents\vocal-removerV2\lib\nets.py", line 34, in __call__
h = self.dec1(h, e1)
File "C:\Users\KennA\Documents\vocal-removerV2\lib\layers.py", line 79, in __call__
x = spec_utils.crop_center(x, skip)
File "C:\Users\KennA\Documents\vocal-removerV2\lib\spec_utils.py", line 20, in crop_center
return torch.cat([h1, h2], dim=1)
RuntimeError: CUDA out of memory. Tried to allocate 384.00 MiB (GPU 0; 2.00 GiB total capacity; 948.49 MiB already allocated; 308.74 MiB free; 137.51 MiB cached)

This didn't happened with the old version. There's a way to solve this? Because using CPU is reaaaally slow. Thank you!

[rkeane]

GPU not much cop mate.....
so how does it work after you have trained it
does it recognize wether its a rock song etc

[Anjok]

Hey Anjok! First of all thank you for this awesome AI, it works really well and does a great job separating the tracks.
But now I have a problem with the new model uploaded.
When I tried to run using GPU I get the following error:

This didn't happened with the old version. There's a way to solve this? Because using CPU is reaaaally slow. Thank you!

You're welcome! I'm glad you've enjoyed it!

To answer your question, this new model is bigger and has more layers, so is requires more V-RAM. Your GPU might not have enough memory for this one sadly :(

[ChrisCall]

I made it to the conversion step and then got an error I can't figure out;

C:\Users\xxxx\Documents\vocal-remover>python inference.py --input Daredevil.mp3 --gpu 0
C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\util\decorators.py:9: NumbaDeprecationWarning: An import was requested from a module that has moved location.
Import requested from: 'numba.decorators', please update to use 'numba.core.decorators' or pin to Numba version 0.48.0. This alias will not be present in Numba version 0.50.0.
from numba.decorators import jit as optional_jit
C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\util\decorators.py:9: NumbaDeprecationWarning: An import was requested from a module that has moved location.
Import of 'jit' requested from: 'numba.decorators', please update to use 'numba.core.decorators' or pin to Numba version 0.48.0. This alias will not be present in Numba version 0.50.0.
from numba.decorators import jit as optional_jit
loading model... done
C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\core\audio.py:161: UserWarning: PySoundFile failed. Trying audioread instead.
warnings.warn('PySoundFile failed. Trying audioread instead.')
loading wave source... Traceback (most recent call last):
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\core\audio.py", line 129, in load
with sf.SoundFile(path) as sf_desc:
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\soundfile.py", line 629, in __init__
self._file = self._open(file, mode_int, closefd)
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\soundfile.py", line 1184, in _open
"Error opening {0!r}: ".format(self.name))
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\soundfile.py", line 1357, in _error_check
raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
RuntimeError: Error opening 'Daredevil.mp3': File contains data in an unknown format.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "inference.py", line 104, in
main()
File "inference.py", line 39, in main
args.input, args.sr, False, dtype=np.float32, res_type='kaiser_fast')
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\core\audio.py", line 162, in load
y, sr_native = __audioread_load(path, offset, duration, dtype)
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\librosa\core\audio.py", line 186, in __audioread_load
with audioread.audio_open(path) as input_file:
File "C:\Users\xxxx\AppData\Local\Programs\Python\Python 37\lib\site-packages\audioread\__init__.py", line 116, in audio_open
raise NoBackendError()
audioread.exceptions.NoBackendError