adobe-research / deepafx-st Goto Github PK

Hello!

When I run the script:

(deepafx-st) E:\CODE\DeepAFx-ST>python scripts/process.py -i "E:\CODE\DeepAFx-ST\audio files\raw\160 JAZZ DNB2_MdcL3.wav" -r "E:\CODE\DeepAFx-ST\audio files\target\05 NOT TiGHT.wav" -c "E:\CODE\DeepAFx-ST\checkpoints\style\jamendo\autodiff\lightning_logs\version_0\checkpoints\epoch=362-step=1210241-val-jamendo-autodiff.ckpt"

I encounter a runtime error:

Resampling to 24000 Hz...
Traceback (most recent call last):
  File "scripts/process.py", line 89, in <module>
    x_24000 = torch.tensor(resampy.resample(x.view(-1).numpy(), x_sr, 24000))
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.

Any ideas how I can resolve this?

System specs:
Windows 10
Anaconda Python
cmd.exe

I want to process an entire audio file, but the code currently uses only five seconds from the input and reference.

When I comment these out in process.py, it returns the processed file, but the audio seems to appear more than once in the output.
x_24000 = x_24000[0:1, : 24000 * 5]
r_24000 = r_24000[0:1, : 24000 * 5]

hi @csteinmetz1 ,

great work.
hoping that the inference notebook would be ready soon on google colab.

there are an EQ and Compressor in "system.processor"
how can I get the detail?

if run process.py with option "--time", it crashed with "forward() got an unexpected keyword argument 'time_it'":

process.py -i examples/voice_raw.wav -r examples/voice_produced.wav --time -c checkpoints/style/libritts/tcn1/lightning_logs/version_1/checkpoints/epoch=367-step=1226911-val-libritts-tcn1.ckpt

Exception has occurred: TypeError (note: full exception trace is shown but execution is paused at: _run_module_as_main)
forward() got an unexpected keyword argument 'time_it'
File "C:\Users\xxx\anaconda3\envs\afx\Lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "D:\DeepAFx-ST-0.1.0\scripts\process.py", line 130, in
y_hat, p, e, encoder_time_sec, dsp_time_sec = system(
File "C:\Users\xxx\anaconda3\envs\afx\Lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\Users\xxx\anaconda3\envs\afx\Lib\runpy.py", line 194, in _run_module_as_main (Current frame)
return _run_code(code, main_globals, None,

Is it possible to change the resample from 24000 to 44100? Ideally, I would like to get the 20hz-20khz bandwidth.

Is the google colab available anywhere or not ? The link on the GitHub does not work :/ Thanks !

I attempted to improve DeepAFx-ST. Here's what I did.

Download the zip from https://github.com/adobe-research/DeepAFx-ST and extract it.

Open Notepad++, press CTRL+SHIFT+F, find 24000, replace 44100, set the directory, replace in files.

At this point you can safely add the checkpoints and examples.

Edit scripts/process.py
Replace x_44100 = torch.tensor(resampy.resample(x.view(-1).numpy(), x_sr, 44100)) with x_44100 = torch.tensor(resampy.resample(x.reshape(-1).numpy(), x_sr, 44100))
Under x_44100 = x_44100.view(1, -1) insert x_44100 = x_44100[0:1, : x_44100.shape[-1] // 2]
Under x_44100 = x insert x_44100 = x_44100[0:1, : x_44100.shape[-1]]
Replace r_44100 = torch.tensor(resampy.resample(r.view(-1).numpy(), r_sr, 44100)) with r_44100 = torch.tensor(resampy.resample(r.reshape(-1).numpy(), r_sr, 44100))
Under r_44100 = r_44100.view(1, -1) insert r_44100 = r_44100[0:1, : r_44100.shape[-1] // 2]
Under r_44100 = r insert r_44100 = r_44100[0:1, : r_44100.shape[-1]]

Remove x_44100 = x_44100[0:1, : 44100 * 5]
Remove r_44100 = r_44100[0:1, : 44100 * 5]

Replace filename = os.path.basename(args.input).replace(".wav", "") with filename = os.path.splitext(os.path.basename(args.input))[0]
Remove reference = os.path.basename(args.reference).replace(".wav", "")
Replace out_filepath = os.path.join(dirname, f"{filename}_out_ref={reference}.wav") with out_filepath = os.path.join(dirname, f"{filename}_DeepAFx-ST.wav")
Remove in_filepath = os.path.join(dirname, f"{filename}_in.wav")
Remove torchaudio.save(in_filepath, x_44100.cpu().view(1, -1), 44100)

You should be good to go!

It's possible that this approach may have broken some things not related to processing.