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This commit is contained in:
Anjok07
2022-06-06 15:44:20 -05:00
committed by GitHub
parent aa2dd10834
commit 32a3df2044
3 changed files with 291 additions and 89 deletions
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265
inference_MDX.py
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@@ -9,6 +9,7 @@ import os.path
from datetime import datetime
import pydub
import shutil
import hashlib
import gc
#MDX-Net
@@ -257,9 +258,10 @@ class Predictor():
widget_text.write('Done!\n')
widget_text.write(base_text + 'Performing Noise Reduction... ')
reduction_sen = float(data['noisereduc_s'])/10
print(noise_pro_set)
subprocess.call("lib_v5\\sox\\sox.exe" + ' "' +
f"{str(non_reduced_vocal_path)}" + '" "' + f"{str(vocal_path)}" + '" ' +
"noisered lib_v5\\sox\\mdxnetnoisereduc.prof " + f"{reduction_sen}",
"noisered lib_v5\\sox\\" + noise_pro_set + ".prof " + f"{reduction_sen}",
shell=True, stdout=subprocess.PIPE,
stdin=subprocess.PIPE, stderr=subprocess.PIPE)
update_progress(**progress_kwargs,
@@ -688,6 +690,7 @@ data = {
'inst_only': False,
'n_fft_scale': 6144,
'dim_f': 2048,
'noise_pro_select': 'Auto Select',
'overlap': 0.5,
'shifts': 0,
'margin': 44100,
@@ -747,6 +750,9 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
global model_set
global model_set_name
global stemset_n
global noise_pro_set
global mdx_model_hash
global channel_set
global margin_set
@@ -773,6 +779,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
file_err = "FileNotFoundError"
ffmp_err = """audioread\__init__.py", line 116, in audio_open"""
sf_write_err = "sf.write"
model_adv_set_err = "Got invalid dimensions for input"
try:
with open('errorlog.txt', 'w') as f:
@@ -816,71 +823,169 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
source_val_set = 0
stem_name = '(Bass)'
if data['mdxnetModel'] == 'UVR-MDX-NET 1':
model_set = 'UVR_MDXNET_1_9703'
model_set_name = 'UVR_MDXNET_1_9703'
modeltype = 'v'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 2':
model_set = 'UVR_MDXNET_2_9682'
model_set_name = 'UVR_MDXNET_2_9682'
modeltype = 'v'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 3':
model_set = 'UVR_MDXNET_3_9662'
model_set_name = 'UVR_MDXNET_3_9662'
modeltype = 'v'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET Karaoke':
model_set = 'UVR_MDXNET_KARA'
model_set_name = 'UVR_MDXNET_Karaoke'
modeltype = 'v'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'other':
model_set = 'other'
model_set_name = 'other'
modeltype = 'o'
stemset_n = '(Other)'
source_val = 2
n_fft_scale_set=8192
dim_f_set=2048
elif data['mdxnetModel'] == 'drums':
model_set = 'drums'
model_set_name = 'drums'
modeltype = 'd'
stemset_n = '(Drums)'
source_val = 1
n_fft_scale_set=4096
dim_f_set=2048
elif data['mdxnetModel'] == 'bass':
model_set = 'bass'
model_set_name = 'bass'
modeltype = 'b'
stemset_n = '(Bass)'
source_val = 0
n_fft_scale_set=16384
dim_f_set=2048
else:
model_set = data['mdxnetModel']
model_set_name = data['mdxnetModel']
modeltype = stemset
stemset_n = stem_name
source_val = source_val_set
n_fft_scale_set=int(data['n_fft_scale'])
dim_f_set=int(data['dim_f'])
try:
if data['mdxnetModel'] == 'UVR-MDX-NET 1':
model_set = 'UVR_MDXNET_1_9703'
model_set_name = 'UVR_MDXNET_1_9703'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 2':
model_set = 'UVR_MDXNET_2_9682'
model_set_name = 'UVR_MDXNET_2_9682'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 3':
model_set = 'UVR_MDXNET_3_9662'
model_set_name = 'UVR_MDXNET_3_9662'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET Karaoke':
model_set = 'UVR_MDXNET_KARA'
model_set_name = 'UVR_MDXNET_Karaoke'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'other':
model_set = 'other'
model_set_name = 'other'
modeltype = 'o'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Other)'
source_val = 2
n_fft_scale_set=8192
dim_f_set=2048
elif data['mdxnetModel'] == 'drums':
model_set = 'drums'
model_set_name = 'drums'
modeltype = 'd'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Drums)'
source_val = 1
n_fft_scale_set=4096
dim_f_set=2048
elif data['mdxnetModel'] == 'bass':
model_set = 'bass'
model_set_name = 'bass'
modeltype = 'b'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Bass)'
source_val = 0
n_fft_scale_set=16384
dim_f_set=2048
else:
model_set = data['mdxnetModel']
model_set_name = data['mdxnetModel']
modeltype = stemset
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = stem_name
source_val = source_val_set
n_fft_scale_set=int(data['n_fft_scale'])
dim_f_set=int(data['dim_f'])
MDXModelName=('models/MDX_Net_Models/' + model_set + '.onnx')
mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
print(mdx_model_hash)
except:
if data['mdxnetModel'] == 'UVR-MDX-NET 1':
model_set = 'UVR_MDXNET_9703'
model_set_name = 'UVR_MDXNET_9703'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 2':
model_set = 'UVR_MDXNET_9682'
model_set_name = 'UVR_MDXNET_9682'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET 3':
model_set = 'UVR_MDXNET_9662'
model_set_name = 'UVR_MDXNET_9662'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'UVR-MDX-NET Karaoke':
model_set = 'UVR_MDXNET_KARA'
model_set_name = 'UVR_MDXNET_Karaoke'
modeltype = 'v'
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
stemset_n = '(Vocals)'
source_val = 3
n_fft_scale_set=6144
dim_f_set=2048
elif data['mdxnetModel'] == 'other':
model_set = 'other'
model_set_name = 'other'
modeltype = 'o'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Other)'
source_val = 2
n_fft_scale_set=8192
dim_f_set=2048
elif data['mdxnetModel'] == 'drums':
model_set = 'drums'
model_set_name = 'drums'
modeltype = 'd'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Drums)'
source_val = 1
n_fft_scale_set=4096
dim_f_set=2048
elif data['mdxnetModel'] == 'bass':
model_set = 'bass'
model_set_name = 'bass'
modeltype = 'b'
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = '(Bass)'
source_val = 0
n_fft_scale_set=16384
dim_f_set=2048
else:
model_set = data['mdxnetModel']
model_set_name = data['mdxnetModel']
modeltype = stemset
noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
stemset_n = stem_name
source_val = source_val_set
n_fft_scale_set=int(data['n_fft_scale'])
dim_f_set=int(data['dim_f'])
MDXModelName=('models/MDX_Net_Models/' + model_set_name + '.onnx')
mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
print(mdx_model_hash)
if data['noise_pro_select'] == 'Auto Select':
noise_pro_set = noise_pro
else:
noise_pro_set = data['noise_pro_select']
print(n_fft_scale_set)
print(dim_f_set)
print(data['DemucsModel'])
@@ -1135,7 +1240,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
with open('errorlog.txt', 'w') as f:
f.write(f'Last Error Received:\n\n' +
f'Error Received while processing "{os.path.basename(music_file)}":\n' +
f'Process Method: Ensemble Mode\n\n' +
f'Process Method: MDX-Net\n\n' +
f'The application was unable to allocate enough GPU memory to use this model.\n' +
f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n' +
f'If the error persists, your GPU might not be supported.\n\n' +
@@ -1159,7 +1264,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
with open('errorlog.txt', 'w') as f:
f.write(f'Last Error Received:\n\n' +
f'Error Received while processing "{os.path.basename(music_file)}":\n' +
f'Process Method: Ensemble Mode\n\n' +
f'Process Method: MDX-Net\n\n' +
f'The application was unable to allocate enough GPU memory to use this model.\n' +
f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n' +
f'If the error persists, your GPU might not be supported.\n\n' +
@@ -1184,7 +1289,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
with open('errorlog.txt', 'w') as f:
f.write(f'Last Error Received:\n\n' +
f'Error Received while processing "{os.path.basename(music_file)}":\n' +
f'Process Method: Ensemble Mode\n\n' +
f'Process Method: MDX-Net\n\n' +
f'Could not write audio file.\n' +
f'This could be due to low storage on target device or a system permissions issue.\n' +
f'If the error persists, please contact the developers.\n\n' +
@@ -1209,7 +1314,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
with open('errorlog.txt', 'w') as f:
f.write(f'Last Error Received:\n\n' +
f'Error Received while processing "{os.path.basename(music_file)}":\n' +
f'Process Method: Ensemble Mode\n\n' +
f'Process Method: MDX-Net\n\n' +
f'The application was unable to allocate enough system memory to use this model.\n' +
f'Please do the following:\n\n1. Restart this application.\n2. Ensure any CPU intensive applications are closed.\n3. Then try again.\n\n' +
f'Please Note: Intel Pentium and Intel Celeron processors do not work well with this application.\n\n' +
@@ -1222,6 +1327,28 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
button_widget.configure(state=tk.NORMAL) # Enable Button
return
if model_adv_set_err in message:
text_widget.write("\n" + base_text + f'Separation failed for the following audio file:\n')
text_widget.write(base_text + f'"{os.path.basename(music_file)}"\n')
text_widget.write(f'\nError Received:\n\n')
text_widget.write(f'The current ONNX model settings are not compatible with the selected \nmodel.\n\n')
text_widget.write(f'Please re-configure the advanced ONNX model settings accordingly and try \nagain.\n\n')
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
try:
with open('errorlog.txt', 'w') as f:
f.write(f'Last Error Received:\n\n' +
f'Error Received while processing "{os.path.basename(music_file)}":\n' +
f'Process Method: MDX-Net\n\n' +
f'The current ONNX model settings are not compatible with the selected model.\n\n' +
f'Please re-configure the advanced ONNX model settings accordingly and try again.\n\n' +
message + f'\nError Time Stamp [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
except:
pass
torch.cuda.empty_cache()
progress_var.set(0)
button_widget.configure(state=tk.NORMAL) # Enable Button
return
print(traceback_text)
print(type(e).__name__, e)