Cool_Tools/ultimatevocalremovergui
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Anjok07 2022-05-22 21:47:47 -05:00 committed by GitHub
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4 changed files with 2042 additions and 669 deletions
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941
UVR.py
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92
inference_MDX.py
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@ -9,6 +9,8 @@ import os.path
from datetime import datetime
import pydub
import shutil
import gc
#MDX-Net
#----------------------------------------
import soundfile as sf
@ -41,6 +43,16 @@ class Predictor():
def prediction_setup(self, demucs_name,
channels=64):
global device
print('Print the gpu setting: ', data['gpu'])
if data['gpu'] >= 0:
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
if data['gpu'] == -1:
device = torch.device('cpu')
if data['demucsmodel']:
self.demucs = Demucs(sources=["drums", "bass", "other", "vocals"], channels=channels)
widget_text.write(base_text + 'Loading Demucs model... ')
@ -66,8 +78,11 @@ class Predictor():
data['gpu'] = -1
widget_text.write("\n" + base_text + "No NVIDIA GPU detected. Switching to CPU... ")
run_type = ['CPUExecutionProvider']
else:
elif data['gpu'] == -1:
run_type = ['CPUExecutionProvider']
print(run_type)
print(str(device))
self.onnx_models[c] = ort.InferenceSession(os.path.join('models/MDX_Net_Models', model_set), providers=run_type)
widget_text.write('Done!\n')
@ -463,18 +478,15 @@ class Predictor():
gpu_mem = round(torch.cuda.get_device_properties(0).total_memory/1.074e+9)
except:
widget_text.write(base_text + 'NVIDIA GPU Required for conversion!\n')
if int(gpu_mem) <= int(5):
if int(gpu_mem) <= int(6):
chunk_set = int(5)
widget_text.write(base_text + 'Chunk size auto-set to 5... \n')
if gpu_mem in [6, 7]:
chunk_set = int(30)
widget_text.write(base_text + 'Chunk size auto-set to 30... \n')
if gpu_mem in [8, 9, 10, 11, 12, 13, 14, 15]:
if gpu_mem in [7, 8, 9, 10, 11, 12, 13, 14, 15]:
chunk_set = int(10)
widget_text.write(base_text + 'Chunk size auto-set to 10... \n')
if int(gpu_mem) >= int(16):
chunk_set = int(40)
widget_text.write(base_text + 'Chunk size auto-set to 40... \n')
if int(gpu_mem) >= int(16):
chunk_set = int(60)
widget_text.write(base_text + 'Chunk size auto-set to 60... \n')
if data['gpu'] == -1:
sys_mem = psutil.virtual_memory().total >> 30
if int(sys_mem) <= int(4):
@ -666,7 +678,6 @@ def get_baseText(total_files, file_num):
warnings.filterwarnings("ignore")
cpu = torch.device('cpu')
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
def hide_opt():
with open(os.devnull, "w") as devnull:
@ -710,6 +721,8 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
onnxmissing = "[ONNXRuntimeError] : 3 : NO_SUCHFILE"
onnxmemerror = "onnxruntime::CudaCall CUDA failure 2: out of memory"
onnxmemerror2 = "onnxruntime::BFCArena::AllocateRawInternal"
systemmemerr = "DefaultCPUAllocator: not enough memory"
runtimeerr = "CUDNN error executing cudnnSetTensorNdDescriptor"
cuda_err = "CUDA out of memory"
mod_err = "ModuleNotFoundError"
@ -965,16 +978,40 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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 application was unable to allocate enough GPU memory to use this model.\n')
text_widget.write(f'\nPlease do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n')
text_widget.write(f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n')
text_widget.write(f'If the error persists, your GPU might not be supported.\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'Process Method: Ensemble Mode\n\n' +
f'The application was unable to allocate enough GPU memory to use this model.\n' +
f'\nPlease do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\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' +
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
if onnxmemerror2 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 application was unable to allocate enough GPU memory to use this model.\n')
text_widget.write(f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n')
text_widget.write(f'If the error persists, your GPU might not be supported.\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: Ensemble Mode\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' +
message + f'\nError Time Stamp [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
except:
@ -1009,6 +1046,33 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
button_widget.configure(state=tk.NORMAL) # Enable Button
return
if systemmemerr 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 application was unable to allocate enough system memory to use this \nmodel.\n\n')
text_widget.write(f'Please do the following:\n\n1. Restart this application.\n2. Ensure any CPU intensive applications are closed.\n3. Then try again.\n\n')
text_widget.write(f'Please Note: Intel Pentium and Intel Celeron processors do not work well with \nthis application.\n\n')
text_widget.write(f'If the error persists, the system may not have enough RAM, or your CPU might \nnot be supported.\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: Ensemble Mode\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' +
f'If the error persists, the system may not have enough RAM, or your CPU might \nnot be supported.\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)
print(message)
@ -1041,7 +1105,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
text_widget.write(f'\nConversion(s) Completed!\n')
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}') # nopep8
torch.cuda.empty_cache()
torch.cuda.empty_cache()
button_widget.configure(state=tk.NORMAL) # Enable Button
if __name__ == '__main__':

48
inference_v5.py
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@ -101,6 +101,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
#Error Handling
runtimeerr = "CUDNN error executing cudnnSetTensorNdDescriptor"
systemmemerr = "DefaultCPUAllocator: not enough memory"
cuda_err = "CUDA out of memory"
mod_err = "ModuleNotFoundError"
file_err = "FileNotFoundError"
@ -453,6 +454,27 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
if model_hash == 'c3448ec923fa0edf3d03a19e633faa53':
model_params_d=str('lib_v5/modelparams/4band_44100.json')
param_name=str('4band_44100')
if model_hash == '68aa2c8093d0080704b200d140f59e54':
model_params_d=str('lib_v5/modelparams/3band_44100.json')
param_name=str('3band_44100.json')
if model_hash == 'fdc83be5b798e4bd29fe00fe6600e147':
model_params_d=str('lib_v5/modelparams/3band_44100_mid.json')
param_name=str('3band_44100_mid.json')
if model_hash == '2ce34bc92fd57f55db16b7a4def3d745':
model_params_d=str('lib_v5/modelparams/3band_44100_mid.json')
param_name=str('3band_44100_mid.json')
if model_hash == '52fdca89576f06cf4340b74a4730ee5f':
model_params_d=str('lib_v5/modelparams/4band_44100.json')
param_name=str('4band_44100.json')
if model_hash == '41191165b05d38fc77f072fa9e8e8a30':
model_params_d=str('lib_v5/modelparams/4band_44100.json')
param_name=str('4band_44100.json')
if model_hash == '89e83b511ad474592689e562d5b1f80e':
model_params_d=str('lib_v5/modelparams/2band_32000.json')
param_name=str('2band_32000.json')
if model_hash == '0b954da81d453b716b114d6d7c95177f':
model_params_d=str('lib_v5/modelparams/2band_32000.json')
param_name=str('2band_32000.json')
#v4 Models
@ -986,6 +1008,32 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
button_widget.configure(state=tk.NORMAL) # Enable Button
return
if systemmemerr 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 application was unable to allocate enough system memory to use this \nmodel.\n\n')
text_widget.write(f'Please do the following:\n\n1. Restart this application.\n2. Ensure any CPU intensive applications are closed.\n3. Then try again.\n\n')
text_widget.write(f'Please Note: Intel Pentium and Intel Celeron processors do not work well with \nthis application.\n\n')
text_widget.write(f'If the error persists, the system may not have enough RAM, or your CPU might \nnot be supported.\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: Ensemble Mode\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' +
f'If the error persists, the system may not have enough RAM, or your CPU might \nnot be supported.\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)
print(message)

1630
inference_v5_ensemble.py
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