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UVR.py
24
UVR.py
@ -114,6 +114,7 @@ DEFAULT_DATA = {
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'chunks': 'Auto',
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'n_fft_scale': 6144,
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'dim_f': 2048,
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'noise_pro_select': 'Auto Select',
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'overlap': 0.5,
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'shifts': 0,
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'margin': 44100,
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@ -408,6 +409,7 @@ class MainWindow(TkinterDnD.Tk):
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self.agg_var = tk.StringVar(value=data['agg'])
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self.n_fft_scale_var = tk.StringVar(value=data['n_fft_scale'])
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self.dim_f_var = tk.StringVar(value=data['dim_f'])
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self.noise_pro_select_var = tk.StringVar(value=data['noise_pro_select'])
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self.overlap_var = tk.StringVar(value=data['overlap'])
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self.shifts_var = tk.StringVar(value=data['shifts'])
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self.channel_var = tk.StringVar(value=data['channel'])
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@ -1083,6 +1085,7 @@ class MainWindow(TkinterDnD.Tk):
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'mixing': mixing,
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'n_fft_scale': self.n_fft_scale_var.get(),
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'dim_f': self.dim_f_var.get(),
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'noise_pro_select': self.noise_pro_select_var.get(),
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'overlap': self.overlap_var.get(),
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'shifts': self.shifts_var.get(),
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'margin': self.margin_var.get(),
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@ -1166,8 +1169,20 @@ class MainWindow(TkinterDnD.Tk):
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for char in e:
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file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 1")
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f = ["UVR_MDXNET_KARA"]
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f = ["UVR_MDXNET_9662"]
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for char in f:
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file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 3")
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g = ["UVR_MDXNET_9682"]
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for char in g:
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file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 2")
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h = ["UVR_MDXNET_9703"]
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for char in h:
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file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 1")
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i = ["UVR_MDXNET_KARA"]
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for char in i:
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file_name_1 = file_name_1.replace(char, "UVR-MDX-NET Karaoke")
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self.options_mdxnetModel_Optionmenu['menu'].add_radiobutton(label=file_name_1,
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@ -1838,6 +1853,12 @@ class MainWindow(TkinterDnD.Tk):
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l0=ttk.Entry(frame0, textvariable=self.compensate_var, justify='center')
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l0.grid(row=7,column=0,padx=0,pady=0)
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l0=tk.Label(frame0, text='Noise Profile', font=("Century Gothic", "9"), foreground='#13a4c9')
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l0.grid(row=8,column=0,padx=0,pady=10)
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l0=ttk.OptionMenu(frame0, self.noise_pro_select_var, None, 'Auto Select', 'MDX-NET_Noise_Profile_14_kHz', 'MDX-NET_Noise_Profile_17_kHz', 'MDX-NET_Noise_Profile_Full_Band')
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l0.grid(row=9,column=0,padx=0,pady=0)
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frame0=Frame(tab2, highlightbackground='red',highlightthicknes=0)
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frame0.grid(row=0,column=0,padx=0,pady=30)
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@ -2873,6 +2894,7 @@ class MainWindow(TkinterDnD.Tk):
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'chunks': chunks,
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'n_fft_scale': self.n_fft_scale_var.get(),
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'dim_f': self.dim_f_var.get(),
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'noise_pro_select': self.noise_pro_select_var.get(),
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'overlap': self.overlap_var.get(),
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'shifts': self.shifts_var.get(),
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'margin': self.margin_var.get(),
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137
inference_MDX.py
137
inference_MDX.py
@ -9,6 +9,7 @@ import os.path
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from datetime import datetime
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import pydub
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import shutil
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import hashlib
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import gc
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#MDX-Net
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@ -257,9 +258,10 @@ class Predictor():
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widget_text.write('Done!\n')
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widget_text.write(base_text + 'Performing Noise Reduction... ')
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reduction_sen = float(data['noisereduc_s'])/10
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print(noise_pro_set)
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subprocess.call("lib_v5\\sox\\sox.exe" + ' "' +
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f"{str(non_reduced_vocal_path)}" + '" "' + f"{str(vocal_path)}" + '" ' +
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"noisered lib_v5\\sox\\mdxnetnoisereduc.prof " + f"{reduction_sen}",
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"noisered lib_v5\\sox\\" + noise_pro_set + ".prof " + f"{reduction_sen}",
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shell=True, stdout=subprocess.PIPE,
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stdin=subprocess.PIPE, stderr=subprocess.PIPE)
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update_progress(**progress_kwargs,
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@ -688,6 +690,7 @@ data = {
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'inst_only': False,
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'n_fft_scale': 6144,
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'dim_f': 2048,
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'noise_pro_select': 'Auto Select',
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'overlap': 0.5,
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'shifts': 0,
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'margin': 44100,
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@ -747,6 +750,9 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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global model_set
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global model_set_name
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global stemset_n
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global noise_pro_set
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global mdx_model_hash
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global channel_set
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global margin_set
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@ -773,6 +779,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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file_err = "FileNotFoundError"
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ffmp_err = """audioread\__init__.py", line 116, in audio_open"""
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sf_write_err = "sf.write"
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model_adv_set_err = "Got invalid dimensions for input"
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try:
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with open('errorlog.txt', 'w') as f:
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@ -816,10 +823,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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source_val_set = 0
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stem_name = '(Bass)'
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try:
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if data['mdxnetModel'] == 'UVR-MDX-NET 1':
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model_set = 'UVR_MDXNET_1_9703'
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model_set_name = 'UVR_MDXNET_1_9703'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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@ -828,6 +838,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'UVR_MDXNET_2_9682'
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model_set_name = 'UVR_MDXNET_2_9682'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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@ -836,6 +847,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'UVR_MDXNET_3_9662'
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model_set_name = 'UVR_MDXNET_3_9662'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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@ -844,6 +856,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'UVR_MDXNET_KARA'
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model_set_name = 'UVR_MDXNET_Karaoke'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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@ -852,6 +865,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'other'
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model_set_name = 'other'
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modeltype = 'o'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Other)'
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source_val = 2
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n_fft_scale_set=8192
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@ -860,6 +874,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'drums'
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model_set_name = 'drums'
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modeltype = 'd'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Drums)'
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source_val = 1
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n_fft_scale_set=4096
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@ -868,6 +883,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = 'bass'
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model_set_name = 'bass'
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modeltype = 'b'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Bass)'
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source_val = 0
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n_fft_scale_set=16384
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@ -876,11 +892,100 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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model_set = data['mdxnetModel']
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model_set_name = data['mdxnetModel']
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modeltype = stemset
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = stem_name
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source_val = source_val_set
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n_fft_scale_set=int(data['n_fft_scale'])
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dim_f_set=int(data['dim_f'])
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MDXModelName=('models/MDX_Net_Models/' + model_set + '.onnx')
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mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
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print(mdx_model_hash)
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except:
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if data['mdxnetModel'] == 'UVR-MDX-NET 1':
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model_set = 'UVR_MDXNET_9703'
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model_set_name = 'UVR_MDXNET_9703'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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dim_f_set=2048
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elif data['mdxnetModel'] == 'UVR-MDX-NET 2':
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model_set = 'UVR_MDXNET_9682'
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model_set_name = 'UVR_MDXNET_9682'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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dim_f_set=2048
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elif data['mdxnetModel'] == 'UVR-MDX-NET 3':
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model_set = 'UVR_MDXNET_9662'
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model_set_name = 'UVR_MDXNET_9662'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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dim_f_set=2048
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elif data['mdxnetModel'] == 'UVR-MDX-NET Karaoke':
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model_set = 'UVR_MDXNET_KARA'
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model_set_name = 'UVR_MDXNET_Karaoke'
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modeltype = 'v'
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noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
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stemset_n = '(Vocals)'
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source_val = 3
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n_fft_scale_set=6144
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dim_f_set=2048
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elif data['mdxnetModel'] == 'other':
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model_set = 'other'
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model_set_name = 'other'
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modeltype = 'o'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Other)'
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source_val = 2
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n_fft_scale_set=8192
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dim_f_set=2048
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elif data['mdxnetModel'] == 'drums':
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model_set = 'drums'
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model_set_name = 'drums'
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modeltype = 'd'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Drums)'
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source_val = 1
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n_fft_scale_set=4096
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dim_f_set=2048
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elif data['mdxnetModel'] == 'bass':
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model_set = 'bass'
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model_set_name = 'bass'
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modeltype = 'b'
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = '(Bass)'
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source_val = 0
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n_fft_scale_set=16384
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dim_f_set=2048
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else:
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model_set = data['mdxnetModel']
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model_set_name = data['mdxnetModel']
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modeltype = stemset
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noise_pro = 'MDX-NET_Noise_Profile_Full_Band'
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stemset_n = stem_name
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source_val = source_val_set
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n_fft_scale_set=int(data['n_fft_scale'])
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dim_f_set=int(data['dim_f'])
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MDXModelName=('models/MDX_Net_Models/' + model_set_name + '.onnx')
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mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
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print(mdx_model_hash)
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if data['noise_pro_select'] == 'Auto Select':
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noise_pro_set = noise_pro
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else:
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noise_pro_set = data['noise_pro_select']
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print(n_fft_scale_set)
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print(dim_f_set)
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print(data['DemucsModel'])
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@ -1135,7 +1240,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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with open('errorlog.txt', 'w') as f:
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f.write(f'Last Error Received:\n\n' +
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f'Error Received while processing "{os.path.basename(music_file)}":\n' +
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f'Process Method: Ensemble Mode\n\n' +
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f'Process Method: MDX-Net\n\n' +
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f'The application was unable to allocate enough GPU memory to use this model.\n' +
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f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n' +
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f'If the error persists, your GPU might not be supported.\n\n' +
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@ -1159,7 +1264,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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with open('errorlog.txt', 'w') as f:
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f.write(f'Last Error Received:\n\n' +
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f'Error Received while processing "{os.path.basename(music_file)}":\n' +
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f'Process Method: Ensemble Mode\n\n' +
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f'Process Method: MDX-Net\n\n' +
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f'The application was unable to allocate enough GPU memory to use this model.\n' +
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f'Please do the following:\n\n1. Close any GPU intensive applications.\n2. Lower the set chunk size.\n3. Then try again.\n\n' +
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f'If the error persists, your GPU might not be supported.\n\n' +
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@ -1184,7 +1289,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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with open('errorlog.txt', 'w') as f:
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f.write(f'Last Error Received:\n\n' +
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f'Error Received while processing "{os.path.basename(music_file)}":\n' +
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f'Process Method: Ensemble Mode\n\n' +
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f'Process Method: MDX-Net\n\n' +
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f'Could not write audio file.\n' +
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f'This could be due to low storage on target device or a system permissions issue.\n' +
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f'If the error persists, please contact the developers.\n\n' +
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@ -1209,7 +1314,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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with open('errorlog.txt', 'w') as f:
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f.write(f'Last Error Received:\n\n' +
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f'Error Received while processing "{os.path.basename(music_file)}":\n' +
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f'Process Method: Ensemble Mode\n\n' +
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f'Process Method: MDX-Net\n\n' +
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f'The application was unable to allocate enough system memory to use this model.\n' +
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f'Please do the following:\n\n1. Restart this application.\n2. Ensure any CPU intensive applications are closed.\n3. Then try again.\n\n' +
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f'Please Note: Intel Pentium and Intel Celeron processors do not work well with this application.\n\n' +
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@ -1222,6 +1327,28 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
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button_widget.configure(state=tk.NORMAL) # Enable Button
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return
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if model_adv_set_err in message:
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text_widget.write("\n" + base_text + f'Separation failed for the following audio file:\n')
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text_widget.write(base_text + f'"{os.path.basename(music_file)}"\n')
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text_widget.write(f'\nError Received:\n\n')
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text_widget.write(f'The current ONNX model settings are not compatible with the selected \nmodel.\n\n')
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text_widget.write(f'Please re-configure the advanced ONNX model settings accordingly and try \nagain.\n\n')
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text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
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try:
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with open('errorlog.txt', 'w') as f:
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f.write(f'Last Error Received:\n\n' +
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f'Error Received while processing "{os.path.basename(music_file)}":\n' +
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f'Process Method: MDX-Net\n\n' +
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f'The current ONNX model settings are not compatible with the selected model.\n\n' +
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f'Please re-configure the advanced ONNX model settings accordingly and try again.\n\n' +
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message + f'\nError Time Stamp [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
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except:
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pass
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torch.cuda.empty_cache()
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progress_var.set(0)
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button_widget.configure(state=tk.NORMAL) # Enable Button
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return
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print(traceback_text)
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print(type(e).__name__, e)
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@ -167,9 +167,10 @@ class Predictor():
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widget_text.write('Done!\n')
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widget_text.write(base_text + 'Performing Noise Reduction... ')
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reduction_sen = float(int(data['noisereduc_s'])/10)
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print(noise_pro_set)
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subprocess.call("lib_v5\\sox\\sox.exe" + ' "' +
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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)
|
||||
widget_text.write('Done!\n')
|
||||
@ -188,7 +189,7 @@ class Predictor():
|
||||
reduction_sen = float(data['noisereduc_s'])/10
|
||||
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,
|
||||
@ -570,7 +571,7 @@ data = {
|
||||
'algo': 'Instrumentals (Min Spec)',
|
||||
#Advanced Options
|
||||
'appendensem': False,
|
||||
|
||||
'noise_pro_select': 'Auto Select',
|
||||
'overlap': 0.5,
|
||||
'shifts': 0,
|
||||
'margin': 44100,
|
||||
@ -624,12 +625,16 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global model_set
|
||||
global model_set_name
|
||||
global ModelName_2
|
||||
global mdx_model_hash
|
||||
|
||||
global channel_set
|
||||
global margin_set
|
||||
global overlap_set
|
||||
global shift_set
|
||||
|
||||
global noise_pro_set
|
||||
|
||||
|
||||
global n_fft_scale_set
|
||||
global dim_f_set
|
||||
|
||||
@ -1215,8 +1220,11 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
vr_ensem_mdx_c_name = data['vr_ensem_mdx_c']
|
||||
vr_ensem_mdx_c = f'models/Main_Models/{vr_ensem_mdx_c_name}.pth'
|
||||
|
||||
#MDX-Net Model
|
||||
|
||||
|
||||
|
||||
#MDX-Net Model
|
||||
try:
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET 1':
|
||||
mdx_ensem = 'UVR_MDXNET_1_9703'
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET 2':
|
||||
@ -1226,6 +1234,24 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET Karaoke':
|
||||
mdx_ensem = 'UVR_MDXNET_KARA'
|
||||
|
||||
MDXModelName=('models/MDX_Net_Models/' + mdx_ensem + '.onnx')
|
||||
mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
|
||||
print(mdx_ensem)
|
||||
except:
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET 1':
|
||||
mdx_ensem = 'UVR_MDXNET_9703'
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET 2':
|
||||
mdx_ensem = 'UVR_MDXNET_9682'
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET 3':
|
||||
mdx_ensem = 'UVR_MDXNET_9662'
|
||||
if data['mdx_ensem'] == 'UVR-MDX-NET Karaoke':
|
||||
mdx_ensem = 'UVR_MDXNET_KARA'
|
||||
|
||||
MDXModelName=('models/MDX_Net_Models/' + mdx_ensem + '.onnx')
|
||||
mdx_model_hash = hashlib.md5(open(MDXModelName, 'rb').read()).hexdigest()
|
||||
print(mdx_model_hash)
|
||||
print(mdx_ensem)
|
||||
|
||||
|
||||
#MDX-Net Model 2
|
||||
|
||||
@ -1236,12 +1262,10 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
if data['mdx_ensem_b'] == 'UVR-MDX-NET 3':
|
||||
mdx_ensem_b = 'UVR_MDXNET_3_9662'
|
||||
if data['mdx_ensem_b'] == 'UVR-MDX-NET Karaoke':
|
||||
mdx_ensem_b = 'UVR_MDXNET_Karaoke'
|
||||
mdx_ensem_b = 'UVR_MDXNET_KARA'
|
||||
if data['mdx_ensem_b'] == 'No Model':
|
||||
mdx_ensem_b = 'pass'
|
||||
|
||||
|
||||
|
||||
if data['vr_ensem'] == 'No Model' and data['vr_ensem_mdx_a'] == 'No Model' and data['vr_ensem_mdx_b'] == 'No Model' and data['vr_ensem_mdx_c'] == 'No Model':
|
||||
mdx_vr = [
|
||||
{
|
||||
@ -1949,22 +1973,51 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
text_widget.write('Ensemble Mode - Running Model - ' + mdx_name + '\n\n')
|
||||
|
||||
if mdx_name == 'UVR_MDXNET_1_9703':
|
||||
mdx_ensem_b = 'UVR_MDXNET_1_9703'
|
||||
model_set = 'UVR_MDXNET_1_9703.onnx'
|
||||
model_set_name = 'UVR_MDXNET_1_9703'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_2_9682':
|
||||
model_set = 'UVR_MDXNET_2_9682.onnx'
|
||||
model_set_name = 'UVR_MDXNET_2_9682'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_3_9662':
|
||||
model_set = 'UVR_MDXNET_3_9662.onnx'
|
||||
model_set_name = 'UVR_MDXNET_3_9662'
|
||||
modeltype = 'v'
|
||||
if mdx_name == 'UVR_MDXNET_Karaoke':
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_KARA':
|
||||
model_set = 'UVR_MDXNET_KARA.onnx'
|
||||
model_set_name = 'UVR_MDXNET_Karaoke'
|
||||
model_set_name = 'UVR_MDXNET_KARA'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_9703':
|
||||
model_set = 'UVR_MDXNET_9703.onnx'
|
||||
model_set_name = 'UVR_MDXNET_9703'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_9682':
|
||||
model_set = 'UVR_MDXNET_9682.onnx'
|
||||
model_set_name = 'UVR_MDXNET_9682'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_9662':
|
||||
model_set = 'UVR_MDXNET_9662.onnx'
|
||||
model_set_name = 'UVR_MDXNET_9662'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
if mdx_name == 'UVR_MDXNET_KARA':
|
||||
model_set = 'UVR_MDXNET_KARA.onnx'
|
||||
model_set_name = 'UVR_MDXNET_KARA'
|
||||
modeltype = 'v'
|
||||
noise_pro = 'MDX-NET_Noise_Profile_14_kHz'
|
||||
|
||||
|
||||
if data['noise_pro_select'] == 'Auto Select':
|
||||
noise_pro_set = noise_pro
|
||||
else:
|
||||
noise_pro_set = data['noise_pro_select']
|
||||
|
||||
update_progress(**progress_kwargs,
|
||||
step=0)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user