From 32a3df20440e4a3256ea9d7b34a143306e241452 Mon Sep 17 00:00:00 2001 From: Anjok07 <68268275+Anjok07@users.noreply.github.com> Date: Mon, 6 Jun 2022 15:44:20 -0500 Subject: [PATCH] Add files via upload --- UVR.py | 24 +++- inference_MDX.py | 265 +++++++++++++++++++++++++++++---------- inference_v5_ensemble.py | 91 +++++++++++--- 3 files changed, 291 insertions(+), 89 deletions(-) diff --git a/UVR.py b/UVR.py index eaa5382..c51f407 100644 --- a/UVR.py +++ b/UVR.py @@ -114,6 +114,7 @@ DEFAULT_DATA = { 'chunks': 'Auto', 'n_fft_scale': 6144, 'dim_f': 2048, + 'noise_pro_select': 'Auto Select', 'overlap': 0.5, 'shifts': 0, 'margin': 44100, @@ -408,6 +409,7 @@ class MainWindow(TkinterDnD.Tk): self.agg_var = tk.StringVar(value=data['agg']) self.n_fft_scale_var = tk.StringVar(value=data['n_fft_scale']) self.dim_f_var = tk.StringVar(value=data['dim_f']) + self.noise_pro_select_var = tk.StringVar(value=data['noise_pro_select']) self.overlap_var = tk.StringVar(value=data['overlap']) self.shifts_var = tk.StringVar(value=data['shifts']) self.channel_var = tk.StringVar(value=data['channel']) @@ -1083,6 +1085,7 @@ class MainWindow(TkinterDnD.Tk): 'mixing': mixing, 'n_fft_scale': self.n_fft_scale_var.get(), 'dim_f': self.dim_f_var.get(), + 'noise_pro_select': self.noise_pro_select_var.get(), 'overlap': self.overlap_var.get(), 'shifts': self.shifts_var.get(), 'margin': self.margin_var.get(), @@ -1166,8 +1169,20 @@ class MainWindow(TkinterDnD.Tk): for char in e: file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 1") - f = ["UVR_MDXNET_KARA"] + f = ["UVR_MDXNET_9662"] for char in f: + file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 3") + + g = ["UVR_MDXNET_9682"] + for char in g: + file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 2") + + h = ["UVR_MDXNET_9703"] + for char in h: + file_name_1 = file_name_1.replace(char, "UVR-MDX-NET 1") + + i = ["UVR_MDXNET_KARA"] + for char in i: file_name_1 = file_name_1.replace(char, "UVR-MDX-NET Karaoke") self.options_mdxnetModel_Optionmenu['menu'].add_radiobutton(label=file_name_1, @@ -1838,6 +1853,12 @@ class MainWindow(TkinterDnD.Tk): l0=ttk.Entry(frame0, textvariable=self.compensate_var, justify='center') l0.grid(row=7,column=0,padx=0,pady=0) + l0=tk.Label(frame0, text='Noise Profile', font=("Century Gothic", "9"), foreground='#13a4c9') + l0.grid(row=8,column=0,padx=0,pady=10) + + 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') + l0.grid(row=9,column=0,padx=0,pady=0) + frame0=Frame(tab2, highlightbackground='red',highlightthicknes=0) frame0.grid(row=0,column=0,padx=0,pady=30) @@ -2873,6 +2894,7 @@ class MainWindow(TkinterDnD.Tk): 'chunks': chunks, 'n_fft_scale': self.n_fft_scale_var.get(), 'dim_f': self.dim_f_var.get(), + 'noise_pro_select': self.noise_pro_select_var.get(), 'overlap': self.overlap_var.get(), 'shifts': self.shifts_var.get(), 'margin': self.margin_var.get(), diff --git a/inference_MDX.py b/inference_MDX.py index 42a4fca..ecf188b 100644 --- a/inference_MDX.py +++ b/inference_MDX.py @@ -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) diff --git a/inference_v5_ensemble.py b/inference_v5_ensemble.py index 377bf88..529d9f2 100644 --- a/inference_v5_ensemble.py +++ b/inference_v5_ensemble.py @@ -167,9 +167,10 @@ class Predictor(): widget_text.write('Done!\n') widget_text.write(base_text + 'Performing Noise Reduction... ') reduction_sen = float(int(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) 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 @@ -1215,18 +1220,39 @@ 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 - - if data['mdx_ensem'] == 'UVR-MDX-NET 1': - mdx_ensem = 'UVR_MDXNET_1_9703' - if data['mdx_ensem'] == 'UVR-MDX-NET 2': - mdx_ensem = 'UVR_MDXNET_2_9682' - if data['mdx_ensem'] == 'UVR-MDX-NET 3': - mdx_ensem = 'UVR_MDXNET_3_9662' - if data['mdx_ensem'] == 'UVR-MDX-NET Karaoke': - mdx_ensem = 'UVR_MDXNET_KARA' - + try: + if data['mdx_ensem'] == 'UVR-MDX-NET 1': + mdx_ensem = 'UVR_MDXNET_1_9703' + if data['mdx_ensem'] == 'UVR-MDX-NET 2': + mdx_ensem = 'UVR_MDXNET_2_9682' + if data['mdx_ensem'] == 'UVR-MDX-NET 3': + mdx_ensem = 'UVR_MDXNET_3_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_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 if data['mdx_ensem_b'] == 'UVR-MDX-NET 1': @@ -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)