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UVR.py
78
UVR.py
@ -21,6 +21,7 @@ from PIL import Image
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from PIL import ImageTk
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import pickle # Save Data
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from pathlib import Path
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# Other Modules
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# Pathfinding
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@ -39,7 +40,6 @@ import inference_MDX
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import inference_v5
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import inference_v5_ensemble
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import inference_demucs
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# Version
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from __version__ import VERSION
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from win32api import GetSystemMetrics
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@ -112,6 +112,7 @@ DEFAULT_DATA = {
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'appendensem': False,
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'demucs_only': False,
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'split_mode': True,
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'normalize': False,
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#MDX-Net
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'demucsmodel': False,
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'demucsmodelVR': False,
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@ -130,6 +131,9 @@ DEFAULT_DATA = {
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'segment': 'None',
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'dim_f': 2048,
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'noise_pro_select': 'Auto Select',
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'wavtype': 'PCM_16',
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'flactype': 'PCM_16',
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'mp3bit': '320k',
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'overlap': 0.25,
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'shifts': 2,
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'overlap_b': 0.25,
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@ -144,6 +148,7 @@ DEFAULT_DATA = {
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'DemucsModel': 'mdx_extra',
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'DemucsModel_MDX': 'UVR_Demucs_Model_1',
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'ModelParams': 'Auto',
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'settest': False,
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}
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def open_image(path: str, size: tuple = None, keep_aspect: bool = True, rotate: int = 0) -> ImageTk.PhotoImage:
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@ -416,6 +421,7 @@ class MainWindow(TkinterDnD.Tk):
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self.appendensem_var = tk.BooleanVar(value=data['appendensem'])
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self.demucs_only_var = tk.BooleanVar(value=data['demucs_only'])
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self.split_mode_var = tk.BooleanVar(value=data['split_mode'])
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self.normalize_var = tk.BooleanVar(value=data['normalize'])
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# Processing Options
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self.gpuConversion_var = tk.BooleanVar(value=data['gpu'])
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self.postprocessing_var = tk.BooleanVar(value=data['postprocess'])
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@ -443,6 +449,9 @@ class MainWindow(TkinterDnD.Tk):
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self.segment_var = tk.StringVar(value=data['segment'])
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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.wavtype_var = tk.StringVar(value=data['wavtype'])
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self.flactype_var = tk.StringVar(value=data['flactype'])
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self.mp3bit_var = tk.StringVar(value=data['mp3bit'])
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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.overlap_b_var = tk.StringVar(value=data['overlap_b'])
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@ -459,6 +468,7 @@ class MainWindow(TkinterDnD.Tk):
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self.inst_only_b_var = tk.BooleanVar(value=data['inst_only_b'])
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self.audfile_var = tk.BooleanVar(value=data['audfile'])
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self.autocompensate_var = tk.BooleanVar(value=data['autocompensate'])
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self.settest_var = tk.BooleanVar(value=data['settest'])
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# Choose Conversion Method
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self.aiModel_var = tk.StringVar(value=data['aiModel'])
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self.last_aiModel = self.aiModel_var.get()
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@ -530,8 +540,10 @@ class MainWindow(TkinterDnD.Tk):
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self.command_Text = ThreadSafeConsole(master=self,
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background='#0e0e0f',fg='#898b8e', font=('Century Gothic', 11),borderwidth=0)
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#self.command_Text.write(f'Ultimate Vocal Remover [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
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self.command_Text.write(f'Ultimate Vocal Remover v{VERSION} [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
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def configure_widgets(self):
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"""Change widget styling and appearance"""
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@ -1223,6 +1235,7 @@ class MainWindow(TkinterDnD.Tk):
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'appendensem': self.appendensem_var.get(),
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'demucs_only': self.demucs_only_var.get(),
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'split_mode': self.split_mode_var.get(),
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'normalize': self.normalize_var.get(),
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'tta': self.tta_var.get(),
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'save': self.save_var.get(),
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'output_image': self.outputImage_var.get(),
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@ -1261,6 +1274,7 @@ class MainWindow(TkinterDnD.Tk):
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'inst_only_b': self.inst_only_b_var.get(),
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'audfile': self.audfile_var.get(),
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'autocompensate': self.autocompensate_var.get(),
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'settest': self.settest_var.get(),
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'chunks': chunks,
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'chunks_d': self.chunks_d_var.get(),
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'noisereduc_s': noisereduc_s,
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@ -1269,6 +1283,9 @@ class MainWindow(TkinterDnD.Tk):
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'segment': self.segment_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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'wavtype': self.wavtype_var.get(),
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'flactype': self.flactype_var.get(),
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'mp3bit': self.mp3bit_var.get(),
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'overlap': self.overlap_var.get(),
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'shifts': self.shifts_var.get(),
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'overlap_b': self.overlap_b_var.get(),
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@ -2009,14 +2026,13 @@ class MainWindow(TkinterDnD.Tk):
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if self.autocompensate_var.get() == True:
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self.compensate_var.set('Auto')
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try:
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self.options_compensate.configure(state=tk.DISABLED)
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except:
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pass
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if self.autocompensate_var.get() == False:
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self.compensate_var.set(1.03597672895)
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#self.compensate_var.set()
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try:
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self.options_compensate.configure(state=tk.NORMAL)
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except:
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@ -2365,25 +2381,19 @@ class MainWindow(TkinterDnD.Tk):
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l0.grid(row=10,column=0,padx=0,pady=0)
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l0=ttk.Checkbutton(frame0, text='Save Stems to Model & Track Name Directory', variable=self.audfile_var)
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l0.grid(row=11,column=0,padx=0,pady=0)
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l0=ttk.Checkbutton(frame0, text='Settings Test Mode', variable=self.modelFolder_var)
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l0.grid(row=12,column=0,padx=0,pady=0)
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# l0=ttk.Checkbutton(frame0, text='Basic Prediction', variable=self.audfile_var)
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# l0.grid(row=10,column=0,padx=0,pady=0)
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l0.grid(row=11,column=0,padx=0,pady=5)
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l0=ttk.Button(frame0,text='Open Demucs Model Folder', command=self.open_Modelfolder_de)
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l0.grid(row=13,column=0,padx=0,pady=0)
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l0.grid(row=12,column=0,padx=0,pady=0)
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l0=ttk.Button(frame0,text='Back to Main Menu', command=close_win)
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l0.grid(row=14,column=0,padx=0,pady=10)
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l0.grid(row=13,column=0,padx=0,pady=10)
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def close_win_self():
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top.destroy()
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l0=ttk.Button(frame0,text='Close Window', command=close_win_self)
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l0.grid(row=15,column=0,padx=0,pady=0)
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l0.grid(row=14,column=0,padx=0,pady=0)
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def advanced_mdx_options(self):
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@ -2467,13 +2477,13 @@ class MainWindow(TkinterDnD.Tk):
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l0.grid(row=8,column=0,padx=0,pady=0)
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l0=ttk.Checkbutton(frame0, text='Autoset Volume Compensation', variable=self.autocompensate_var)
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l0.grid(row=9,column=0,padx=0,pady=10)
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l0.grid(row=9,column=0,padx=0,pady=5)
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l0=ttk.Checkbutton(frame0, text='Reduce Instrumental Noise Separately', variable=self.nophaseinst_var)
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l0.grid(row=10,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=11,column=0,padx=0,pady=10)
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l0.grid(row=11,column=0,padx=0,pady=5)
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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=12,column=0,padx=0,pady=0)
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@ -3242,14 +3252,19 @@ class MainWindow(TkinterDnD.Tk):
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tabControl = ttk.Notebook(top)
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tab1 = ttk.Frame(tabControl)
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tab2 = ttk.Frame(tabControl)
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tabControl.add(tab1, text ='Settings Guide')
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tabControl.add(tab2, text ='Audio Format Settings')
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tabControl.pack(expand = 1, fill ="both")
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tab1.grid_rowconfigure(0, weight=1)
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tab1.grid_columnconfigure(0, weight=1)
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tab2.grid_rowconfigure(0, weight=1)
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tab2.grid_columnconfigure(0, weight=1)
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frame0=Frame(tab1,highlightbackground='red',highlightthicknes=0)
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frame0.grid(row=0,column=0,padx=0,pady=0)
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@ -3277,11 +3292,35 @@ class MainWindow(TkinterDnD.Tk):
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l0=Label(frame0,text="Additional Options",font=("Century Gothic", "13", "bold", "underline"), justify="center", fg="#13a4c9")
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l0.grid(row=7,column=0,padx=0,pady=10)
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l0=ttk.Checkbutton(frame0, text='Settings Test Mode', variable=self.settest_var)
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l0.grid(row=8,column=0,padx=0,pady=0)
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l0=ttk.Button(frame0,text='Open Application Directory', command=self.open_appdir_filedialog)
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l0.grid(row=8,column=0,padx=20,pady=5)
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l0.grid(row=9,column=0,padx=20,pady=5)
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l0=ttk.Button(frame0,text='Close Window', command=close_win)
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l0.grid(row=9,column=0,padx=20,pady=5)
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l0.grid(row=10,column=0,padx=20,pady=5)
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frame0=Frame(tab2,highlightbackground='red',highlightthicknes=0)
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frame0.grid(row=0,column=0,padx=0,pady=0)
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l0=Label(frame0,text="Audio Format Settings",font=("Century Gothic", "13", "bold", "underline"), justify="center", fg="#13a4c9")
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l0.grid(row=0,column=0,padx=0,pady=10)
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l0=tk.Label(frame0, text='Wav Type', font=("Century Gothic", "9"), foreground='#13a4c9')
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l0.grid(row=1,column=0,padx=0,pady=10)
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l0=ttk.OptionMenu(frame0, self.wavtype_var, None, 'PCM_U8', 'PCM_16', 'PCM_24', 'PCM_32', '32-bit Float', '64-bit Float')
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l0.grid(row=2,column=0,padx=20,pady=0)
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l0=tk.Label(frame0, text='Mp3 Bitrate', font=("Century Gothic", "9"), foreground='#13a4c9')
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l0.grid(row=5,column=0,padx=0,pady=10)
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l0=ttk.OptionMenu(frame0, self.mp3bit_var, None, '96k', '128k', '160k', '224k', '256k', '320k')
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l0.grid(row=6,column=0,padx=20,pady=0)
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l0=ttk.Checkbutton(frame0, text='Normalize Outputs\n(Prevents clipping)', variable=self.normalize_var)
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l0.grid(row=7,column=0,padx=0,pady=10)
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def error_log(self):
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@ -3443,6 +3482,7 @@ class MainWindow(TkinterDnD.Tk):
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'appendensem': self.appendensem_var.get(),
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'demucs_only': self.demucs_only_var.get(),
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'split_mode': self.split_mode_var.get(),
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'normalize': self.normalize_var.get(),
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'postprocess': self.postprocessing_var.get(),
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'tta': self.tta_var.get(),
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'save': self.save_var.get(),
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@ -3473,12 +3513,16 @@ class MainWindow(TkinterDnD.Tk):
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'inst_only_b': self.inst_only_b_var.get(),
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'audfile': self.audfile_var.get(),
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'autocompensate': self.autocompensate_var.get(),
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'settest': self.settest_var.get(),
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'chunks': chunks,
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'chunks_d': self.chunks_d_var.get(),
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'n_fft_scale': self.n_fft_scale_var.get(),
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'segment': self.segment_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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'wavtype': self.wavtype_var.get(),
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'flactype': self.flactype_var.get(),
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'mp3bit': self.mp3bit_var.get(),
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'overlap': self.overlap_var.get(),
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'shifts': self.shifts_var.get(),
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'overlap_b': self.overlap_b_var.get(),
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@ -38,6 +38,7 @@ import torch
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import tkinter as tk
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import traceback # Error Message Recent Calls
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import time # Timer
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from random import randrange
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from typing import Literal
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@ -213,7 +214,7 @@ class Predictor():
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non_reduced_Instrumental_path = '{save_path}/{file_name}.wav'.format(
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save_path=save_path,
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file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',)
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non_reduced_path_mp3 = '{save_path}/{file_name}.mp3'.format(
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non_reduced_Instrumental_path_mp3 = '{save_path}/{file_name}.mp3'.format(
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save_path=save_path,
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file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',)
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non_reduced_Instrumental_path_flac = '{save_path}/{file_name}.flac'.format(
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@ -257,7 +258,7 @@ class Predictor():
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else:
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widget_text.write(base_text + 'Saving vocals... ')
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sf.write(non_reduced_vocal_path, sources[c].T, samplerate)
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sf.write(non_reduced_vocal_path, sources[c].T, samplerate, subtype=wav_type_set)
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update_progress(**progress_kwargs,
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step=(0.9))
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widget_text.write('Done!\n')
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@ -279,9 +280,9 @@ class Predictor():
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if data['demucs_only']:
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if 'UVR' in demucs_model_set:
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sf.write(non_reduced_vocal_path, sources[1].T, samplerate)
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sf.write(non_reduced_vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
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else:
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sf.write(non_reduced_vocal_path, sources[source_val].T, samplerate)
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sf.write(non_reduced_vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
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update_progress(**progress_kwargs,
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step=(0.9))
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widget_text.write('Done!\n')
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@ -304,7 +305,7 @@ class Predictor():
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widget_text.write(base_text + 'Preparing Instrumental...')
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else:
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widget_text.write(base_text + 'Saving Vocals... ')
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sf.write(vocal_path, sources[c].T, samplerate)
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sf.write(vocal_path, sources[c].T, samplerate, subtype=wav_type_set)
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update_progress(**progress_kwargs,
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step=(0.9))
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widget_text.write('Done!\n')
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@ -316,11 +317,11 @@ class Predictor():
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if data['demucs_only']:
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if 'UVR' in demucs_model_set:
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sf.write(vocal_path, sources[1].T, samplerate)
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sf.write(vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
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else:
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sf.write(vocal_path, sources[source_val].T, samplerate)
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sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
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else:
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sf.write(vocal_path, sources[source_val].T, samplerate)
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sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
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update_progress(**progress_kwargs,
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step=(0.9))
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@ -387,12 +388,13 @@ class Predictor():
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y_mag = np.abs(specs[1])
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max_mag = np.where(X_mag >= y_mag, X_mag, y_mag)
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v_spec = specs[1] - max_mag * np.exp(1.j * np.angle(specs[0]))
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update_progress(**progress_kwargs,
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step=(1))
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if not data['noisereduc_s'] == 'None':
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if data['nophaseinst']:
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sf.write(non_reduced_Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
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sf.write(non_reduced_Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
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reduction_sen = float(data['noisereduc_s'])/10
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print(noise_pro_set)
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@ -403,9 +405,9 @@ class Predictor():
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shell=True, stdout=subprocess.PIPE,
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stdin=subprocess.PIPE, stderr=subprocess.PIPE)
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else:
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sf.write(Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
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sf.write(Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
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else:
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sf.write(Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
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sf.write(Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
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if data['inst_only']:
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if file_exists_v == 'there':
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@ -427,7 +429,7 @@ class Predictor():
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pass
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||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(non_reduced_Instrumental_path)
|
||||
musfile.export(non_reduced_Instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(non_reduced_Instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
try:
|
||||
os.remove(non_reduced_Instrumental_path)
|
||||
except:
|
||||
@ -435,7 +437,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(vocal_path)
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_v == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -451,7 +453,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(non_reduced_Instrumental_path)
|
||||
musfile.export(non_reduced_Instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(non_reduced_Instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_n == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -462,7 +464,7 @@ class Predictor():
|
||||
if data['voc_only'] == True:
|
||||
if data['non_red'] == True:
|
||||
musfile = pydub.AudioSegment.from_wav(non_reduced_vocal_path)
|
||||
musfile.export(non_reduced_vocal_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(non_reduced_vocal_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
try:
|
||||
os.remove(non_reduced_vocal_path)
|
||||
except:
|
||||
@ -470,7 +472,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(Instrumental_path)
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_i == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -483,7 +485,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(non_reduced_vocal_path)
|
||||
musfile.export(non_reduced_vocal_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(non_reduced_vocal_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_n == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -713,7 +715,6 @@ class Predictor():
|
||||
|
||||
if not data['demucsmodel']:
|
||||
sources = self.demix_base(segmented_mix, margin_size=margin)
|
||||
#value=float(0.9)*float(compensate)
|
||||
elif data['demucs_only']:
|
||||
if split_mode == True:
|
||||
sources = self.demix_demucs_split(mix)
|
||||
@ -742,7 +743,11 @@ class Predictor():
|
||||
sources[source_val] = (spec_effects(wave=[demucs_out[source_val],base_out[0]],
|
||||
algorithm=data['mixing'],
|
||||
value=b[source_val])*float(compensate)) # compensation
|
||||
return sources
|
||||
|
||||
if not data['demucsmodel']:
|
||||
return sources*float(compensate)
|
||||
else:
|
||||
return sources
|
||||
|
||||
def demix_base(self, mixes, margin_size):
|
||||
chunked_sources = []
|
||||
@ -882,10 +887,14 @@ data = {
|
||||
'shifts': 0,
|
||||
'margin': 44100,
|
||||
'split_mode': False,
|
||||
'normalize': False,
|
||||
'nophaseinst': True,
|
||||
'compensate': 1.03597672895,
|
||||
'autocompensate': True,
|
||||
'demucs_only': False,
|
||||
'wavtype': 'PCM_16',
|
||||
'flactype': 'PCM_16',
|
||||
'mp3bit': '320k',
|
||||
'mixing': 'Default',
|
||||
'DemucsModel_MDX': 'UVR_Demucs_Model_1',
|
||||
# Choose Model
|
||||
@ -941,10 +950,8 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global stemset_n
|
||||
global noise_pro_set
|
||||
global demucs_model_set
|
||||
|
||||
global autocompensate
|
||||
global compensate
|
||||
|
||||
global channel_set
|
||||
global margin_set
|
||||
global overlap_set
|
||||
@ -952,10 +959,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global source_val
|
||||
global split_mode
|
||||
global demucs_model_set
|
||||
global wav_type_set
|
||||
global flac_type_set
|
||||
global mp3_bit_set
|
||||
global normalization_set
|
||||
|
||||
global demucs_switch
|
||||
|
||||
autocompensate = data['autocompensate']
|
||||
|
||||
# Update default settings
|
||||
default_chunks = data['chunks']
|
||||
@ -987,6 +997,8 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
data.update(kwargs)
|
||||
|
||||
autocompensate = data['autocompensate']
|
||||
|
||||
if data['mdxnetModeltype'] == 'Vocals (Custom)':
|
||||
stemset = 'v'
|
||||
source_val_set = 3
|
||||
@ -1156,7 +1168,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
else:
|
||||
noise_pro_set = data['noise_pro_select']
|
||||
|
||||
if data['wavtype'] == '32-bit Float':
|
||||
wav_type_set = 'FLOAT'
|
||||
elif data['wavtype'] == '64-bit Float':
|
||||
wav_type_set = 'DOUBLE'
|
||||
else:
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
flac_type_set = data['flactype']
|
||||
mp3_bit_set = data['mp3bit']
|
||||
|
||||
if data['normalize'] == True:
|
||||
normalization_set = spec_utils.normalize
|
||||
print('normalization on')
|
||||
else:
|
||||
normalization_set = spec_utils.nonormalize
|
||||
print('normalization off')
|
||||
|
||||
print(n_fft_scale_set)
|
||||
print(dim_f_set)
|
||||
@ -1179,6 +1206,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
split_mode = data['split_mode']
|
||||
demucs_switch = data['demucsmodel']
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Flac':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if stemset_n == '(Bass)':
|
||||
if 'UVR' in demucs_model_set:
|
||||
text_widget.write('The selected Demucs model can only be used with vocal stems.\n')
|
||||
@ -1211,8 +1254,17 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
pass
|
||||
|
||||
_mixture = f'{data["input_paths"]}'
|
||||
_basename = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
timestampnum = round(datetime.utcnow().timestamp())
|
||||
randomnum = randrange(100000, 1000000)
|
||||
|
||||
if data['settest']:
|
||||
try:
|
||||
_basename = f'{data["export_path"]}/{str(timestampnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
except:
|
||||
_basename = f'{data["export_path"]}/{str(randomnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
else:
|
||||
_basename = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
# -Get text and update progress-
|
||||
base_text = get_baseText(total_files=len(data['input_paths']),
|
||||
file_num=file_num)
|
||||
|
||||
@ -245,22 +245,22 @@ class Predictor():
|
||||
pass
|
||||
|
||||
if 'UVR' in model_set_name:
|
||||
sf.write(Instrumental_path, sources[0].T, samplerate)
|
||||
sf.write(vocals_path, sources[1].T, samplerate)
|
||||
sf.write(Instrumental_path, normalization_set(sources[0]).T, samplerate, subtype=wav_type_set)
|
||||
sf.write(vocals_path, normalization_set(sources[1]).T, samplerate, subtype=wav_type_set)
|
||||
else:
|
||||
sf.write(bass_path, sources[0].T, samplerate)
|
||||
sf.write(drums_path, sources[1].T, samplerate)
|
||||
sf.write(other_path, sources[2].T, samplerate)
|
||||
sf.write(vocals_path, sources[3].T, samplerate)
|
||||
sf.write(bass_path, normalization_set(sources[0]).T, samplerate, subtype=wav_type_set)
|
||||
sf.write(drums_path, normalization_set(sources[1]).T, samplerate, subtype=wav_type_set)
|
||||
sf.write(other_path, normalization_set(sources[2]).T, samplerate, subtype=wav_type_set)
|
||||
sf.write(vocals_path, normalization_set(sources[3]).T, samplerate, subtype=wav_type_set)
|
||||
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
try:
|
||||
if 'UVR' in model_set_name:
|
||||
widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ')
|
||||
musfile = pydub.AudioSegment.from_wav(vocals_path)
|
||||
musfile.export(vocals_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(vocals_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
musfile = pydub.AudioSegment.from_wav(Instrumental_path)
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
try:
|
||||
os.remove(Instrumental_path)
|
||||
os.remove(vocals_path)
|
||||
@ -269,13 +269,13 @@ class Predictor():
|
||||
else:
|
||||
widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ')
|
||||
musfile = pydub.AudioSegment.from_wav(drums_path)
|
||||
musfile.export(drums_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(drums_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
musfile = pydub.AudioSegment.from_wav(bass_path)
|
||||
musfile.export(bass_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(bass_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
musfile = pydub.AudioSegment.from_wav(other_path)
|
||||
musfile.export(other_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(other_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
musfile = pydub.AudioSegment.from_wav(vocals_path)
|
||||
musfile.export(vocals_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(vocals_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
try:
|
||||
os.remove(drums_path)
|
||||
os.remove(bass_path)
|
||||
@ -364,11 +364,11 @@ class Predictor():
|
||||
else:
|
||||
if 'UVR' in model_set_name:
|
||||
if stemset_n == '(Vocals)':
|
||||
sf.write(vocal_path, sources[1].T, samplerate)
|
||||
sf.write(vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
|
||||
else:
|
||||
sf.write(vocal_path, sources[source_val].T, samplerate)
|
||||
sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
|
||||
else:
|
||||
sf.write(vocal_path, sources[source_val].T, samplerate)
|
||||
sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
|
||||
|
||||
widget_text.write('Done!\n')
|
||||
|
||||
@ -426,7 +426,7 @@ class Predictor():
|
||||
update_progress(**progress_kwargs,
|
||||
step=(1))
|
||||
|
||||
sf.write(Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
|
||||
sf.write(Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
|
||||
if data['inst_only_b']:
|
||||
@ -449,7 +449,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(vocal_path)
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_v == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -461,7 +461,7 @@ class Predictor():
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(Instrumental_path)
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(Instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_i == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -693,7 +693,7 @@ data = {
|
||||
'demucsmodel': True,
|
||||
'gpu': -1,
|
||||
'chunks_d': 'Full',
|
||||
'modelFolder': False,
|
||||
'settest': False,
|
||||
'voc_only_b': False,
|
||||
'inst_only_b': False,
|
||||
'overlap_b': 0.25,
|
||||
@ -701,10 +701,13 @@ data = {
|
||||
'segment': 'None',
|
||||
'margin': 44100,
|
||||
'split_mode': False,
|
||||
'normalize': False,
|
||||
'compensate': 1.03597672895,
|
||||
'demucs_stems': 'All Stems',
|
||||
'DemucsModel': 'mdx_extra',
|
||||
'audfile': True,
|
||||
'wavtype': 'PCM_16',
|
||||
'mp3bit': '320k',
|
||||
}
|
||||
default_chunks = data['chunks_d']
|
||||
|
||||
@ -754,6 +757,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global source_val
|
||||
global split_mode
|
||||
|
||||
global wav_type_set
|
||||
global flac_type_set
|
||||
global mp3_bit_set
|
||||
global normalization_set
|
||||
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
# Update default settings
|
||||
default_chunks = data['chunks_d']
|
||||
|
||||
@ -786,6 +796,23 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
data.update(kwargs)
|
||||
|
||||
if data['wavtype'] == '32-bit Float':
|
||||
wav_type_set = 'FLOAT'
|
||||
elif data['wavtype'] == '64-bit Float':
|
||||
wav_type_set = 'DOUBLE'
|
||||
else:
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
flac_type_set = data['flactype']
|
||||
mp3_bit_set = data['mp3bit']
|
||||
|
||||
if data['normalize'] == True:
|
||||
normalization_set = spec_utils.normalize
|
||||
print('normalization on')
|
||||
else:
|
||||
normalization_set = spec_utils.nonormalize
|
||||
print('normalization off')
|
||||
|
||||
stime = time.perf_counter()
|
||||
progress_var.set(0)
|
||||
text_widget.clear()
|
||||
@ -794,6 +821,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
try: #Load File(s)
|
||||
for file_num, music_file in tqdm(enumerate(data['input_paths'], start=1)):
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Flac':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
model_set_name = data['DemucsModel']
|
||||
|
||||
if data['demucs_stems'] == 'Vocals':
|
||||
@ -889,20 +932,20 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
os.mkdir(folder_path)
|
||||
|
||||
_mixture = f'{data["input_paths"]}'
|
||||
if data['modelFolder']:
|
||||
if data['settest']:
|
||||
try:
|
||||
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{file_num}_{str(timestampnum)}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{str(timestampnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
except:
|
||||
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{file_num}_{str(randomnum)}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{str(randomnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
else:
|
||||
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
else:
|
||||
_mixture = f'{data["input_paths"]}'
|
||||
if data['modelFolder']:
|
||||
if data['settest']:
|
||||
try:
|
||||
_basename = f'{data["export_path"]}/{file_num}_{str(timestampnum)}_{model_set_name}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
_basename = f'{data["export_path"]}/{str(timestampnum)}_{file_num}_{model_set_name}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
except:
|
||||
_basename = f'{data["export_path"]}/{file_num}_{str(randomnum)}_{model_set_name}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
_basename = f'{data["export_path"]}/{str(randomnum)}{file_num}_{model_set_name}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
else:
|
||||
_basename = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
|
||||
@ -28,6 +28,7 @@ from collections import defaultdict
|
||||
import tkinter as tk
|
||||
import traceback # Error Message Recent Calls
|
||||
import time # Timer
|
||||
from random import randrange
|
||||
|
||||
class VocalRemover(object):
|
||||
|
||||
@ -63,7 +64,11 @@ data = {
|
||||
'shifts': 0,
|
||||
'segment': 'None',
|
||||
'split_mode': False,
|
||||
'normalize': False,
|
||||
'demucsmodelVR': True,
|
||||
'wavtype': 'PCM_16',
|
||||
'mp3bit': '320k',
|
||||
'settest': False,
|
||||
}
|
||||
|
||||
default_window_size = data['window_size']
|
||||
@ -113,6 +118,12 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global shift_set
|
||||
global split_mode
|
||||
global demucs_model_set
|
||||
global wav_type_set
|
||||
|
||||
global flac_type_set
|
||||
global mp3_bit_set
|
||||
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
#Error Handling
|
||||
|
||||
@ -158,13 +169,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
# and for vocal the instrumental is the temp file due
|
||||
# to reversement
|
||||
if data['demucsmodelVR']:
|
||||
sameplerate = 44100
|
||||
samplerate = 44100
|
||||
else:
|
||||
sameplerate = mp.param['sr']
|
||||
samplerate = mp.param['sr']
|
||||
|
||||
|
||||
sf.write(f'temp.wav',
|
||||
wav_instrument.T, sameplerate)
|
||||
normalization_set(wav_instrument).T, samplerate, subtype=wav_type_set)
|
||||
|
||||
appendModelFolderName = modelFolderName.replace('/', '_')
|
||||
|
||||
@ -199,14 +210,14 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
if VModel in model_name and data['voc_only']:
|
||||
sf.write(instrumental_path,
|
||||
wav_instrument.T, sameplerate)
|
||||
normalization_set(wav_instrument).T, samplerate, subtype=wav_type_set)
|
||||
elif VModel in model_name and data['inst_only']:
|
||||
pass
|
||||
elif data['voc_only']:
|
||||
pass
|
||||
else:
|
||||
sf.write(instrumental_path,
|
||||
wav_instrument.T, sameplerate)
|
||||
normalization_set(wav_instrument).T, samplerate, subtype=wav_type_set)
|
||||
|
||||
# Vocal
|
||||
if vocal_name is not None:
|
||||
@ -238,14 +249,14 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
if VModel in model_name and data['inst_only']:
|
||||
sf.write(vocal_path,
|
||||
wav_vocals.T, sameplerate)
|
||||
normalization_set(wav_vocals).T, samplerate, subtype=wav_type_set)
|
||||
elif VModel in model_name and data['voc_only']:
|
||||
pass
|
||||
elif data['inst_only']:
|
||||
pass
|
||||
else:
|
||||
sf.write(vocal_path,
|
||||
wav_vocals.T, sameplerate)
|
||||
normalization_set(wav_vocals).T, samplerate, subtype=wav_type_set)
|
||||
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
try:
|
||||
@ -253,7 +264,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(vocal_path)
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(vocal_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_v == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -265,7 +276,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
pass
|
||||
else:
|
||||
musfile = pydub.AudioSegment.from_wav(instrumental_path)
|
||||
musfile.export(instrumental_path_mp3, format="mp3", bitrate="320k")
|
||||
musfile.export(instrumental_path_mp3, format="mp3", bitrate=mp3_bit_set)
|
||||
if file_exists_i == 'there':
|
||||
pass
|
||||
else:
|
||||
@ -377,6 +388,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
# Update default settings
|
||||
global default_window_size
|
||||
global default_agg
|
||||
global normalization_set
|
||||
default_window_size = data['window_size']
|
||||
default_agg = data['agg']
|
||||
|
||||
@ -390,15 +402,42 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
demucs_model_set = data['demucsmodel_sel_VR']
|
||||
split_mode = data['split_mode']
|
||||
|
||||
if data['wavtype'] == '32-bit Float':
|
||||
wav_type_set = 'FLOAT'
|
||||
elif data['wavtype'] == '64-bit Float':
|
||||
wav_type_set = 'DOUBLE'
|
||||
else:
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
flac_type_set = data['flactype']
|
||||
mp3_bit_set = data['mp3bit']
|
||||
|
||||
if data['normalize'] == True:
|
||||
normalization_set = spec_utils.normalize
|
||||
print('normalization on')
|
||||
else:
|
||||
normalization_set = spec_utils.nonormalize
|
||||
print('normalization off')
|
||||
|
||||
vocal_remover = VocalRemover(data, text_widget)
|
||||
modelFolderName = determineModelFolderName()
|
||||
|
||||
timestampnum = round(datetime.utcnow().timestamp())
|
||||
randomnum = randrange(100000, 1000000)
|
||||
|
||||
# Separation Preperation
|
||||
try: #Load File(s)
|
||||
for file_num, music_file in enumerate(data['input_paths'], start=1):
|
||||
# Determine File Name
|
||||
m=music_file
|
||||
base_name = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
if data['settest']:
|
||||
try:
|
||||
base_name = f'{data["export_path"]}/{str(timestampnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
except:
|
||||
base_name = f'{data["export_path"]}/{str(randomnum)}_{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
else:
|
||||
base_name = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
model_name = os.path.basename(data[f'{data["useModel"]}Model'])
|
||||
model = vocal_remover.models[data['useModel']]
|
||||
@ -436,6 +475,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
except:
|
||||
pass
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Flac':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
#Load Model
|
||||
text_widget.write(base_text + 'Loading models...')
|
||||
|
||||
|
||||
@ -6,6 +6,7 @@ from pathlib import Path
|
||||
import pydub
|
||||
import hashlib
|
||||
from random import randrange
|
||||
import re
|
||||
|
||||
import subprocess
|
||||
import soundfile as sf
|
||||
@ -172,7 +173,7 @@ class Predictor():
|
||||
widget_text.write(base_text + 'Preparing to save Instrumental...')
|
||||
else:
|
||||
widget_text.write(base_text + 'Saving vocals... ')
|
||||
sf.write(non_reduced_vocal_path, sources[c].T, samplerate)
|
||||
sf.write(non_reduced_vocal_path, sources[c].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.9))
|
||||
widget_text.write('Done!\n')
|
||||
@ -193,17 +194,17 @@ class Predictor():
|
||||
widget_text.write(base_text + 'Saving Vocals... ')
|
||||
if demucs_only == 'on':
|
||||
if 'UVR' in model_set_name:
|
||||
sf.write(vocal_path, sources[1].T, samplerate)
|
||||
sf.write(vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.95))
|
||||
widget_text.write('Done!\n')
|
||||
if 'extra' in model_set_name:
|
||||
sf.write(vocal_path, sources[3].T, samplerate)
|
||||
sf.write(vocal_path, sources[3].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.95))
|
||||
widget_text.write('Done!\n')
|
||||
else:
|
||||
sf.write(non_reduced_vocal_path, sources[3].T, samplerate)
|
||||
sf.write(non_reduced_vocal_path, sources[3].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.9))
|
||||
widget_text.write('Done!\n')
|
||||
@ -221,7 +222,7 @@ class Predictor():
|
||||
c += 1
|
||||
if demucs_switch == 'off':
|
||||
widget_text.write(base_text + 'Saving Vocals..')
|
||||
sf.write(vocal_path, sources[c].T, samplerate)
|
||||
sf.write(vocal_path, sources[c].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.9))
|
||||
widget_text.write('Done!\n')
|
||||
@ -229,11 +230,11 @@ class Predictor():
|
||||
widget_text.write(base_text + 'Saving Vocals... ')
|
||||
if demucs_only == 'on':
|
||||
if 'UVR' in model_set_name:
|
||||
sf.write(vocal_path, sources[1].T, samplerate)
|
||||
sf.write(vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
|
||||
if 'extra' in model_set_name:
|
||||
sf.write(vocal_path, sources[3].T, samplerate)
|
||||
sf.write(vocal_path, sources[3].T, samplerate, subtype=wav_type_set)
|
||||
else:
|
||||
sf.write(vocal_path, sources[3].T, samplerate)
|
||||
sf.write(vocal_path, sources[3].T, samplerate, subtype=wav_type_set)
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.9))
|
||||
widget_text.write('Done!\n')
|
||||
@ -284,7 +285,7 @@ class Predictor():
|
||||
v_spec = specs[1] - max_mag * np.exp(1.j * np.angle(specs[0]))
|
||||
update_progress(**progress_kwargs,
|
||||
step=(0.95))
|
||||
sf.write(Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
|
||||
sf.write(Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
|
||||
if data['inst_only']:
|
||||
if file_exists == 'there':
|
||||
pass
|
||||
@ -413,7 +414,10 @@ class Predictor():
|
||||
algorithm=data['mixing'],
|
||||
value=b[3])*float(compensate)) # compensation
|
||||
|
||||
return sources
|
||||
if demucs_switch == 'off':
|
||||
return sources*float(compensate)
|
||||
else:
|
||||
return sources
|
||||
|
||||
def demix_base(self, mixes, margin_size):
|
||||
chunked_sources = []
|
||||
@ -642,11 +646,15 @@ data = {
|
||||
'shifts': 0,
|
||||
'margin': 44100,
|
||||
'split_mode': False,
|
||||
'normalize': False,
|
||||
'compensate': 1.03597672895,
|
||||
'autocompensate': True,
|
||||
'demucs_only': False,
|
||||
'mixing': 'Default',
|
||||
'DemucsModel_MDX': 'UVR_Demucs_Model_1',
|
||||
'wavtype': 'PCM_16',
|
||||
'mp3bit': '320k',
|
||||
'settest': False,
|
||||
|
||||
# Models
|
||||
'instrumentalModel': None,
|
||||
@ -694,21 +702,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
global ModelName_2
|
||||
global compensate
|
||||
global autocompensate
|
||||
|
||||
global demucs_model_set
|
||||
|
||||
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
|
||||
|
||||
global split_mode
|
||||
global demucs_switch
|
||||
global demucs_only
|
||||
global wav_type_set
|
||||
global flac_type_set
|
||||
global mp3_bit_set
|
||||
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
# Update default settings
|
||||
default_chunks = data['chunks']
|
||||
@ -768,7 +777,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
# to reversement
|
||||
|
||||
sf.write(f'temp.wav',
|
||||
wav_instrument, mp.param['sr'])
|
||||
normalization_set(wav_instrument), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
# -Save files-
|
||||
# Instrumental
|
||||
@ -780,14 +789,14 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
if VModel in ModelName_1 and data['voc_only']:
|
||||
sf.write(instrumental_path,
|
||||
wav_instrument, mp.param['sr'])
|
||||
normalization_set(wav_instrument), mp.param['sr'], subtype=wav_type_set)
|
||||
elif VModel in ModelName_1 and data['inst_only']:
|
||||
pass
|
||||
elif data['voc_only']:
|
||||
pass
|
||||
else:
|
||||
sf.write(instrumental_path,
|
||||
wav_instrument, mp.param['sr'])
|
||||
normalization_set(wav_instrument), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
# Vocal
|
||||
if vocal_name is not None:
|
||||
@ -798,23 +807,42 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
|
||||
if VModel in ModelName_1 and data['inst_only']:
|
||||
sf.write(vocal_path,
|
||||
wav_vocals, mp.param['sr'])
|
||||
normalization_set(wav_vocals), mp.param['sr'], subtype=wav_type_set)
|
||||
elif VModel in ModelName_1 and data['voc_only']:
|
||||
pass
|
||||
elif data['inst_only']:
|
||||
pass
|
||||
else:
|
||||
sf.write(vocal_path,
|
||||
wav_vocals, mp.param['sr'])
|
||||
normalization_set(wav_vocals), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
data.update(kwargs)
|
||||
|
||||
# Update default settings
|
||||
global default_window_size
|
||||
global default_agg
|
||||
global normalization_set
|
||||
|
||||
default_window_size = data['window_size']
|
||||
default_agg = data['agg']
|
||||
|
||||
if data['wavtype'] == '32-bit Float':
|
||||
wav_type_set = 'FLOAT'
|
||||
elif data['wavtype'] == '64-bit Float':
|
||||
wav_type_set = 'DOUBLE'
|
||||
else:
|
||||
wav_type_set = data['wavtype']
|
||||
|
||||
flac_type_set = data['flactype']
|
||||
mp3_bit_set = data['mp3bit']
|
||||
|
||||
if data['normalize'] == True:
|
||||
normalization_set = spec_utils.normalize
|
||||
print('normalization on')
|
||||
else:
|
||||
normalization_set = spec_utils.nonormalize
|
||||
print('normalization off')
|
||||
|
||||
stime = time.perf_counter()
|
||||
progress_var.set(0)
|
||||
text_widget.clear()
|
||||
@ -853,6 +881,21 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
else:
|
||||
demucs_only = 'off'
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Flac':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if data['wavtype'] == '64-bit Float':
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
text_widget.write('Please select \"WAV\" as your save format to use 64-bit Float.\n')
|
||||
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}')
|
||||
progress_var.set(0)
|
||||
button_widget.configure(state=tk.NORMAL) # Enable Button
|
||||
return
|
||||
|
||||
if not data['ensChoose'] == 'Manual Ensemble':
|
||||
|
||||
@ -1706,10 +1749,17 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
os.mkdir(folder_path)
|
||||
|
||||
# Determine File Name
|
||||
|
||||
base_name = f'{data["export_path"]}{enseFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
enseExport = f'{data["export_path"]}{enseFolderName}/'
|
||||
trackname = f'{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
|
||||
|
||||
def get_numbers_from_filename(filename):
|
||||
return re.search(r'\d+', filename).group(0)
|
||||
|
||||
foldernum = get_numbers_from_filename(enseFolderName)
|
||||
|
||||
|
||||
if c['model_location'] == 'pass':
|
||||
pass
|
||||
@ -2249,79 +2299,156 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
return [f"{folder}{i}" for i in os.listdir(folder) if i.startswith(prefix) if i.endswith(suffix)]
|
||||
|
||||
if data['appendensem'] == False:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_(Instrumental)'.format(trackname),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_(Vocals)'.format(trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
if data['settest']:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_{}_(Instrumental)'.format(foldernum, trackname),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_{}_(Vocals)'.format(foldernum, trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_(Instrumental)'.format(trackname),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_{}_(Instrumental)'.format(foldernum, trackname),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_{}_(Vocals)'.format(foldernum, trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
else:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_(Instrumental)'.format(trackname),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_(Vocals)'.format(trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_(Instrumental)'.format(trackname),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_(Vocals)'.format(trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_(Vocals)'.format(trackname),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
else:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
if data['settest']:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_{}_Ensembled_{}_(Instrumental)'.format(foldernum, trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_{}_Ensembled_{}_(Vocals)'.format(foldernum, trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_{}_Ensembled_{}_(Instrumental)'.format(foldernum, trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_{}_Ensembled_{}_(Vocals)'.format(foldernum, trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
else:
|
||||
voc_inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
},
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
inst = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
|
||||
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocal = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
|
||||
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
if data['voc_only']:
|
||||
ensembles = vocal
|
||||
@ -2362,13 +2489,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
del wave
|
||||
|
||||
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
|
||||
spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
|
||||
specs), mp), mp.param['sr'])
|
||||
normalization_set(spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
|
||||
specs), mp)), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
try:
|
||||
musfile = pydub.AudioSegment.from_wav(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])))
|
||||
musfile.export((os.path.join('{}'.format(data['export_path']),'{}.mp3'.format(e['output']))), format="mp3", bitrate="320k")
|
||||
musfile.export((os.path.join('{}'.format(data['export_path']),'{}.mp3'.format(e['output']))), format="mp3", bitrate=mp3_bit_set)
|
||||
os.remove((os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))))
|
||||
except Exception as e:
|
||||
traceback_text = ''.join(traceback.format_tb(e.__traceback__))
|
||||
@ -2456,7 +2583,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
if trackname in file:
|
||||
musfile = pydub.AudioSegment.from_wav(file)
|
||||
#rename them using the old name + ".wav"
|
||||
musfile.export("{0}.mp3".format(name), format="mp3", bitrate="320k")
|
||||
musfile.export("{0}.mp3".format(name), format="mp3", bitrate=mp3_bit_set)
|
||||
try:
|
||||
files = get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav")
|
||||
for file in files:
|
||||
@ -2607,39 +2734,112 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
savefilename = (data['input_paths'][0])
|
||||
trackname1 = f'{os.path.splitext(os.path.basename(savefilename))[0]}'
|
||||
|
||||
insts = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output':'{}_Manual_Ensemble_(Min Spec)'.format(trackname1),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
timestampnum = round(datetime.utcnow().timestamp())
|
||||
randomnum = randrange(100000, 1000000)
|
||||
|
||||
vocals = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_Manual_Ensemble_(Max Spec)'.format(trackname1),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
if data['settest']:
|
||||
try:
|
||||
insts = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output':'{}_{}_Manual_Ensemble_(Min Spec)'.format(timestampnum, trackname1),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
invert_spec = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_diff_si'.format(trackname1),
|
||||
'type': 'Spectral Inversion'
|
||||
}
|
||||
]
|
||||
vocals = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_Manual_Ensemble_(Max Spec)'.format(timestampnum, trackname1),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
invert_nor = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_diff_ni'.format(trackname1),
|
||||
'type': 'Normal Inversion'
|
||||
}
|
||||
]
|
||||
invert_spec = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_diff_si'.format(timestampnum, trackname1),
|
||||
'type': 'Spectral Inversion'
|
||||
}
|
||||
]
|
||||
|
||||
invert_nor = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_diff_ni'.format(timestampnum, trackname1),
|
||||
'type': 'Normal Inversion'
|
||||
}
|
||||
]
|
||||
except:
|
||||
insts = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output':'{}_{}_Manual_Ensemble_(Min Spec)'.format(randomnum, trackname1),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocals = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_Manual_Ensemble_(Max Spec)'.format(randomnum, trackname1),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
invert_spec = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_diff_si'.format(randomnum, trackname1),
|
||||
'type': 'Spectral Inversion'
|
||||
}
|
||||
]
|
||||
|
||||
invert_nor = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_{}_diff_ni'.format(randomnum, trackname1),
|
||||
'type': 'Normal Inversion'
|
||||
}
|
||||
]
|
||||
else:
|
||||
insts = [
|
||||
{
|
||||
'algorithm':'min_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output':'{}_Manual_Ensemble_(Min Spec)'.format(trackname1),
|
||||
'type': 'Instrumentals'
|
||||
}
|
||||
]
|
||||
|
||||
vocals = [
|
||||
{
|
||||
'algorithm':'max_mag',
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_Manual_Ensemble_(Max Spec)'.format(trackname1),
|
||||
'type': 'Vocals'
|
||||
}
|
||||
]
|
||||
|
||||
invert_spec = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_diff_si'.format(trackname1),
|
||||
'type': 'Spectral Inversion'
|
||||
}
|
||||
]
|
||||
|
||||
invert_nor = [
|
||||
{
|
||||
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
|
||||
'output': '{}_diff_ni'.format(trackname1),
|
||||
'type': 'Normal Inversion'
|
||||
}
|
||||
]
|
||||
|
||||
if data['algo'] == 'Instrumentals (Min Spec)':
|
||||
ensem = insts
|
||||
@ -2681,13 +2881,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
del wave
|
||||
|
||||
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
|
||||
spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
|
||||
specs), mp), mp.param['sr'])
|
||||
normalization_set(spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
|
||||
specs), mp)), mp.param['sr'], subtype=wav_type_set)
|
||||
|
||||
if data['saveFormat'] == 'Mp3':
|
||||
try:
|
||||
musfile = pydub.AudioSegment.from_wav(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])))
|
||||
musfile.export((os.path.join('{}'.format(data['export_path']),'{}.mp3'.format(e['output']))), format="mp3", bitrate="320k")
|
||||
musfile.export((os.path.join('{}'.format(data['export_path']),'{}.mp3'.format(e['output']))), format="mp3", bitrate=mp3_bit_set)
|
||||
os.remove((os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))))
|
||||
except Exception as e:
|
||||
text_widget.write('\n' + base_text + 'Failed to save output(s) as Mp3.')
|
||||
@ -2782,11 +2982,11 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
|
||||
max_mag = np.where(X_mag >= y_mag, X_mag, y_mag)
|
||||
v_spec = specs[1] - max_mag * np.exp(1.j * np.angle(specs[0]))
|
||||
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
|
||||
spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'])
|
||||
spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr'], subtype=wav_type_set)
|
||||
if data['algo'] == 'Invert (Normal)':
|
||||
v_spec = specs[0] - specs[1]
|
||||
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
|
||||
spec_utils.cmb_spectrogram_to_wave(v_spec, mp), mp.param['sr'])
|
||||
spec_utils.cmb_spectrogram_to_wave(v_spec, mp), mp.param['sr'], subtype=wav_type_set)
|
||||
text_widget.write("Done!\n")
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user