Cool_Tools/ultimatevocalremovergui
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Anjok07 2022-07-06 02:57:56 -05:00 committed by GitHub
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78
UVR.py
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@ -21,6 +21,7 @@ from PIL import Image
from PIL import ImageTk from PIL import ImageTk
import pickle # Save Data import pickle # Save Data
from pathlib import Path from pathlib import Path
# Other Modules # Other Modules
# Pathfinding # Pathfinding
@ -39,7 +40,6 @@ import inference_MDX
import inference_v5 import inference_v5
import inference_v5_ensemble import inference_v5_ensemble
import inference_demucs import inference_demucs
# Version
from __version__ import VERSION from __version__ import VERSION
from win32api import GetSystemMetrics from win32api import GetSystemMetrics
@ -112,6 +112,7 @@ DEFAULT_DATA = {
'appendensem': False, 'appendensem': False,
'demucs_only': False, 'demucs_only': False,
'split_mode': True, 'split_mode': True,
'normalize': False,
#MDX-Net #MDX-Net
'demucsmodel': False, 'demucsmodel': False,
'demucsmodelVR': False, 'demucsmodelVR': False,
@ -130,6 +131,9 @@ DEFAULT_DATA = {
'segment': 'None', 'segment': 'None',
'dim_f': 2048, 'dim_f': 2048,
'noise_pro_select': 'Auto Select', 'noise_pro_select': 'Auto Select',
'wavtype': 'PCM_16',
'flactype': 'PCM_16',
'mp3bit': '320k',
'overlap': 0.25, 'overlap': 0.25,
'shifts': 2, 'shifts': 2,
'overlap_b': 0.25, 'overlap_b': 0.25,
@ -144,6 +148,7 @@ DEFAULT_DATA = {
'DemucsModel': 'mdx_extra', 'DemucsModel': 'mdx_extra',
'DemucsModel_MDX': 'UVR_Demucs_Model_1', 'DemucsModel_MDX': 'UVR_Demucs_Model_1',
'ModelParams': 'Auto', 'ModelParams': 'Auto',
'settest': False,
} }
def open_image(path: str, size: tuple = None, keep_aspect: bool = True, rotate: int = 0) -> ImageTk.PhotoImage: def open_image(path: str, size: tuple = None, keep_aspect: bool = True, rotate: int = 0) -> ImageTk.PhotoImage:
@ -416,6 +421,7 @@ class MainWindow(TkinterDnD.Tk):
self.appendensem_var = tk.BooleanVar(value=data['appendensem']) self.appendensem_var = tk.BooleanVar(value=data['appendensem'])
self.demucs_only_var = tk.BooleanVar(value=data['demucs_only']) self.demucs_only_var = tk.BooleanVar(value=data['demucs_only'])
self.split_mode_var = tk.BooleanVar(value=data['split_mode']) self.split_mode_var = tk.BooleanVar(value=data['split_mode'])
self.normalize_var = tk.BooleanVar(value=data['normalize'])
# Processing Options # Processing Options
self.gpuConversion_var = tk.BooleanVar(value=data['gpu']) self.gpuConversion_var = tk.BooleanVar(value=data['gpu'])
self.postprocessing_var = tk.BooleanVar(value=data['postprocess']) self.postprocessing_var = tk.BooleanVar(value=data['postprocess'])
@ -443,6 +449,9 @@ class MainWindow(TkinterDnD.Tk):
self.segment_var = tk.StringVar(value=data['segment']) self.segment_var = tk.StringVar(value=data['segment'])
self.dim_f_var = tk.StringVar(value=data['dim_f']) self.dim_f_var = tk.StringVar(value=data['dim_f'])
self.noise_pro_select_var = tk.StringVar(value=data['noise_pro_select']) self.noise_pro_select_var = tk.StringVar(value=data['noise_pro_select'])
self.wavtype_var = tk.StringVar(value=data['wavtype'])
self.flactype_var = tk.StringVar(value=data['flactype'])
self.mp3bit_var = tk.StringVar(value=data['mp3bit'])
self.overlap_var = tk.StringVar(value=data['overlap']) self.overlap_var = tk.StringVar(value=data['overlap'])
self.shifts_var = tk.StringVar(value=data['shifts']) self.shifts_var = tk.StringVar(value=data['shifts'])
self.overlap_b_var = tk.StringVar(value=data['overlap_b']) self.overlap_b_var = tk.StringVar(value=data['overlap_b'])
@ -459,6 +468,7 @@ class MainWindow(TkinterDnD.Tk):
self.inst_only_b_var = tk.BooleanVar(value=data['inst_only_b']) self.inst_only_b_var = tk.BooleanVar(value=data['inst_only_b'])
self.audfile_var = tk.BooleanVar(value=data['audfile']) self.audfile_var = tk.BooleanVar(value=data['audfile'])
self.autocompensate_var = tk.BooleanVar(value=data['autocompensate']) self.autocompensate_var = tk.BooleanVar(value=data['autocompensate'])
self.settest_var = tk.BooleanVar(value=data['settest'])
# Choose Conversion Method # Choose Conversion Method
self.aiModel_var = tk.StringVar(value=data['aiModel']) self.aiModel_var = tk.StringVar(value=data['aiModel'])
self.last_aiModel = self.aiModel_var.get() self.last_aiModel = self.aiModel_var.get()
@ -530,8 +540,10 @@ class MainWindow(TkinterDnD.Tk):
self.command_Text = ThreadSafeConsole(master=self, self.command_Text = ThreadSafeConsole(master=self,
background='#0e0e0f',fg='#898b8e', font=('Century Gothic', 11),borderwidth=0) background='#0e0e0f',fg='#898b8e', font=('Century Gothic', 11),borderwidth=0)
#self.command_Text.write(f'Ultimate Vocal Remover [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
self.command_Text.write(f'Ultimate Vocal Remover v{VERSION} [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n') self.command_Text.write(f'Ultimate Vocal Remover v{VERSION} [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]\n')
def configure_widgets(self): def configure_widgets(self):
"""Change widget styling and appearance""" """Change widget styling and appearance"""
@ -1223,6 +1235,7 @@ class MainWindow(TkinterDnD.Tk):
'appendensem': self.appendensem_var.get(), 'appendensem': self.appendensem_var.get(),
'demucs_only': self.demucs_only_var.get(), 'demucs_only': self.demucs_only_var.get(),
'split_mode': self.split_mode_var.get(), 'split_mode': self.split_mode_var.get(),
'normalize': self.normalize_var.get(),
'tta': self.tta_var.get(), 'tta': self.tta_var.get(),
'save': self.save_var.get(), 'save': self.save_var.get(),
'output_image': self.outputImage_var.get(), 'output_image': self.outputImage_var.get(),
@ -1261,6 +1274,7 @@ class MainWindow(TkinterDnD.Tk):
'inst_only_b': self.inst_only_b_var.get(), 'inst_only_b': self.inst_only_b_var.get(),
'audfile': self.audfile_var.get(), 'audfile': self.audfile_var.get(),
'autocompensate': self.autocompensate_var.get(), 'autocompensate': self.autocompensate_var.get(),
'settest': self.settest_var.get(),
'chunks': chunks, 'chunks': chunks,
'chunks_d': self.chunks_d_var.get(), 'chunks_d': self.chunks_d_var.get(),
'noisereduc_s': noisereduc_s, 'noisereduc_s': noisereduc_s,
@ -1269,6 +1283,9 @@ class MainWindow(TkinterDnD.Tk):
'segment': self.segment_var.get(), 'segment': self.segment_var.get(),
'dim_f': self.dim_f_var.get(), 'dim_f': self.dim_f_var.get(),
'noise_pro_select': self.noise_pro_select_var.get(), 'noise_pro_select': self.noise_pro_select_var.get(),
'wavtype': self.wavtype_var.get(),
'flactype': self.flactype_var.get(),
'mp3bit': self.mp3bit_var.get(),
'overlap': self.overlap_var.get(), 'overlap': self.overlap_var.get(),
'shifts': self.shifts_var.get(), 'shifts': self.shifts_var.get(),
'overlap_b': self.overlap_b_var.get(), 'overlap_b': self.overlap_b_var.get(),
@ -2009,14 +2026,13 @@ class MainWindow(TkinterDnD.Tk):
if self.autocompensate_var.get() == True: if self.autocompensate_var.get() == True:
self.compensate_var.set('Auto')
try: try:
self.options_compensate.configure(state=tk.DISABLED) self.options_compensate.configure(state=tk.DISABLED)
except: except:
pass pass
if self.autocompensate_var.get() == False: if self.autocompensate_var.get() == False:
self.compensate_var.set(1.03597672895) #self.compensate_var.set()
try: try:
self.options_compensate.configure(state=tk.NORMAL) self.options_compensate.configure(state=tk.NORMAL)
except: except:
@ -2365,25 +2381,19 @@ class MainWindow(TkinterDnD.Tk):
l0.grid(row=10,column=0,padx=0,pady=0) l0.grid(row=10,column=0,padx=0,pady=0)
l0=ttk.Checkbutton(frame0, text='Save Stems to Model & Track Name Directory', variable=self.audfile_var) l0=ttk.Checkbutton(frame0, text='Save Stems to Model & Track Name Directory', variable=self.audfile_var)
l0.grid(row=11,column=0,padx=0,pady=0) l0.grid(row=11,column=0,padx=0,pady=5)
l0=ttk.Checkbutton(frame0, text='Settings Test Mode', variable=self.modelFolder_var)
l0.grid(row=12,column=0,padx=0,pady=0)
# l0=ttk.Checkbutton(frame0, text='Basic Prediction', variable=self.audfile_var)
# l0.grid(row=10,column=0,padx=0,pady=0)
l0=ttk.Button(frame0,text='Open Demucs Model Folder', command=self.open_Modelfolder_de) l0=ttk.Button(frame0,text='Open Demucs Model Folder', command=self.open_Modelfolder_de)
l0.grid(row=13,column=0,padx=0,pady=0) l0.grid(row=12,column=0,padx=0,pady=0)
l0=ttk.Button(frame0,text='Back to Main Menu', command=close_win) l0=ttk.Button(frame0,text='Back to Main Menu', command=close_win)
l0.grid(row=14,column=0,padx=0,pady=10) l0.grid(row=13,column=0,padx=0,pady=10)
def close_win_self(): def close_win_self():
top.destroy() top.destroy()
l0=ttk.Button(frame0,text='Close Window', command=close_win_self) l0=ttk.Button(frame0,text='Close Window', command=close_win_self)
l0.grid(row=15,column=0,padx=0,pady=0) l0.grid(row=14,column=0,padx=0,pady=0)
def advanced_mdx_options(self): def advanced_mdx_options(self):
@ -2467,13 +2477,13 @@ class MainWindow(TkinterDnD.Tk):
l0.grid(row=8,column=0,padx=0,pady=0) l0.grid(row=8,column=0,padx=0,pady=0)
l0=ttk.Checkbutton(frame0, text='Autoset Volume Compensation', variable=self.autocompensate_var) l0=ttk.Checkbutton(frame0, text='Autoset Volume Compensation', variable=self.autocompensate_var)
l0.grid(row=9,column=0,padx=0,pady=10) l0.grid(row=9,column=0,padx=0,pady=5)
l0=ttk.Checkbutton(frame0, text='Reduce Instrumental Noise Separately', variable=self.nophaseinst_var) l0=ttk.Checkbutton(frame0, text='Reduce Instrumental Noise Separately', variable=self.nophaseinst_var)
l0.grid(row=10,column=0,padx=0,pady=0) l0.grid(row=10,column=0,padx=0,pady=0)
l0=tk.Label(frame0, text='Noise Profile', font=("Century Gothic", "9"), foreground='#13a4c9') l0=tk.Label(frame0, text='Noise Profile', font=("Century Gothic", "9"), foreground='#13a4c9')
l0.grid(row=11,column=0,padx=0,pady=10) l0.grid(row=11,column=0,padx=0,pady=5)
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=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=12,column=0,padx=0,pady=0) l0.grid(row=12,column=0,padx=0,pady=0)
@ -3242,14 +3252,19 @@ class MainWindow(TkinterDnD.Tk):
tabControl = ttk.Notebook(top) tabControl = ttk.Notebook(top)
tab1 = ttk.Frame(tabControl) tab1 = ttk.Frame(tabControl)
tab2 = ttk.Frame(tabControl)
tabControl.add(tab1, text ='Settings Guide') tabControl.add(tab1, text ='Settings Guide')
tabControl.add(tab2, text ='Audio Format Settings')
tabControl.pack(expand = 1, fill ="both") tabControl.pack(expand = 1, fill ="both")
tab1.grid_rowconfigure(0, weight=1) tab1.grid_rowconfigure(0, weight=1)
tab1.grid_columnconfigure(0, weight=1) tab1.grid_columnconfigure(0, weight=1)
tab2.grid_rowconfigure(0, weight=1)
tab2.grid_columnconfigure(0, weight=1)
frame0=Frame(tab1,highlightbackground='red',highlightthicknes=0) frame0=Frame(tab1,highlightbackground='red',highlightthicknes=0)
frame0.grid(row=0,column=0,padx=0,pady=0) frame0.grid(row=0,column=0,padx=0,pady=0)
@ -3277,11 +3292,35 @@ class MainWindow(TkinterDnD.Tk):
l0=Label(frame0,text="Additional Options",font=("Century Gothic", "13", "bold", "underline"), justify="center", fg="#13a4c9") l0=Label(frame0,text="Additional Options",font=("Century Gothic", "13", "bold", "underline"), justify="center", fg="#13a4c9")
l0.grid(row=7,column=0,padx=0,pady=10) l0.grid(row=7,column=0,padx=0,pady=10)
l0=ttk.Checkbutton(frame0, text='Settings Test Mode', variable=self.settest_var)
l0.grid(row=8,column=0,padx=0,pady=0)
l0=ttk.Button(frame0,text='Open Application Directory', command=self.open_appdir_filedialog) l0=ttk.Button(frame0,text='Open Application Directory', command=self.open_appdir_filedialog)
l0.grid(row=8,column=0,padx=20,pady=5) l0.grid(row=9,column=0,padx=20,pady=5)
l0=ttk.Button(frame0,text='Close Window', command=close_win) l0=ttk.Button(frame0,text='Close Window', command=close_win)
l0.grid(row=9,column=0,padx=20,pady=5) l0.grid(row=10,column=0,padx=20,pady=5)
frame0=Frame(tab2,highlightbackground='red',highlightthicknes=0)
frame0.grid(row=0,column=0,padx=0,pady=0)
l0=Label(frame0,text="Audio Format Settings",font=("Century Gothic", "13", "bold", "underline"), justify="center", fg="#13a4c9")
l0.grid(row=0,column=0,padx=0,pady=10)
l0=tk.Label(frame0, text='Wav Type', font=("Century Gothic", "9"), foreground='#13a4c9')
l0.grid(row=1,column=0,padx=0,pady=10)
l0=ttk.OptionMenu(frame0, self.wavtype_var, None, 'PCM_U8', 'PCM_16', 'PCM_24', 'PCM_32', '32-bit Float', '64-bit Float')
l0.grid(row=2,column=0,padx=20,pady=0)
l0=tk.Label(frame0, text='Mp3 Bitrate', font=("Century Gothic", "9"), foreground='#13a4c9')
l0.grid(row=5,column=0,padx=0,pady=10)
l0=ttk.OptionMenu(frame0, self.mp3bit_var, None, '96k', '128k', '160k', '224k', '256k', '320k')
l0.grid(row=6,column=0,padx=20,pady=0)
l0=ttk.Checkbutton(frame0, text='Normalize Outputs\n(Prevents clipping)', variable=self.normalize_var)
l0.grid(row=7,column=0,padx=0,pady=10)
def error_log(self): def error_log(self):
@ -3443,6 +3482,7 @@ class MainWindow(TkinterDnD.Tk):
'appendensem': self.appendensem_var.get(), 'appendensem': self.appendensem_var.get(),
'demucs_only': self.demucs_only_var.get(), 'demucs_only': self.demucs_only_var.get(),
'split_mode': self.split_mode_var.get(), 'split_mode': self.split_mode_var.get(),
'normalize': self.normalize_var.get(),
'postprocess': self.postprocessing_var.get(), 'postprocess': self.postprocessing_var.get(),
'tta': self.tta_var.get(), 'tta': self.tta_var.get(),
'save': self.save_var.get(), 'save': self.save_var.get(),
@ -3473,12 +3513,16 @@ class MainWindow(TkinterDnD.Tk):
'inst_only_b': self.inst_only_b_var.get(), 'inst_only_b': self.inst_only_b_var.get(),
'audfile': self.audfile_var.get(), 'audfile': self.audfile_var.get(),
'autocompensate': self.autocompensate_var.get(), 'autocompensate': self.autocompensate_var.get(),
'settest': self.settest_var.get(),
'chunks': chunks, 'chunks': chunks,
'chunks_d': self.chunks_d_var.get(), 'chunks_d': self.chunks_d_var.get(),
'n_fft_scale': self.n_fft_scale_var.get(), 'n_fft_scale': self.n_fft_scale_var.get(),
'segment': self.segment_var.get(), 'segment': self.segment_var.get(),
'dim_f': self.dim_f_var.get(), 'dim_f': self.dim_f_var.get(),
'noise_pro_select': self.noise_pro_select_var.get(), 'noise_pro_select': self.noise_pro_select_var.get(),
'wavtype': self.wavtype_var.get(),
'flactype': self.flactype_var.get(),
'mp3bit': self.mp3bit_var.get(),
'overlap': self.overlap_var.get(), 'overlap': self.overlap_var.get(),
'shifts': self.shifts_var.get(), 'shifts': self.shifts_var.get(),
'overlap_b': self.overlap_b_var.get(), 'overlap_b': self.overlap_b_var.get(),

98
inference_MDX.py
View File

@ -38,6 +38,7 @@ import torch
import tkinter as tk import tkinter as tk
import traceback # Error Message Recent Calls import traceback # Error Message Recent Calls
import time # Timer import time # Timer
from random import randrange
from typing import Literal from typing import Literal
@ -213,7 +214,7 @@ class Predictor():
non_reduced_Instrumental_path = '{save_path}/{file_name}.wav'.format( non_reduced_Instrumental_path = '{save_path}/{file_name}.wav'.format(
save_path=save_path, save_path=save_path,
file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',) file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',)
non_reduced_path_mp3 = '{save_path}/{file_name}.mp3'.format( non_reduced_Instrumental_path_mp3 = '{save_path}/{file_name}.mp3'.format(
save_path=save_path, save_path=save_path,
file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',) file_name = f'{os.path.basename(_basename)}_{Instrumental_name}_{model_set_name}_No_Reduction',)
non_reduced_Instrumental_path_flac = '{save_path}/{file_name}.flac'.format( non_reduced_Instrumental_path_flac = '{save_path}/{file_name}.flac'.format(
@ -257,7 +258,7 @@ class Predictor():
else: else:
widget_text.write(base_text + 'Saving vocals... ') 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -279,9 +280,9 @@ class Predictor():
if data['demucs_only']: if data['demucs_only']:
if 'UVR' in demucs_model_set: if 'UVR' in demucs_model_set:
sf.write(non_reduced_vocal_path, sources[1].T, samplerate) sf.write(non_reduced_vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
else: else:
sf.write(non_reduced_vocal_path, sources[source_val].T, samplerate) sf.write(non_reduced_vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
update_progress(**progress_kwargs, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -304,7 +305,7 @@ class Predictor():
widget_text.write(base_text + 'Preparing Instrumental...') widget_text.write(base_text + 'Preparing Instrumental...')
else: else:
widget_text.write(base_text + 'Saving Vocals... ') 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -316,11 +317,11 @@ class Predictor():
if data['demucs_only']: if data['demucs_only']:
if 'UVR' in demucs_model_set: if 'UVR' in demucs_model_set:
sf.write(vocal_path, sources[1].T, samplerate) sf.write(vocal_path, sources[1].T, samplerate, subtype=wav_type_set)
else: else:
sf.write(vocal_path, sources[source_val].T, samplerate) sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
else: else:
sf.write(vocal_path, sources[source_val].T, samplerate) sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
update_progress(**progress_kwargs, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
@ -387,12 +388,13 @@ class Predictor():
y_mag = np.abs(specs[1]) y_mag = np.abs(specs[1])
max_mag = np.where(X_mag >= y_mag, X_mag, y_mag) 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])) v_spec = specs[1] - max_mag * np.exp(1.j * np.angle(specs[0]))
update_progress(**progress_kwargs, update_progress(**progress_kwargs,
step=(1)) step=(1))
if not data['noisereduc_s'] == 'None': if not data['noisereduc_s'] == 'None':
if data['nophaseinst']: if data['nophaseinst']:
sf.write(non_reduced_Instrumental_path, spec_utils.cmb_spectrogram_to_wave(-v_spec, mp), mp.param['sr']) sf.write(non_reduced_Instrumental_path, normalization_set(spec_utils.cmb_spectrogram_to_wave(-v_spec, mp)), mp.param['sr'], subtype=wav_type_set)
reduction_sen = float(data['noisereduc_s'])/10 reduction_sen = float(data['noisereduc_s'])/10
print(noise_pro_set) print(noise_pro_set)
@ -403,9 +405,9 @@ class Predictor():
shell=True, stdout=subprocess.PIPE, shell=True, stdout=subprocess.PIPE,
stdin=subprocess.PIPE, stderr=subprocess.PIPE) stdin=subprocess.PIPE, stderr=subprocess.PIPE)
else: else:
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)
else: else:
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 data['inst_only']:
if file_exists_v == 'there': if file_exists_v == 'there':
@ -427,7 +429,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(non_reduced_Instrumental_path) 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: try:
os.remove(non_reduced_Instrumental_path) os.remove(non_reduced_Instrumental_path)
except: except:
@ -435,7 +437,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(vocal_path) 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': if file_exists_v == 'there':
pass pass
else: else:
@ -451,7 +453,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(non_reduced_Instrumental_path) 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': if file_exists_n == 'there':
pass pass
else: else:
@ -462,7 +464,7 @@ class Predictor():
if data['voc_only'] == True: if data['voc_only'] == True:
if data['non_red'] == True: if data['non_red'] == True:
musfile = pydub.AudioSegment.from_wav(non_reduced_vocal_path) 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: try:
os.remove(non_reduced_vocal_path) os.remove(non_reduced_vocal_path)
except: except:
@ -470,7 +472,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(Instrumental_path) 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': if file_exists_i == 'there':
pass pass
else: else:
@ -483,7 +485,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(non_reduced_vocal_path) 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': if file_exists_n == 'there':
pass pass
else: else:
@ -713,7 +715,6 @@ class Predictor():
if not data['demucsmodel']: if not data['demucsmodel']:
sources = self.demix_base(segmented_mix, margin_size=margin) sources = self.demix_base(segmented_mix, margin_size=margin)
#value=float(0.9)*float(compensate)
elif data['demucs_only']: elif data['demucs_only']:
if split_mode == True: if split_mode == True:
sources = self.demix_demucs_split(mix) 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]], sources[source_val] = (spec_effects(wave=[demucs_out[source_val],base_out[0]],
algorithm=data['mixing'], algorithm=data['mixing'],
value=b[source_val])*float(compensate)) # compensation 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): def demix_base(self, mixes, margin_size):
chunked_sources = [] chunked_sources = []
@ -882,10 +887,14 @@ data = {
'shifts': 0, 'shifts': 0,
'margin': 44100, 'margin': 44100,
'split_mode': False, 'split_mode': False,
'normalize': False,
'nophaseinst': True, 'nophaseinst': True,
'compensate': 1.03597672895, 'compensate': 1.03597672895,
'autocompensate': True, 'autocompensate': True,
'demucs_only': False, 'demucs_only': False,
'wavtype': 'PCM_16',
'flactype': 'PCM_16',
'mp3bit': '320k',
'mixing': 'Default', 'mixing': 'Default',
'DemucsModel_MDX': 'UVR_Demucs_Model_1', 'DemucsModel_MDX': 'UVR_Demucs_Model_1',
# Choose Model # Choose Model
@ -941,10 +950,8 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
global stemset_n global stemset_n
global noise_pro_set global noise_pro_set
global demucs_model_set global demucs_model_set
global autocompensate global autocompensate
global compensate global compensate
global channel_set global channel_set
global margin_set global margin_set
global overlap_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 source_val
global split_mode global split_mode
global demucs_model_set global demucs_model_set
global wav_type_set
global flac_type_set
global mp3_bit_set
global normalization_set
global demucs_switch global demucs_switch
autocompensate = data['autocompensate']
# Update default settings # Update default settings
default_chunks = data['chunks'] 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) data.update(kwargs)
autocompensate = data['autocompensate']
if data['mdxnetModeltype'] == 'Vocals (Custom)': if data['mdxnetModeltype'] == 'Vocals (Custom)':
stemset = 'v' stemset = 'v'
source_val_set = 3 source_val_set = 3
@ -1156,7 +1168,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
else: else:
noise_pro_set = data['noise_pro_select'] 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(n_fft_scale_set)
print(dim_f_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'] split_mode = data['split_mode']
demucs_switch = data['demucsmodel'] 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 stemset_n == '(Bass)':
if 'UVR' in demucs_model_set: if 'UVR' in demucs_model_set:
text_widget.write('The selected Demucs model can only be used with vocal stems.\n') 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 pass
_mixture = f'{data["input_paths"]}' _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- # -Get text and update progress-
base_text = get_baseText(total_files=len(data['input_paths']), base_text = get_baseText(total_files=len(data['input_paths']),
file_num=file_num) file_num=file_num)

93
inference_demucs.py
View File

@ -245,22 +245,22 @@ class Predictor():
pass pass
if 'UVR' in model_set_name: if 'UVR' in model_set_name:
sf.write(Instrumental_path, sources[0].T, samplerate) sf.write(Instrumental_path, normalization_set(sources[0]).T, samplerate, subtype=wav_type_set)
sf.write(vocals_path, sources[1].T, samplerate) sf.write(vocals_path, normalization_set(sources[1]).T, samplerate, subtype=wav_type_set)
else: else:
sf.write(bass_path, sources[0].T, samplerate) sf.write(bass_path, normalization_set(sources[0]).T, samplerate, subtype=wav_type_set)
sf.write(drums_path, sources[1].T, samplerate) sf.write(drums_path, normalization_set(sources[1]).T, samplerate, subtype=wav_type_set)
sf.write(other_path, sources[2].T, samplerate) sf.write(other_path, normalization_set(sources[2]).T, samplerate, subtype=wav_type_set)
sf.write(vocals_path, sources[3].T, samplerate) sf.write(vocals_path, normalization_set(sources[3]).T, samplerate, subtype=wav_type_set)
if data['saveFormat'] == 'Mp3': if data['saveFormat'] == 'Mp3':
try: try:
if 'UVR' in model_set_name: if 'UVR' in model_set_name:
widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ') widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ')
musfile = pydub.AudioSegment.from_wav(vocals_path) 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 = 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: try:
os.remove(Instrumental_path) os.remove(Instrumental_path)
os.remove(vocals_path) os.remove(vocals_path)
@ -269,13 +269,13 @@ class Predictor():
else: else:
widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ') widget_text.write(base_text + 'Saving Stem(s) as Mp3(s)... ')
musfile = pydub.AudioSegment.from_wav(drums_path) 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 = 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 = 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 = 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: try:
os.remove(drums_path) os.remove(drums_path)
os.remove(bass_path) os.remove(bass_path)
@ -364,11 +364,11 @@ class Predictor():
else: else:
if 'UVR' in model_set_name: if 'UVR' in model_set_name:
if stemset_n == '(Vocals)': 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: else:
sf.write(vocal_path, sources[source_val].T, samplerate) sf.write(vocal_path, sources[source_val].T, samplerate, subtype=wav_type_set)
else: 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') widget_text.write('Done!\n')
@ -426,7 +426,7 @@ class Predictor():
update_progress(**progress_kwargs, update_progress(**progress_kwargs,
step=(1)) 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']: if data['inst_only_b']:
@ -449,7 +449,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(vocal_path) 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': if file_exists_v == 'there':
pass pass
else: else:
@ -461,7 +461,7 @@ class Predictor():
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(Instrumental_path) 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': if file_exists_i == 'there':
pass pass
else: else:
@ -693,7 +693,7 @@ data = {
'demucsmodel': True, 'demucsmodel': True,
'gpu': -1, 'gpu': -1,
'chunks_d': 'Full', 'chunks_d': 'Full',
'modelFolder': False, 'settest': False,
'voc_only_b': False, 'voc_only_b': False,
'inst_only_b': False, 'inst_only_b': False,
'overlap_b': 0.25, 'overlap_b': 0.25,
@ -701,10 +701,13 @@ data = {
'segment': 'None', 'segment': 'None',
'margin': 44100, 'margin': 44100,
'split_mode': False, 'split_mode': False,
'normalize': False,
'compensate': 1.03597672895, 'compensate': 1.03597672895,
'demucs_stems': 'All Stems', 'demucs_stems': 'All Stems',
'DemucsModel': 'mdx_extra', 'DemucsModel': 'mdx_extra',
'audfile': True, 'audfile': True,
'wavtype': 'PCM_16',
'mp3bit': '320k',
} }
default_chunks = data['chunks_d'] 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 source_val
global split_mode 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 # Update default settings
default_chunks = data['chunks_d'] 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) 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() stime = time.perf_counter()
progress_var.set(0) progress_var.set(0)
text_widget.clear() 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) try: #Load File(s)
for file_num, music_file in tqdm(enumerate(data['input_paths'], start=1)): 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'] model_set_name = data['DemucsModel']
if data['demucs_stems'] == 'Vocals': 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) os.mkdir(folder_path)
_mixture = f'{data["input_paths"]}' _mixture = f'{data["input_paths"]}'
if data['modelFolder']: if data['settest']:
try: 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: 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: else:
_basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}' _basename = f'{data["export_path"]}{modelFolderName}{songFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
else: else:
_mixture = f'{data["input_paths"]}' _mixture = f'{data["input_paths"]}'
if data['modelFolder']: if data['settest']:
try: 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: 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: else:
_basename = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}' _basename = f'{data["export_path"]}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'

75
inference_v5.py
View File

@ -28,6 +28,7 @@ from collections import defaultdict
import tkinter as tk import tkinter as tk
import traceback # Error Message Recent Calls import traceback # Error Message Recent Calls
import time # Timer import time # Timer
from random import randrange
class VocalRemover(object): class VocalRemover(object):
@ -63,7 +64,11 @@ data = {
'shifts': 0, 'shifts': 0,
'segment': 'None', 'segment': 'None',
'split_mode': False, 'split_mode': False,
'normalize': False,
'demucsmodelVR': True, 'demucsmodelVR': True,
'wavtype': 'PCM_16',
'mp3bit': '320k',
'settest': False,
} }
default_window_size = data['window_size'] 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 shift_set
global split_mode global split_mode
global demucs_model_set global demucs_model_set
global wav_type_set
global flac_type_set
global mp3_bit_set
wav_type_set = data['wavtype']
#Error Handling #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 # and for vocal the instrumental is the temp file due
# to reversement # to reversement
if data['demucsmodelVR']: if data['demucsmodelVR']:
sameplerate = 44100 samplerate = 44100
else: else:
sameplerate = mp.param['sr'] samplerate = mp.param['sr']
sf.write(f'temp.wav', sf.write(f'temp.wav',
wav_instrument.T, sameplerate) normalization_set(wav_instrument).T, samplerate, subtype=wav_type_set)
appendModelFolderName = modelFolderName.replace('/', '_') 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']: if VModel in model_name and data['voc_only']:
sf.write(instrumental_path, 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']: elif VModel in model_name and data['inst_only']:
pass pass
elif data['voc_only']: elif data['voc_only']:
pass pass
else: else:
sf.write(instrumental_path, sf.write(instrumental_path,
wav_instrument.T, sameplerate) normalization_set(wav_instrument).T, samplerate, subtype=wav_type_set)
# Vocal # Vocal
if vocal_name is not None: 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']: if VModel in model_name and data['inst_only']:
sf.write(vocal_path, 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']: elif VModel in model_name and data['voc_only']:
pass pass
elif data['inst_only']: elif data['inst_only']:
pass pass
else: else:
sf.write(vocal_path, sf.write(vocal_path,
wav_vocals.T, sameplerate) normalization_set(wav_vocals).T, samplerate, subtype=wav_type_set)
if data['saveFormat'] == 'Mp3': if data['saveFormat'] == 'Mp3':
try: try:
@ -253,7 +264,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(vocal_path) 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': if file_exists_v == 'there':
pass pass
else: else:
@ -265,7 +276,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
pass pass
else: else:
musfile = pydub.AudioSegment.from_wav(instrumental_path) 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': if file_exists_i == 'there':
pass pass
else: else:
@ -377,6 +388,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
# Update default settings # Update default settings
global default_window_size global default_window_size
global default_agg global default_agg
global normalization_set
default_window_size = data['window_size'] default_window_size = data['window_size']
default_agg = data['agg'] 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'] demucs_model_set = data['demucsmodel_sel_VR']
split_mode = data['split_mode'] 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) vocal_remover = VocalRemover(data, text_widget)
modelFolderName = determineModelFolderName() modelFolderName = determineModelFolderName()
timestampnum = round(datetime.utcnow().timestamp())
randomnum = randrange(100000, 1000000)
# Separation Preperation # Separation Preperation
try: #Load File(s) try: #Load File(s)
for file_num, music_file in enumerate(data['input_paths'], start=1): for file_num, music_file in enumerate(data['input_paths'], start=1):
# Determine File Name # Determine File Name
m=music_file 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_name = os.path.basename(data[f'{data["useModel"]}Model'])
model = vocal_remover.models[data['useModel']] 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: except:
pass 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 #Load Model
text_widget.write(base_text + 'Loading models...') text_widget.write(base_text + 'Loading models...')

452
inference_v5_ensemble.py
View File

@ -6,6 +6,7 @@ from pathlib import Path
import pydub import pydub
import hashlib import hashlib
from random import randrange from random import randrange
import re
import subprocess import subprocess
import soundfile as sf import soundfile as sf
@ -172,7 +173,7 @@ class Predictor():
widget_text.write(base_text + 'Preparing to save Instrumental...') widget_text.write(base_text + 'Preparing to save Instrumental...')
else: else:
widget_text.write(base_text + 'Saving vocals... ') 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -193,17 +194,17 @@ class Predictor():
widget_text.write(base_text + 'Saving Vocals... ') widget_text.write(base_text + 'Saving Vocals... ')
if demucs_only == 'on': if demucs_only == 'on':
if 'UVR' in model_set_name: 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, update_progress(**progress_kwargs,
step=(0.95)) step=(0.95))
widget_text.write('Done!\n') widget_text.write('Done!\n')
if 'extra' in model_set_name: 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, update_progress(**progress_kwargs,
step=(0.95)) step=(0.95))
widget_text.write('Done!\n') widget_text.write('Done!\n')
else: 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -221,7 +222,7 @@ class Predictor():
c += 1 c += 1
if demucs_switch == 'off': if demucs_switch == 'off':
widget_text.write(base_text + 'Saving Vocals..') 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') widget_text.write('Done!\n')
@ -229,11 +230,11 @@ class Predictor():
widget_text.write(base_text + 'Saving Vocals... ') widget_text.write(base_text + 'Saving Vocals... ')
if demucs_only == 'on': if demucs_only == 'on':
if 'UVR' in model_set_name: 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: 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: 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, update_progress(**progress_kwargs,
step=(0.9)) step=(0.9))
widget_text.write('Done!\n') 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])) v_spec = specs[1] - max_mag * np.exp(1.j * np.angle(specs[0]))
update_progress(**progress_kwargs, update_progress(**progress_kwargs,
step=(0.95)) 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 data['inst_only']:
if file_exists == 'there': if file_exists == 'there':
pass pass
@ -413,7 +414,10 @@ class Predictor():
algorithm=data['mixing'], algorithm=data['mixing'],
value=b[3])*float(compensate)) # compensation 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): def demix_base(self, mixes, margin_size):
chunked_sources = [] chunked_sources = []
@ -642,11 +646,15 @@ data = {
'shifts': 0, 'shifts': 0,
'margin': 44100, 'margin': 44100,
'split_mode': False, 'split_mode': False,
'normalize': False,
'compensate': 1.03597672895, 'compensate': 1.03597672895,
'autocompensate': True, 'autocompensate': True,
'demucs_only': False, 'demucs_only': False,
'mixing': 'Default', 'mixing': 'Default',
'DemucsModel_MDX': 'UVR_Demucs_Model_1', 'DemucsModel_MDX': 'UVR_Demucs_Model_1',
'wavtype': 'PCM_16',
'mp3bit': '320k',
'settest': False,
# Models # Models
'instrumentalModel': None, 'instrumentalModel': None,
@ -694,21 +702,22 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
global ModelName_2 global ModelName_2
global compensate global compensate
global autocompensate global autocompensate
global demucs_model_set global demucs_model_set
global channel_set global channel_set
global margin_set global margin_set
global overlap_set global overlap_set
global shift_set global shift_set
global noise_pro_set global noise_pro_set
global n_fft_scale_set global n_fft_scale_set
global dim_f_set global dim_f_set
global split_mode global split_mode
global demucs_switch global demucs_switch
global demucs_only global demucs_only
global wav_type_set
global flac_type_set
global mp3_bit_set
wav_type_set = data['wavtype']
# Update default settings # Update default settings
default_chunks = data['chunks'] default_chunks = data['chunks']
@ -768,7 +777,7 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
# to reversement # to reversement
sf.write(f'temp.wav', sf.write(f'temp.wav',
wav_instrument, mp.param['sr']) normalization_set(wav_instrument), mp.param['sr'], subtype=wav_type_set)
# -Save files- # -Save files-
# Instrumental # 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']: if VModel in ModelName_1 and data['voc_only']:
sf.write(instrumental_path, 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']: elif VModel in ModelName_1 and data['inst_only']:
pass pass
elif data['voc_only']: elif data['voc_only']:
pass pass
else: else:
sf.write(instrumental_path, sf.write(instrumental_path,
wav_instrument, mp.param['sr']) normalization_set(wav_instrument), mp.param['sr'], subtype=wav_type_set)
# Vocal # Vocal
if vocal_name is not None: 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']: if VModel in ModelName_1 and data['inst_only']:
sf.write(vocal_path, 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']: elif VModel in ModelName_1 and data['voc_only']:
pass pass
elif data['inst_only']: elif data['inst_only']:
pass pass
else: else:
sf.write(vocal_path, sf.write(vocal_path,
wav_vocals, mp.param['sr']) normalization_set(wav_vocals), mp.param['sr'], subtype=wav_type_set)
data.update(kwargs) data.update(kwargs)
# Update default settings # Update default settings
global default_window_size global default_window_size
global default_agg global default_agg
global normalization_set
default_window_size = data['window_size'] default_window_size = data['window_size']
default_agg = data['agg'] 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() stime = time.perf_counter()
progress_var.set(0) progress_var.set(0)
text_widget.clear() text_widget.clear()
@ -853,6 +881,21 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
else: else:
demucs_only = 'off' 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': 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) os.mkdir(folder_path)
# Determine File Name # Determine File Name
base_name = f'{data["export_path"]}{enseFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}' base_name = f'{data["export_path"]}{enseFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
enseExport = f'{data["export_path"]}{enseFolderName}/' enseExport = f'{data["export_path"]}{enseFolderName}/'
trackname = f'{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}' 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': if c['model_location'] == 'pass':
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)] return [f"{folder}{i}" for i in os.listdir(folder) if i.startswith(prefix) if i.endswith(suffix)]
if data['appendensem'] == False: if data['appendensem'] == False:
voc_inst = [ if data['settest']:
{ voc_inst = [
'algorithm':'min_mag', {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'algorithm':'min_mag',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"), 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output':'{}_(Instrumental)'.format(trackname), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
'type': 'Instrumentals' 'output':'{}_{}_(Instrumental)'.format(foldernum, trackname),
}, 'type': 'Instrumentals'
{ },
'algorithm':'max_mag', {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'algorithm':'max_mag',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"), 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output': '{}_(Vocals)'.format(trackname), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
'type': 'Vocals' 'output': '{}_{}_(Vocals)'.format(foldernum, trackname),
} 'type': 'Vocals'
] }
]
inst = [ inst = [
{ {
'algorithm':'min_mag', 'algorithm':'min_mag',
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
'output':'{}_(Instrumental)'.format(trackname), 'output':'{}_{}_(Instrumental)'.format(foldernum, trackname),
'type': 'Instrumentals' '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: else:
voc_inst = [ if data['settest']:
{ voc_inst = [
'algorithm':'min_mag', {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'algorithm':'min_mag',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"), 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
'type': 'Instrumentals' 'output':'{}_{}_Ensembled_{}_(Instrumental)'.format(foldernum, trackname, ensemode),
}, 'type': 'Instrumentals'
{ },
'algorithm':'max_mag', {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'algorithm':'max_mag',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"), 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
'type': 'Vocals' 'output': '{}_{}_Ensembled_{}_(Vocals)'.format(foldernum, trackname, ensemode),
} 'type': 'Vocals'
] }
]
inst = [ inst = [
{ {
'algorithm':'min_mag', 'algorithm':'min_mag',
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Instrumental).wav"),
'output':'{}_Ensembled_{}_(Instrumental)'.format(trackname, ensemode), 'output':'{}_{}_Ensembled_{}_(Instrumental)'.format(foldernum, trackname, ensemode),
'type': 'Instrumentals' 'type': 'Instrumentals'
} }
] ]
vocal = [ vocal = [
{ {
'algorithm':'max_mag', 'algorithm':'max_mag',
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"), 'files':get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav"),
'output': '{}_Ensembled_{}_(Vocals)'.format(trackname, ensemode), 'output': '{}_{}_Ensembled_{}_(Vocals)'.format(foldernum, trackname, ensemode),
'type': 'Vocals' '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']: if data['voc_only']:
ensembles = vocal ensembles = vocal
@ -2362,13 +2489,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
del wave del wave
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])), sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'], normalization_set(spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
specs), mp), mp.param['sr']) specs), mp)), mp.param['sr'], subtype=wav_type_set)
if data['saveFormat'] == 'Mp3': if data['saveFormat'] == 'Mp3':
try: try:
musfile = pydub.AudioSegment.from_wav(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))) 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'])))) os.remove((os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))))
except Exception as e: except Exception as e:
traceback_text = ''.join(traceback.format_tb(e.__traceback__)) 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: if trackname in file:
musfile = pydub.AudioSegment.from_wav(file) musfile = pydub.AudioSegment.from_wav(file)
#rename them using the old name + ".wav" #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: try:
files = get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav") files = get_files(folder=enseExport, prefix=trackname, suffix="_(Vocals).wav")
for file in files: 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]) savefilename = (data['input_paths'][0])
trackname1 = f'{os.path.splitext(os.path.basename(savefilename))[0]}' trackname1 = f'{os.path.splitext(os.path.basename(savefilename))[0]}'
insts = [ timestampnum = round(datetime.utcnow().timestamp())
{ randomnum = randrange(100000, 1000000)
'algorithm':'min_mag',
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output':'{}_Manual_Ensemble_(Min Spec)'.format(trackname1),
'type': 'Instrumentals'
}
]
vocals = [ if data['settest']:
{ try:
'algorithm':'max_mag', insts = [
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', {
'output': '{}_Manual_Ensemble_(Max Spec)'.format(trackname1), 'algorithm':'min_mag',
'type': 'Vocals' 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
} 'output':'{}_{}_Manual_Ensemble_(Min Spec)'.format(timestampnum, trackname1),
] 'type': 'Instrumentals'
}
]
invert_spec = [ vocals = [
{ {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'algorithm':'max_mag',
'output': '{}_diff_si'.format(trackname1), 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'type': 'Spectral Inversion' 'output': '{}_{}_Manual_Ensemble_(Max Spec)'.format(timestampnum, trackname1),
} 'type': 'Vocals'
] }
]
invert_nor = [ invert_spec = [
{ {
'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json', 'model_params':'lib_v5/modelparams/1band_sr44100_hl512.json',
'output': '{}_diff_ni'.format(trackname1), 'output': '{}_{}_diff_si'.format(timestampnum, trackname1),
'type': 'Normal Inversion' '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)': if data['algo'] == 'Instrumentals (Min Spec)':
ensem = insts ensem = insts
@ -2681,13 +2881,13 @@ def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress
del wave del wave
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])), sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])),
spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'], normalization_set(spec_utils.cmb_spectrogram_to_wave(spec_utils.ensembling(e['algorithm'],
specs), mp), mp.param['sr']) specs), mp)), mp.param['sr'], subtype=wav_type_set)
if data['saveFormat'] == 'Mp3': if data['saveFormat'] == 'Mp3':
try: try:
musfile = pydub.AudioSegment.from_wav(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))) 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'])))) os.remove((os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output']))))
except Exception as e: except Exception as e:
text_widget.write('\n' + base_text + 'Failed to save output(s) as Mp3.') 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) 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])) 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'])), 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)': if data['algo'] == 'Invert (Normal)':
v_spec = specs[0] - specs[1] v_spec = specs[0] - specs[1]
sf.write(os.path.join('{}'.format(data['export_path']),'{}.wav'.format(e['output'])), 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") text_widget.write("Done!\n")