Cool_Tools/ultimatevocalremovergui
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# GUI modules
import tkinter as tk
import tkinter.ttk as ttk
import tkinter.messagebox
import tkinter.filedialog
import tkinter.font
from tkinterdnd2 import TkinterDnD, DND_FILES # Enable Drag & Drop
from datetime import datetime
# Images
from PIL import Image
from PIL import ImageTk
import pickle # Save Data
# Other Modules
import subprocess # Run python file
# Pathfinding
import pathlib
import sys
import os
import subprocess
from collections import defaultdict
# Used for live text displaying
import queue
import threading # Run the algorithm inside a thread
from pathlib import Path
import inference_v5
# Change the current working directory to the directory
# this file sits in
if getattr(sys, 'frozen', False):
# If the application is run as a bundle, the PyInstaller bootloader
# extends the sys module by a flag frozen=True and sets the app
# path into variable _MEIPASS'.
base_path = sys._MEIPASS
else:
base_path = os.path.dirname(os.path.abspath(__file__))
os.chdir(base_path) # Change the current working directory to the base path
instrumentalModels_dir = os.path.join(base_path, 'models')
banner_path = os.path.join(base_path, 'img', 'UVR-banner.png')
refresh_path = os.path.join(base_path, 'img', 'refresh.png')
DEFAULT_DATA = {
'exportPath': '',
'inputPaths': [],
'gpu': False,
'postprocess': False,
'tta': False,
'output_image': False,
'window_size': '512',
'agg': 10,
'modelFolder': False,
'modelInstrumentalLabel': '',
#'aiModel': 'v5',
'useModel': 'instrumental',
'lastDir': None,
}
def open_image(path: str, size: tuple = None, keep_aspect: bool = True, rotate: int = 0) -> ImageTk.PhotoImage:
"""
Open the image on the path and apply given settings\n
Paramaters:
path(str):
Absolute path of the image
size(tuple):
first value - width
second value - height
keep_aspect(bool):
keep aspect ratio of image and resize
to maximum possible width and height
(maxima are given by size)
rotate(int):
clockwise rotation of image
Returns(ImageTk.PhotoImage):
Image of path
"""
img = Image.open(path).convert(mode='RGBA')
ratio = img.height/img.width
img = img.rotate(angle=-rotate)
if size is not None:
size = (int(size[0]), int(size[1]))
if keep_aspect:
img = img.resize((size[0], int(size[0] * ratio)), Image.ANTIALIAS)
else:
img = img.resize(size, Image.ANTIALIAS)
return ImageTk.PhotoImage(img)
def save_data(data):
"""
Saves given data as a .pkl (pickle) file
Paramters:
data(dict):
Dictionary containing all the necessary data to save
"""
# Open data file, create it if it does not exist
with open('data.pkl', 'wb') as data_file:
pickle.dump(data, data_file)
def load_data() -> dict:
"""
Loads saved pkl file and returns the stored data
Returns(dict):
Dictionary containing all the saved data
"""
try:
with open('data.pkl', 'rb') as data_file: # Open data file
data = pickle.load(data_file)
return data
except (ValueError, FileNotFoundError):
# Data File is corrupted or not found so recreate it
save_data(data=DEFAULT_DATA)
return load_data()
def drop(event, accept_mode: str = 'files'):
"""
Drag & Drop verification process
"""
path = event.data
if accept_mode == 'folder':
path = path.replace('{', '').replace('}', '')
if not os.path.isdir(path):
tk.messagebox.showerror(title='Invalid Folder',
message='Your given export path is not a valid folder!')
return
# Set Variables
root.exportPath_var.set(path)
elif accept_mode == 'files':
# Clean path text and set path to the list of paths
path = path.replace('{', '')
path = path.split('} ')
path[-1] = path[-1].replace('}', '')
# Set Variables
root.inputPaths = path
root.update_inputPaths()
else:
# Invalid accept mode
return
class ThreadSafeConsole(tk.Text):
"""
Text Widget which is thread safe for tkinter
"""
def __init__(self, master, **options):
tk.Text.__init__(self, master, **options)
self.queue = queue.Queue()
self.update_me()
def write(self, line):
self.queue.put(line)
def clear(self):
self.queue.put(None)
def update_me(self):
self.configure(state=tk.NORMAL)
try:
while 1:
line = self.queue.get_nowait()
if line is None:
self.delete(1.0, tk.END)
else:
self.insert(tk.END, str(line))
self.see(tk.END)
self.update_idletasks()
except queue.Empty:
pass
self.configure(state=tk.DISABLED)
self.after(100, self.update_me)
class MainWindow(TkinterDnD.Tk):
# --Constants--
# Layout
IMAGE_HEIGHT = 140
FILEPATHS_HEIGHT = 80
OPTIONS_HEIGHT = 190
CONVERSIONBUTTON_HEIGHT = 35
COMMAND_HEIGHT = 200
PROGRESS_HEIGHT = 26
PADDING = 10
COL1_ROWS = 6
COL2_ROWS = 5
COL3_ROWS = 6
def __init__(self):
# Run the __init__ method on the tk.Tk class
super().__init__()
# Calculate window height
height = self.IMAGE_HEIGHT + self.FILEPATHS_HEIGHT + self.OPTIONS_HEIGHT
height += self.CONVERSIONBUTTON_HEIGHT + self.COMMAND_HEIGHT + self.PROGRESS_HEIGHT
height += self.PADDING * 5 # Padding
# --Window Settings--
self.title('Vocal Remover')
# Set Geometry and Center Window
self.geometry('{width}x{height}+{xpad}+{ypad}'.format(
width=620,
height=height,
xpad=int(self.winfo_screenwidth()/2 - 550/2),
ypad=int(self.winfo_screenheight()/2 - height/2 - 30)))
self.configure(bg='#000000') # Set background color to black
self.protocol("WM_DELETE_WINDOW", self.save_values)
self.resizable(False, False)
self.update()
# --Variables--
self.logo_img = open_image(path=banner_path,
size=(self.winfo_width(), 9999))
self.refresh_img = open_image(path=refresh_path,
size=(20, 20))
self.instrumentalLabel_to_path = defaultdict(lambda: '')
self.lastInstrumentalModels = []
# -Tkinter Value Holders-
data = load_data()
# Paths
self.exportPath_var = tk.StringVar(value=data['exportPath'])
self.inputPaths = data['inputPaths']
# Processing Options
self.gpuConversion_var = tk.BooleanVar(value=data['gpu'])
self.postprocessing_var = tk.BooleanVar(value=data['postprocess'])
self.tta_var = tk.BooleanVar(value=data['tta'])
self.outputImage_var = tk.BooleanVar(value=data['output_image'])
# Models
self.instrumentalModel_var = tk.StringVar(value=data['modelInstrumentalLabel'])
# Model Test Mode
self.modelFolder_var = tk.BooleanVar(value=data['modelFolder'])
# Constants
self.winSize_var = tk.StringVar(value=data['window_size'])
self.agg_var = tk.StringVar(value=data['agg'])
# AI model
#self.aiModel_var = tk.StringVar(value=data['aiModel'])
#self.last_aiModel = self.aiModel_var.get()
# Other
self.inputPathsEntry_var = tk.StringVar(value='')
self.lastDir = data['lastDir'] # nopep8
self.progress_var = tk.IntVar(value=0)
# Font
self.font = tk.font.Font(family='Microsoft JhengHei', size=9, weight='bold')
# --Widgets--
self.create_widgets()
self.configure_widgets()
self.bind_widgets()
self.place_widgets()
self.update_available_models()
self.update_states()
self.update_loop()
# -Widget Methods-
def create_widgets(self):
"""Create window widgets"""
self.title_Label = tk.Label(master=self, bg='black',
image=self.logo_img, compound=tk.TOP)
self.filePaths_Frame = tk.Frame(master=self, bg='black')
self.fill_filePaths_Frame()
self.options_Frame = tk.Frame(master=self, bg='black')
self.fill_options_Frame()
self.conversion_Button = ttk.Button(master=self,
text='Start Conversion',
command=self.start_conversion)
self.refresh_Button = ttk.Button(master=self,
image=self.refresh_img,
command=self.restart)
self.progressbar = ttk.Progressbar(master=self,
variable=self.progress_var)
self.command_Text = ThreadSafeConsole(master=self,
background='#a0a0a0',
borderwidth=0,)
self.command_Text.write(f'COMMAND LINE [{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]') # nopep8
def configure_widgets(self):
"""Change widget styling and appearance"""
ttk.Style().configure('TCheckbutton', background='black',
font=self.font, foreground='white')
ttk.Style().configure('TRadiobutton', background='black',
font=self.font, foreground='white')
ttk.Style().configure('T', font=self.font, foreground='white')
def bind_widgets(self):
"""Bind widgets to the drag & drop mechanic"""
self.filePaths_saveTo_Button.drop_target_register(DND_FILES)
self.filePaths_saveTo_Entry.drop_target_register(DND_FILES)
self.filePaths_musicFile_Button.drop_target_register(DND_FILES)
self.filePaths_musicFile_Entry.drop_target_register(DND_FILES)
self.filePaths_saveTo_Button.dnd_bind('<<Drop>>',
lambda e: drop(e, accept_mode='folder'))
self.filePaths_saveTo_Entry.dnd_bind('<<Drop>>',
lambda e: drop(e, accept_mode='folder'))
self.filePaths_musicFile_Button.dnd_bind('<<Drop>>',
lambda e: drop(e, accept_mode='files'))
self.filePaths_musicFile_Entry.dnd_bind('<<Drop>>',
lambda e: drop(e, accept_mode='files'))
def place_widgets(self):
"""Place main widgets"""
self.title_Label.place(x=-2, y=-2)
self.filePaths_Frame.place(x=10, y=155, width=-20, height=self.FILEPATHS_HEIGHT,
relx=0, rely=0, relwidth=1, relheight=0)
self.options_Frame.place(x=25, y=250, width=-50, height=self.OPTIONS_HEIGHT,
relx=0, rely=0, relwidth=1, relheight=0)
self.conversion_Button.place(x=10, y=self.IMAGE_HEIGHT + self.FILEPATHS_HEIGHT + self.OPTIONS_HEIGHT + self.PADDING*2, width=-20 - 40, height=self.CONVERSIONBUTTON_HEIGHT,
relx=0, rely=0, relwidth=1, relheight=0)
self.refresh_Button.place(x=-10 - 35, y=self.IMAGE_HEIGHT + self.FILEPATHS_HEIGHT + self.OPTIONS_HEIGHT + self.PADDING*2, width=35, height=self.CONVERSIONBUTTON_HEIGHT,
relx=1, rely=0, relwidth=0, relheight=0)
self.command_Text.place(x=15, y=self.IMAGE_HEIGHT + self.FILEPATHS_HEIGHT + self.OPTIONS_HEIGHT + self.CONVERSIONBUTTON_HEIGHT + self.PADDING*3, width=-30, height=self.COMMAND_HEIGHT,
relx=0, rely=0, relwidth=1, relheight=0)
self.progressbar.place(x=25, y=self.IMAGE_HEIGHT + self.FILEPATHS_HEIGHT + self.OPTIONS_HEIGHT + self.CONVERSIONBUTTON_HEIGHT + self.COMMAND_HEIGHT + self.PADDING*4, width=-50, height=self.PROGRESS_HEIGHT,
relx=0, rely=0, relwidth=1, relheight=0)
def fill_filePaths_Frame(self):
"""Fill Frame with neccessary widgets"""
# -Create Widgets-
# Save To Option
self.filePaths_saveTo_Button = ttk.Button(master=self.filePaths_Frame,
text='Save to',
command=self.open_export_filedialog)
self.filePaths_saveTo_Entry = ttk.Entry(master=self.filePaths_Frame,
textvariable=self.exportPath_var,
state=tk.DISABLED
)
# Select Music Files Option
self.filePaths_musicFile_Button = ttk.Button(master=self.filePaths_Frame,
text='Select Your Audio File(s)',
command=self.open_file_filedialog)
self.filePaths_musicFile_Entry = ttk.Entry(master=self.filePaths_Frame,
textvariable=self.inputPathsEntry_var,
state=tk.DISABLED
)
# -Place Widgets-
# Save To Option
self.filePaths_saveTo_Button.place(x=0, y=5, width=0, height=-10,
relx=0, rely=0, relwidth=0.3, relheight=0.5)
self.filePaths_saveTo_Entry.place(x=10, y=7, width=-20, height=-14,
relx=0.3, rely=0, relwidth=0.7, relheight=0.5)
# Select Music Files Option
self.filePaths_musicFile_Button.place(x=0, y=5, width=0, height=-10,
relx=0, rely=0.5, relwidth=0.4, relheight=0.5)
self.filePaths_musicFile_Entry.place(x=10, y=7, width=-20, height=-14,
relx=0.4, rely=0.5, relwidth=0.6, relheight=0.5)
def fill_options_Frame(self):
"""Fill Frame with neccessary widgets"""
# -Create Widgets-
# -Column 1-
# GPU Selection
self.options_gpu_Checkbutton = ttk.Checkbutton(master=self.options_Frame,
text='GPU Conversion',
variable=self.gpuConversion_var,
)
# Postprocessing
self.options_post_Checkbutton = ttk.Checkbutton(master=self.options_Frame,
text='Post-Process',
variable=self.postprocessing_var,
)
# TTA
self.options_tta_Checkbutton = ttk.Checkbutton(master=self.options_Frame,
text='TTA',
variable=self.tta_var,
)
# Save Image
self.options_image_Checkbutton = ttk.Checkbutton(master=self.options_Frame,
text='Output Image',
variable=self.outputImage_var,
)
self.options_modelFolder_Checkbutton = ttk.Checkbutton(master=self.options_Frame,
text='Model Test Mode',
variable=self.modelFolder_var,
)
# -Column 2-
# WINDOW SIZE
self.options_winSize_Label = tk.Label(master=self.options_Frame,
text='Window Size', anchor=tk.CENTER,
background='#404040', font=self.font, foreground='white', relief="groove")
self.options_winSize_Optionmenu = ttk.OptionMenu(self.options_Frame,
self.winSize_var,
None, '320', '512','1024')
# AGG
self.options_agg_Entry = ttk.Entry(master=self.options_Frame,
textvariable=self.agg_var, justify='center')
self.options_agg_Label = tk.Label(master=self.options_Frame,
text='Aggression Setting',
background='#404040', font=self.font, foreground='white', relief="groove")
# AI model
# self.options_aiModel_Label = tk.Label(master=self.options_Frame,
# text='Choose AI Engine', anchor=tk.CENTER,
# background='#63605f', font=self.font, foreground='white', relief="sunken")
# self.options_aiModel_Optionmenu = ttk.OptionMenu(self.options_Frame,
# self.aiModel_var,
# None, 'v5')
# "Save to", "Select Your Audio File(s)"", and "Start Conversion" Button Style
s = ttk.Style()
s.configure('TButton', background='blue', foreground='black', font=('Microsoft JhengHei', '9', 'bold'), relief="groove")
# -Column 3-
# Choose Instrumental Model
self.options_instrumentalModel_Label = tk.Label(master=self.options_Frame,
text='Choose Main Model',
background='#404040', font=self.font, foreground='white', relief="groove")
self.options_instrumentalModel_Optionmenu = ttk.OptionMenu(self.options_Frame,
self.instrumentalModel_var)
# Add New Model Button
self.options_model_Button = ttk.Button(master=self.options_Frame,
text='Open Export Directory',
style="Bold.TButton",
command=self.open_newModel_filedialog)
# -Place Widgets-
# -Column 1-
self.options_gpu_Checkbutton.place(x=0, y=0, width=0, height=0,
relx=0, rely=0, relwidth=1/3, relheight=1/self.COL1_ROWS)
self.options_post_Checkbutton.place(x=0, y=0, width=0, height=0,
relx=0, rely=1/self.COL1_ROWS, relwidth=1/3, relheight=1/self.COL1_ROWS)
self.options_tta_Checkbutton.place(x=0, y=0, width=0, height=0,
relx=0, rely=2/self.COL1_ROWS, relwidth=1/3, relheight=1/self.COL1_ROWS)
self.options_image_Checkbutton.place(x=0, y=0, width=0, height=0,
relx=0, rely=3/self.COL1_ROWS, relwidth=1/3, relheight=1/self.COL1_ROWS)
self.options_modelFolder_Checkbutton.place(x=0, y=0, width=0, height=0,
relx=0, rely=4/self.COL1_ROWS, relwidth=1/3, relheight=1/self.COL1_ROWS)
# -Column 2-
self.options_instrumentalModel_Label.place(x=-15, y=6, width=0, height=-10,
relx=1/3, rely=0/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
self.options_instrumentalModel_Optionmenu.place(x=-15, y=6, width=0, height=-10,
relx=1/3, rely=1/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
self.options_model_Button.place(x=0, y=0, width=-30, height=-8,
relx=1/3, rely=3/self.COL3_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# -Column 3-
# WINDOW
self.options_winSize_Label.place(x=35, y=6, width=-40, height=-10,
relx=2/3, rely=0, relwidth=1/3, relheight=1/self.COL3_ROWS)
self.options_winSize_Optionmenu.place(x=80, y=6, width=-133, height=-10,
relx=2/3, rely=1/self.COL3_ROWS, relwidth=1/3, relheight=1/self.COL3_ROWS)
# AGG
self.options_agg_Label.place(x=35, y=6, width=-40, height=-10,
relx=2/3, rely=2/self.COL3_ROWS, relwidth=1/3, relheight=1/self.COL3_ROWS)
self.options_agg_Entry.place(x=80, y=6, width=-133, height=-10,
relx=2/3, rely=3/self.COL3_ROWS, relwidth=1/3, relheight=1/self.COL3_ROWS)
# AI model
# self.options_aiModel_Label.place(x=5, y=-5, width=-30, height=-8,
# relx=1/3, rely=5/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# self.options_aiModel_Optionmenu.place(x=5, y=-5, width=-30, height=-8,
# relx=1/3, rely=6/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# Model deselect
# self.aiModel_var.trace_add('write',
# lambda *args: self.deselect_models())
# Opening filedialogs
def open_file_filedialog(self):
"""Make user select music files"""
if self.lastDir is not None:
if not os.path.isdir(self.lastDir):
self.lastDir = None
paths = tk.filedialog.askopenfilenames(
parent=self,
title=f'Select Music Files',
initialfile='',
initialdir=self.lastDir,
)
if paths: # Path selected
self.inputPaths = paths
self.update_inputPaths()
self.lastDir = os.path.dirname(paths[0])
def open_export_filedialog(self):
"""Make user select a folder to export the converted files in"""
path = tk.filedialog.askdirectory(
parent=self,
title=f'Select Folder',)
if path: # Path selected
self.exportPath_var.set(path)
def open_newModel_filedialog(self):
"""Let user paste a ".pth" model to use for the vocal seperation"""
filename = self.exportPath_var.get()
if sys.platform == "win32":
os.startfile(filename)
else:
opener = "open" if sys.platform == "darwin" else "xdg-open"
subprocess.call([opener, filename])
def start_conversion(self):
"""
Start the conversion for all the given mp3 and wav files
"""
# -Get all variables-
export_path = self.exportPath_var.get()
input_paths = self.inputPaths
instrumentalModel_path = self.instrumentalLabel_to_path[self.instrumentalModel_var.get()] # nopep8
# Get constants
instrumental = self.instrumentalModel_var.get()
try:
if [bool(instrumental)].count(True) == 2: #CHECKTHIS
window_size = DEFAULT_DATA['window_size']
agg = DEFAULT_DATA['agg']
else:
window_size = int(self.winSize_var.get())
agg = int(self.agg_var.get())
except ValueError: # Non integer was put in entry box
tk.messagebox.showwarning(master=self,
title='Invalid Input',
message='Please make sure you only input integer numbers!')
return
except SyntaxError: # Non integer was put in entry box
tk.messagebox.showwarning(master=self,
title='Invalid Music File',
message='You have selected an invalid music file!\nPlease make sure that your files still exist and ends with either ".mp3", ".mp4", ".m4a", ".flac", ".wav"')
return
# -Check for invalid inputs-
for path in input_paths:
if not os.path.isfile(path):
tk.messagebox.showwarning(master=self,
title='Invalid Music File',
message='You have selected an invalid music file! Please make sure that the file still exists!',
detail=f'File path: {path}')
return
if not os.path.isdir(export_path):
tk.messagebox.showwarning(master=self,
title='Invalid Export Directory',
message='You have selected an invalid export directory!\nPlease make sure that your directory still exists!')
return
# if self.aiModel_var.get() == 'v4':
# inference = inference_v4
# elif self.aiModel_var.get() == 'v5':
# inference = inference_v5
# else:
# raise TypeError('This error should not occur.')
inference = inference_v5
# -Run the algorithm-
threading.Thread(target=inference.main,
kwargs={
# Paths
'input_paths': input_paths,
'export_path': export_path,
# Processing Options
'gpu': 0 if self.gpuConversion_var.get() else -1,
'postprocess': self.postprocessing_var.get(),
'tta': self.tta_var.get(), # not needed for v2
'output_image': self.outputImage_var.get(),
# Models
'instrumentalModel': instrumentalModel_path,
'vocalModel': '', # Always not needed
'useModel': 'instrumental', # Always instrumental
# Model Folder
'modelFolder': self.modelFolder_var.get(),
# Constants
'window_size': window_size,
'agg': agg,
# Other Variables (Tkinter)
'window': self,
'text_widget': self.command_Text,
'button_widget': self.conversion_Button,
'progress_var': self.progress_var,
},
daemon=True
).start()
# Models
def update_inputPaths(self):
"""Update the music file entry"""
if self.inputPaths:
# Non-empty Selection
text = '; '.join(self.inputPaths)
else:
# Empty Selection
text = ''
self.inputPathsEntry_var.set(text)
def update_loop(self):
"""Update the dropdown menu"""
self.update_available_models()
self.after(3000, self.update_loop)
def update_available_models(self):
"""
Loop through every model (.pth) in the models directory
and add to the select your model list
"""
#temp_instrumentalModels_dir = os.path.join(instrumentalModels_dir, self.aiModel_var.get(), 'Main Models') # nopep8
temp_instrumentalModels_dir = os.path.join(instrumentalModels_dir, 'Main Models') # nopep8
# Instrumental models
new_InstrumentalModels = os.listdir(temp_instrumentalModels_dir)
if new_InstrumentalModels != self.lastInstrumentalModels:
self.instrumentalLabel_to_path.clear()
self.options_instrumentalModel_Optionmenu['menu'].delete(0, 'end')
for file_name in new_InstrumentalModels:
if file_name.endswith('.pth'):
# Add Radiobutton to the Options Menu
self.options_instrumentalModel_Optionmenu['menu'].add_radiobutton(label=file_name,
command=tk._setit(self.instrumentalModel_var, file_name))
# Link the files name to its absolute path
self.instrumentalLabel_to_path[file_name] = os.path.join(temp_instrumentalModels_dir, file_name) # nopep8
self.lastInstrumentalModels = new_InstrumentalModels
def update_states(self):
"""
Vary the states for all widgets based
on certain selections
"""
# Models
# self.options_instrumentalModel_Label.configure(foreground='#000')
# self.options_instrumentalModel_Optionmenu.configure(state=tk.NORMAL) # nopep8
# if self.aiModel_var.get() == 'v5':
# self.options_tta_Checkbutton.configure(state=tk.NORMAL)
# self.options_agg_Label.place(x=5, y=-5, width=-30, height=-8,
# relx=1/3, rely=3/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# self.options_agg_Entry.place(x=5, y=-4, width=-30, height=-8,
# relx=1/3, rely=4/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# else:
# self.options_tta_Checkbutton.configure(state=tk.NORMAL)
# self.options_agg_Label.place(x=5, y=-5, width=-30, height=-8,
# relx=1/3, rely=3/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
# self.options_agg_Entry.place(x=5, y=-4, width=-30, height=-8,
# relx=1/3, rely=4/self.COL2_ROWS, relwidth=1/3, relheight=1/self.COL2_ROWS)
self.update_inputPaths()
def deselect_models(self):
"""
Run this method on version change
"""
if self.aiModel_var.get() == self.last_aiModel:
return
else:
self.last_aiModel = self.aiModel_var.get()
self.instrumentalModel_var.set('')
self.winSize_var.set(DEFAULT_DATA['window_size'])
self.agg_var.set(DEFAULT_DATA['agg'])
self.update_available_models()
self.update_states()
def restart(self):
"""
Restart the application after asking for confirmation
"""
save = tk.messagebox.askyesno(title='Confirmation',
message='The application will restart. Do you want to save the data?')
if save:
self.save_values()
subprocess.Popen(f'python "{__file__}"', shell=True)
exit()
def save_values(self):
"""
Save the data of the application
"""
# Get constants
instrumental = self.instrumentalModel_var.get()
if [bool(instrumental)].count(True) == 2: #Checkthis
window_size = DEFAULT_DATA['window_size']
agg = DEFAULT_DATA['agg']
else:
window_size = self.winSize_var.get()
agg = self.agg_var.get()
# -Save Data-
save_data(data={
'exportPath': self.exportPath_var.get(),
'inputPaths': self.inputPaths,
'gpu': self.gpuConversion_var.get(),
'postprocess': self.postprocessing_var.get(),
'tta': self.tta_var.get(),
'output_image': self.outputImage_var.get(),
'window_size': window_size,
'agg': agg,
'useModel': 'instrumental',
'lastDir': self.lastDir,
'modelFolder': self.modelFolder_var.get(),
'modelInstrumentalLabel': self.instrumentalModel_var.get(),
#'aiModel': self.aiModel_var.get(),
})
self.destroy()
if __name__ == "__main__":
root = MainWindow()
root.mainloop()

440
inference_v5.py Normal file
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import pprint
import argparse
import os
import importlib
import cv2
import librosa
import math
import numpy as np
import soundfile as sf
from tqdm import tqdm
from lib_v5 import dataset
from lib_v5 import spec_utils
from lib_v5.model_param_init import ModelParameters
import torch
# Command line text parsing and widget manipulation
from collections import defaultdict
import tkinter as tk
import traceback # Error Message Recent Calls
import time # Timer
class VocalRemover(object):
def __init__(self, data, text_widget: tk.Text):
self.data = data
self.text_widget = text_widget
self.models = defaultdict(lambda: None)
self.devices = defaultdict(lambda: None)
self._load_models()
# self.offset = model.offset
def _load_models(self):
self.text_widget.write('Loading models...\n') # nopep8 Write Command Text
nn_arch_sizes = [
31191, # default
33966, 123821, 123812, 537238 # custom
]
global args
global model_params_d
p = argparse.ArgumentParser()
p.add_argument('--paramone', type=str, default='lib_v5/modelparams/4band_44100.json')
p.add_argument('--paramtwo', type=str, default='lib_v5/modelparams/4band_v2.json')
p.add_argument('--paramthree', type=str, default='lib_v5/modelparams/3band_44100_msb2.json')
p.add_argument('--paramfour', type=str, default='lib_v5/modelparams/4band_v2_sn.json')
p.add_argument('--aggressiveness',type=float, default=data['agg']/100)
p.add_argument('--nn_architecture', type=str, choices= ['auto'] + list('{}KB'.format(s) for s in nn_arch_sizes), default='auto')
p.add_argument('--high_end_process', type=str, default='mirroring')
args = p.parse_args()
if 'auto' == args.nn_architecture:
model_size = math.ceil(os.stat(data['instrumentalModel']).st_size / 1024)
args.nn_architecture = '{}KB'.format(min(nn_arch_sizes, key=lambda x:abs(x-model_size)))
nets = importlib.import_module('lib_v5.nets' + f'_{args.nn_architecture}'.replace('_{}KB'.format(nn_arch_sizes[0]), ''), package=None)
ModelName=(data['instrumentalModel'])
ModelParam1="4BAND_44100"
ModelParam2="4BAND_44100_B"
ModelParam3="MSB2"
ModelParam4="4BAND_44100_SN"
if ModelParam1 in ModelName:
model_params_d=args.paramone
if ModelParam2 in ModelName:
model_params_d=args.paramtwo
if ModelParam3 in ModelName:
model_params_d=args.paramthree
if ModelParam4 in ModelName:
model_params_d=args.paramfour
print(model_params_d)
mp = ModelParameters(model_params_d)
# -Instrumental-
if os.path.isfile(data['instrumentalModel']):
device = torch.device('cpu')
model = nets.CascadedASPPNet(mp.param['bins'] * 2)
model.load_state_dict(torch.load(self.data['instrumentalModel'],
map_location=device))
if torch.cuda.is_available() and self.data['gpu'] >= 0:
device = torch.device('cuda:{}'.format(self.data['gpu']))
model.to(device)
self.models['instrumental'] = model
self.devices['instrumental'] = device
self.text_widget.write('Done!\n')
def _execute(self, X_mag_pad, roi_size, n_window, device, model, aggressiveness):
model.eval()
with torch.no_grad():
preds = []
for i in tqdm(range(n_window)):
start = i * roi_size
X_mag_window = X_mag_pad[None, :, :, start:start + self.data['window_size']]
X_mag_window = torch.from_numpy(X_mag_window).to(device)
pred = model.predict(X_mag_window, aggressiveness)
pred = pred.detach().cpu().numpy()
preds.append(pred[0])
pred = np.concatenate(preds, axis=2)
return pred
def preprocess(self, X_spec):
X_mag = np.abs(X_spec)
X_phase = np.angle(X_spec)
return X_mag, X_phase
def inference(self, X_spec, device, model, aggressiveness):
X_mag, X_phase = self.preprocess(X_spec)
coef = X_mag.max()
X_mag_pre = X_mag / coef
n_frame = X_mag_pre.shape[2]
pad_l, pad_r, roi_size = dataset.make_padding(n_frame,
self.data['window_size'], model.offset)
n_window = int(np.ceil(n_frame / roi_size))
X_mag_pad = np.pad(
X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode='constant')
pred = self._execute(X_mag_pad, roi_size, n_window,
device, model, aggressiveness)
pred = pred[:, :, :n_frame]
return pred * coef, X_mag, np.exp(1.j * X_phase)
def inference_tta(self, X_spec, device, model, aggressiveness):
X_mag, X_phase = self.preprocess(X_spec)
coef = X_mag.max()
X_mag_pre = X_mag / coef
n_frame = X_mag_pre.shape[2]
pad_l, pad_r, roi_size = dataset.make_padding(n_frame,
self.data['window_size'], model.offset)
n_window = int(np.ceil(n_frame / roi_size))
X_mag_pad = np.pad(
X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode='constant')
pred = self._execute(X_mag_pad, roi_size, n_window,
device, model, aggressiveness)
pred = pred[:, :, :n_frame]
pad_l += roi_size // 2
pad_r += roi_size // 2
n_window += 1
X_mag_pad = np.pad(
X_mag_pre, ((0, 0), (0, 0), (pad_l, pad_r)), mode='constant')
pred_tta = self._execute(X_mag_pad, roi_size, n_window,
device, model, aggressiveness)
pred_tta = pred_tta[:, :, roi_size // 2:]
pred_tta = pred_tta[:, :, :n_frame]
return (pred + pred_tta) * 0.5 * coef, X_mag, np.exp(1.j * X_phase)
data = {
# Paths
'input_paths': None,
'export_path': None,
# Processing Options
'gpu': -1,
'postprocess': True,
'tta': True,
'output_image': True,
# Models
'instrumentalModel': None,
'useModel': None,
# Constants
'window_size': 384,
'agg': 10
}
default_window_size = data['window_size']
default_agg = data['agg']
def update_progress(progress_var, total_files, file_num, step: float = 1):
"""Calculate the progress for the progress widget in the GUI"""
base = (100 / total_files)
progress = base * (file_num - 1)
progress += step
progress_var.set(progress)
def get_baseText(total_files, file_num):
"""Create the base text for the command widget"""
text = 'File {file_num}/{total_files} '.format(file_num=file_num,
total_files=total_files)
return text
def determineModelFolderName():
"""
Determine the name that is used for the folder and appended
to the back of the music files
"""
modelFolderName = ''
if not data['modelFolder']:
# Model Test Mode not selected
return modelFolderName
# -Instrumental-
if os.path.isfile(data['instrumentalModel']):
modelFolderName += os.path.splitext(os.path.basename(data['instrumentalModel']))[0]
if modelFolderName:
modelFolderName = '/' + modelFolderName
return modelFolderName
def main(window: tk.Wm, text_widget: tk.Text, button_widget: tk.Button, progress_var: tk.Variable,
**kwargs: dict):
def save_files(wav_instrument, wav_vocals):
"""Save output music files"""
vocal_name = '(Vocals)'
instrumental_name = '(Instrumental)'
save_path = os.path.dirname(base_name)
# Swap names if vocal model
VModel="Vocal"
if VModel in model_name:
# Reverse names
vocal_name, instrumental_name = instrumental_name, vocal_name
# Save Temp File
# For instrumental the instrumental is the temp file
# and for vocal the instrumental is the temp file due
# to reversement
sf.write(f'temp.wav',
wav_instrument, mp.param['sr'])
appendModelFolderName = modelFolderName.replace('/', '_')
# -Save files-
# Instrumental
if instrumental_name is not None:
instrumental_path = '{save_path}/{file_name}.wav'.format(
save_path=save_path,
file_name=f'{os.path.basename(base_name)}_{instrumental_name}{appendModelFolderName}',
)
sf.write(instrumental_path,
wav_instrument, mp.param['sr'])
# Vocal
if vocal_name is not None:
vocal_path = '{save_path}/{file_name}.wav'.format(
save_path=save_path,
file_name=f'{os.path.basename(base_name)}_{vocal_name}{appendModelFolderName}',
)
sf.write(vocal_path,
wav_vocals, mp.param['sr'])
data.update(kwargs)
# Update default settings
global default_window_size
global default_agg
default_window_size = data['window_size']
default_agg = data['agg']
stime = time.perf_counter()
progress_var.set(0)
text_widget.clear()
button_widget.configure(state=tk.DISABLED) # Disable Button
vocal_remover = VocalRemover(data, text_widget)
modelFolderName = determineModelFolderName()
if modelFolderName:
folder_path = f'{data["export_path"]}{modelFolderName}'
if not os.path.isdir(folder_path):
os.mkdir(folder_path)
# Separation Preperation
try:
for file_num, music_file in enumerate(data['input_paths'], start=1):
# Determine File Name
base_name = f'{data["export_path"]}{modelFolderName}/{file_num}_{os.path.splitext(os.path.basename(music_file))[0]}'
# Start Separation
model_name = os.path.basename(data[f'{data["useModel"]}Model'])
model = vocal_remover.models[data['useModel']]
device = vocal_remover.devices[data['useModel']]
# -Get text and update progress-
base_text = get_baseText(total_files=len(data['input_paths']),
file_num=file_num)
progress_kwargs = {'progress_var': progress_var,
'total_files': len(data['input_paths']),
'file_num': file_num}
update_progress(**progress_kwargs,
step=0)
mp = ModelParameters(model_params_d)
# -Go through the different steps of seperation-
# Wave source
text_widget.write(base_text + 'Loading wave source...\n')
X_wave, y_wave, X_spec_s, y_spec_s = {}, {}, {}, {}
bands_n = len(mp.param['band'])
for d in range(bands_n, 0, -1):
bp = mp.param['band'][d]
if d == bands_n: # high-end band
X_wave[d], _ = librosa.load(
music_file, bp['sr'], False, dtype=np.float32, res_type=bp['res_type'])
if X_wave[d].ndim == 1:
X_wave[d] = np.asarray([X_wave[d], X_wave[d]])
else: # lower bands
X_wave[d] = librosa.resample(X_wave[d+1], mp.param['band'][d+1]['sr'], bp['sr'], res_type=bp['res_type'])
# Stft of wave source
X_spec_s[d] = spec_utils.wave_to_spectrogram_mt(X_wave[d], bp['hl'], bp['n_fft'], mp.param['mid_side'],
mp.param['mid_side_b2'], mp.param['reverse'])
if d == bands_n and args.high_end_process != 'none':
input_high_end_h = (bp['n_fft']//2 - bp['crop_stop']) + (mp.param['pre_filter_stop'] - mp.param['pre_filter_start'])
input_high_end = X_spec_s[d][:, bp['n_fft']//2-input_high_end_h:bp['n_fft']//2, :]
text_widget.write(base_text + 'Done!\n')
update_progress(**progress_kwargs,
step=0.1)
text_widget.write(base_text + 'Stft of wave source...\n')
X_spec_m = spec_utils.combine_spectrograms(X_spec_s, mp)
del X_wave, X_spec_s
if data['tta']:
pred, X_mag, X_phase = vocal_remover.inference_tta(X_spec_m,
device,
model, {'value': args.aggressiveness,'split_bin': mp.param['band'][1]['crop_stop']})
else:
pred, X_mag, X_phase = vocal_remover.inference(X_spec_m,
device,
model, {'value': args.aggressiveness,'split_bin': mp.param['band'][1]['crop_stop']})
text_widget.write(base_text + 'Done!\n')
update_progress(**progress_kwargs,
step=0.6)
# Postprocess
if data['postprocess']:
text_widget.write(base_text + 'Post processing...\n')
pred_inv = np.clip(X_mag - pred, 0, np.inf)
pred = spec_utils.mask_silence(pred, pred_inv)
text_widget.write(base_text + 'Done!\n')
update_progress(**progress_kwargs,
step=0.65)
# Inverse stft
text_widget.write(base_text + 'Inverse stft of instruments and vocals...\n') # nopep8
y_spec_m = pred * X_phase
v_spec_m = X_spec_m - y_spec_m
if args.high_end_process.startswith('mirroring'):
input_high_end_ = spec_utils.mirroring(args.high_end_process, y_spec_m, input_high_end, mp)
wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, mp, input_high_end_h, input_high_end_)
else:
wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, mp)
if args.high_end_process.startswith('mirroring'):
input_high_end_ = spec_utils.mirroring(args.high_end_process, v_spec_m, input_high_end, mp)
wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, mp, input_high_end_h, input_high_end_)
else:
wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, mp)
text_widget.write(base_text + 'Done!\n')
update_progress(**progress_kwargs,
step=0.7)
# Save output music files
text_widget.write(base_text + 'Saving Files...\n')
save_files(wav_instrument, wav_vocals)
text_widget.write(base_text + 'Done!\n')
update_progress(**progress_kwargs,
step=0.8)
# Save output image
if data['output_image']:
with open('{}_Instruments.jpg'.format(base_name), mode='wb') as f:
image = spec_utils.spectrogram_to_image(y_spec_m)
_, bin_image = cv2.imencode('.jpg', image)
bin_image.tofile(f)
with open('{}_Vocals.jpg'.format(base_name), mode='wb') as f:
image = spec_utils.spectrogram_to_image(v_spec_m)
_, bin_image = cv2.imencode('.jpg', image)
bin_image.tofile(f)
text_widget.write(base_text + 'Completed Seperation!\n\n')
except Exception as e:
traceback_text = ''.join(traceback.format_tb(e.__traceback__))
message = f'Traceback Error: "{traceback_text}"\n{type(e).__name__}: "{e}"\nFile: {music_file}\nPlease contact the creator and attach a screenshot of this error with the file and settings that caused it!'
tk.messagebox.showerror(master=window,
title='Untracked Error',
message=message)
print(traceback_text)
print(type(e).__name__, e)
print(message)
progress_var.set(0)
button_widget.configure(state=tk.NORMAL) # Enable Button
return
os.remove('temp.wav')
progress_var.set(0)
text_widget.write(f'Conversion(s) Completed and Saving all Files!\n')
text_widget.write(f'Time Elapsed: {time.strftime("%H:%M:%S", time.gmtime(int(time.perf_counter() - stime)))}') # nopep8
torch.cuda.empty_cache()
button_widget.configure(state=tk.NORMAL) # Enable Button

8
requirements.txt Normal file
View File

@ -0,0 +1,8 @@
Pillow
tqdm==4.45.0
librosa==0.7.2
opencv-python
numba==0.48.0
numpy==1.19.3
SoundFile
soundstretch