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6
UVR.py
6
UVR.py
@ -78,7 +78,7 @@ def get_execution_time(function, name):
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time_difference = end - start
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print(f'{name} Execution Time: ', time_difference)
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PREVIOUS_PATCH_WIN = 'UVR_Patch_9_25_23_2_1'
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PREVIOUS_PATCH_WIN = 'UVR_Patch_10_6_23_4_27'
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is_dnd_compatible = True
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banner_placement = -2
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@ -108,7 +108,7 @@ elif OPERATING_SYSTEM=="Windows":
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is_macos = False
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right_click_button = '<Button-3>'
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application_extension = ".exe"
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def right_click_release_linux(window, top_win=None):
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if OPERATING_SYSTEM=="Linux":
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root.bind('<Button-1>', lambda e:window.destroy())
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@ -3228,7 +3228,7 @@ class MainWindow(TkinterDnD.Tk if is_dnd_compatible else tk.Tk):
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self.app_update_button = ttk.Button(settings_menu_main_Frame, textvariable=self.app_update_button_Text_var, width=SETTINGS_BUT_WIDTH-2, command=lambda:self.pop_up_update_confirmation())
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self.app_update_button.grid(pady=MENU_PADDING_1)
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self.app_update_status_Label = tk.Label(settings_menu_main_Frame, textvariable=self.app_update_status_Text_var, font=(MAIN_FONT_NAME, f"{FONT_SIZE_4}"), width=UPDATE_LABEL_WIDTH, justify="center", relief="ridge", fg="#13849f")
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self.app_update_status_Label = tk.Label(settings_menu_main_Frame, textvariable=self.app_update_status_Text_var, padx=3, pady=3, font=(MAIN_FONT_NAME, f"{FONT_SIZE_4}"), width=UPDATE_LABEL_WIDTH, justify="center", relief="ridge", fg="#13849f")
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self.app_update_status_Label.grid(pady=20)
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donate_Button = ttk.Button(settings_menu_main_Frame, image=self.donate_img, command=lambda:webbrowser.open_new_tab(DONATE_LINK_BMAC))
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41
separate.py
41
separate.py
@ -117,7 +117,7 @@ class SeperateAttributes:
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self.main_model_primary = main_model_primary
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self.ensemble_primary_stem = model_data.ensemble_primary_stem
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self.is_multi_stem_ensemble = model_data.is_multi_stem_ensemble
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self.is_gpu = False
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self.is_mps = False
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self.is_deverb = True
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self.DENOISER_MODEL = model_data.DENOISER_MODEL
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self.DEVERBER_MODEL = model_data.DEVERBER_MODEL
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@ -137,6 +137,8 @@ class SeperateAttributes:
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self.stem_path_init = os.path.join(self.export_path, f'{self.audio_file_base}_({self.secondary_stem}).wav')
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self.deverb_vocal_opt = model_data.deverb_vocal_opt
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self.is_save_vocal_only = model_data.is_save_vocal_only
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self.device = 'cpu'
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self.run_type = ['CPUExecutionProvider']
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if self.is_inst_only_voc_splitter or self.is_sec_bv_rebalance:
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self.is_primary_stem_only = False
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@ -145,6 +147,14 @@ class SeperateAttributes:
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if main_model_primary and self.is_multi_stem_ensemble:
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self.primary_stem, self.secondary_stem = main_model_primary, secondary_stem(main_model_primary)
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if self.is_gpu_conversion >= 0:
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if OPERATING_SYSTEM == 'Darwin' and torch.backends.mps.is_available():
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self.device = 'mps'
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self.is_mps = True
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elif torch.cuda.is_available():
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self.device = 'cuda:0'
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self.run_type = ['CUDAExecutionProvider']
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if model_data.process_method == MDX_ARCH_TYPE:
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self.is_mdx_ckpt = model_data.is_mdx_ckpt
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self.primary_model_name, self.primary_sources = self.cached_source_callback(MDX_ARCH_TYPE, model_name=self.model_basename)
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@ -170,13 +180,6 @@ class SeperateAttributes:
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self.dim_c = 4
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self.hop = 1024
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if self.is_gpu_conversion >= 0 and torch.cuda.is_available():
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self.is_gpu = True
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self.device, self.run_type = torch.device('cuda:0'), ['CUDAExecutionProvider']
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else:
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self.is_gpu = False
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self.device, self.run_type = torch.device('cpu'), ['CPUExecutionProvider']
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if model_data.process_method == DEMUCS_ARCH_TYPE:
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self.demucs_stems = model_data.demucs_stems if not main_process_method in [MDX_ARCH_TYPE, VR_ARCH_TYPE] else None
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self.secondary_model_4_stem = model_data.secondary_model_4_stem
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@ -189,7 +192,8 @@ class SeperateAttributes:
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self.is_demucs_combine_stems = model_data.is_demucs_combine_stems
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self.demucs_stem_count = model_data.demucs_stem_count
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self.pre_proc_model = model_data.pre_proc_model
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self.device = 'cpu' if self.is_mps and not self.demucs_version == DEMUCS_V4 else self.device
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self.primary_stem = model_data.ensemble_primary_stem if process_data['is_ensemble_master'] else model_data.primary_stem
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self.secondary_stem = model_data.ensemble_secondary_stem if process_data['is_ensemble_master'] else model_data.secondary_stem
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@ -218,7 +222,6 @@ class SeperateAttributes:
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self.primary_model_name, self.primary_sources = self.cached_source_callback(DEMUCS_ARCH_TYPE, model_name=self.model_basename)
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if model_data.process_method == VR_ARCH_TYPE:
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self.device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')
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self.check_label_secondary_stem_runs()
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self.primary_model_name, self.primary_sources = self.cached_source_callback(VR_ARCH_TYPE, model_name=self.model_basename)
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self.mp = model_data.vr_model_param
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@ -446,7 +449,7 @@ class SeperateMDX(SeperateAttributes):
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separator = MdxnetSet.ConvTDFNet(**model_params)
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self.model_run = separator.load_from_checkpoint(self.model_path).to(self.device).eval()
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else:
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if self.mdx_segment_size == self.dim_t:
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if self.mdx_segment_size == self.dim_t and not self.is_mps:
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ort_ = ort.InferenceSession(self.model_path, providers=self.run_type)
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self.model_run = lambda spek:ort_.run(None, {'input': spek.cpu().numpy()})[0]
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else:
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@ -600,7 +603,7 @@ class SeperateMDXC(SeperateAttributes):
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def seperate(self):
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samplerate = 44100
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sources = None
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if self.primary_model_name == self.model_basename and isinstance(self.primary_sources, tuple):
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mix, sources = self.primary_sources
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self.load_cached_sources()
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@ -786,11 +789,6 @@ class SeperateDemucs(SeperateAttributes):
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mix = prepare_mix(self.audio_file)
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if is_no_cache:
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if self.is_gpu_conversion >= 0:
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self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
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else:
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self.device = torch.device('cpu')
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if self.demucs_version == DEMUCS_V1:
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if str(self.model_path).endswith(".gz"):
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self.model_path = gzip.open(self.model_path, "rb")
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@ -1002,13 +1000,8 @@ class SeperateVR(SeperateAttributes):
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self.load_cached_sources()
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else:
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self.start_inference_console_write()
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if self.is_gpu_conversion >= 0:
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if OPERATING_SYSTEM == 'Darwin':
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device = torch.device('mps' if torch.backends.mps.is_available() else 'cpu')
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else:
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device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
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else:
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device = torch.device('cpu')
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device = self.device
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nn_arch_sizes = [
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31191, # default
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