Cool_Tools/ultimatevocalremovergui
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Anjok07 2024-11-26 14:03:18 -06:00 committed by GitHub
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3 changed files with 29 additions and 21 deletions
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13
UVR.py
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@ -526,6 +526,7 @@ class ModelData():
self.mdx_segment_size = int(root.mdx_segment_size_var.get()) self.mdx_segment_size = int(root.mdx_segment_size_var.get())
self.get_mdx_model_path() self.get_mdx_model_path()
self.get_model_hash() self.get_model_hash()
print(self.model_hash)
if self.model_hash: if self.model_hash:
self.model_hash_dir = os.path.join(MDX_HASH_DIR, f"{self.model_hash}.json") self.model_hash_dir = os.path.join(MDX_HASH_DIR, f"{self.model_hash}.json")
if is_change_def: if is_change_def:
@ -554,8 +555,11 @@ class ModelData():
if self.is_roformer and self.mdx_c_configs.training.target_instrument == VOCAL_STEM and self.is_ensemble_mode: if self.is_roformer and self.mdx_c_configs.training.target_instrument == VOCAL_STEM and self.is_ensemble_mode:
self.mdxnet_stem_select = self.ensemble_primary_stem self.mdxnet_stem_select = self.ensemble_primary_stem
if self.is_roformer and self.mdx_c_configs.training.target_instrument == INST_STEM and self.is_ensemble_mode:
self.mdxnet_stem_select = self.ensemble_primary_stem
print("self.primary_stem target", self.primary_stem) #print("self.primary_stem target", self.primary_stem)
else: else:
# If no specific target_instrument, use all instruments in the training config # If no specific target_instrument, use all instruments in the training config
@ -583,10 +587,12 @@ class ModelData():
self.check_if_karaokee_model() self.check_if_karaokee_model()
print("self.primary_stem final", self.primary_stem) #print("self.primary_stem final", self.primary_stem)
self.secondary_stem = secondary_stem(self.primary_stem) self.secondary_stem = secondary_stem(self.primary_stem)
else: else:
self.model_status = False self.model_status = False
#print("self.mdxnet_stem_select", self.mdxnet_stem_select)
if self.process_method == DEMUCS_ARCH_TYPE: if self.process_method == DEMUCS_ARCH_TYPE:
self.is_secondary_model_activated = root.demucs_is_secondary_model_activate_var.get() if not is_secondary_model else False self.is_secondary_model_activated = root.demucs_is_secondary_model_activate_var.get() if not is_secondary_model else False
@ -1217,9 +1223,6 @@ class ComboBoxEditableMenu(ttk.Combobox):
self.bind('<FocusIn>', self.focusin) self.bind('<FocusIn>', self.focusin)
self.bind('<FocusOut>', lambda e: self.var_validation(is_focus_only=True)) self.bind('<FocusOut>', lambda e: self.var_validation(is_focus_only=True))
self.bind('<MouseWheel>', lambda e: "break") self.bind('<MouseWheel>', lambda e: "break")
#self.bind('<MouseWheel>', lambda e: print("Scrolling"))
# self.bind('<Shift-MouseWheel>', lambda e: "break")
# self.bind('<Control-MouseWheel>', lambda e: "break")
if is_macos: if is_macos:
self.bind('<Enter>', lambda e:self.button_released()) self.bind('<Enter>', lambda e:self.button_released())

8
__version__.py
View File

@ -1,4 +1,4 @@
VERSION = 'v5.6.0' VERSION = 'v5.6.1'
PATCH = 'UVR_Patch_9_29_23_1_39' PATCH = 'UVR_Patch_11_25_24_1_48_BETA'
PATCH_MAC = 'UVR_Patch_9_29_23_1_39' PATCH_MAC = 'UVR_Patch_12_29_22_07_20'
PATCH_LINUX = 'UVR_Patch_9_29_23_1_39' PATCH_LINUX = 'UVR_Patch_12_29_22_07_20'

29
separate.py
View File

@ -134,9 +134,11 @@ class SeperateAttributes:
self.primary_model_primary_stem = model_data.primary_model_primary_stem self.primary_model_primary_stem = model_data.primary_model_primary_stem
self.primary_stem_native = model_data.primary_stem_native self.primary_stem_native = model_data.primary_stem_native
self.primary_stem = model_data.primary_stem # self.primary_stem = model_data.primary_stem #
print(self.primary_stem)
self.secondary_stem = model_data.secondary_stem # self.secondary_stem = model_data.secondary_stem #
self.is_invert_spec = model_data.is_invert_spec # self.is_invert_spec = model_data.is_invert_spec #
self.is_deverb_vocals = model_data.is_deverb_vocals self.is_deverb_vocals = model_data.is_deverb_vocals
self.is_target_instrument = model_data.is_target_instrument
self.is_mixer_mode = model_data.is_mixer_mode # self.is_mixer_mode = model_data.is_mixer_mode #
self.secondary_model_scale = model_data.secondary_model_scale # self.secondary_model_scale = model_data.secondary_model_scale #
self.is_demucs_pre_proc_model_inst_mix = model_data.is_demucs_pre_proc_model_inst_mix # self.is_demucs_pre_proc_model_inst_mix = model_data.is_demucs_pre_proc_model_inst_mix #
@ -172,7 +174,7 @@ class SeperateAttributes:
self.is_save_vocal_only = model_data.is_save_vocal_only self.is_save_vocal_only = model_data.is_save_vocal_only
self.device = cpu self.device = cpu
self.run_type = ['CPUExecutionProvider'] self.run_type = ['CPUExecutionProvider']
self.is_opencl = False self.is_using_opencl = False
self.device_set = model_data.device_set self.device_set = model_data.device_set
self.is_use_opencl = model_data.is_use_opencl self.is_use_opencl = model_data.is_use_opencl
#Roformer #Roformer
@ -198,6 +200,7 @@ class SeperateAttributes:
if directml_available and self.is_use_opencl: if directml_available and self.is_use_opencl:
self.device = torch_directml.device() if not device_prefix else f'{device_prefix}:{self.device_set}' self.device = torch_directml.device() if not device_prefix else f'{device_prefix}:{self.device_set}'
self.is_other_gpu = True self.is_other_gpu = True
self.is_using_opencl = True
elif cuda_available and not self.is_use_opencl: elif cuda_available and not self.is_use_opencl:
self.device = CUDA_DEVICE if not device_prefix else f'{device_prefix}:{self.device_set}' self.device = CUDA_DEVICE if not device_prefix else f'{device_prefix}:{self.device_set}'
self.run_type = ['CUDAExecutionProvider'] self.run_type = ['CUDAExecutionProvider']
@ -214,8 +217,9 @@ class SeperateAttributes:
if self.is_mdx_c: if self.is_mdx_c:
if not self.is_4_stem_ensemble: if not self.is_4_stem_ensemble:
self.primary_stem = model_data.ensemble_primary_stem if process_data['is_ensemble_master'] else model_data.primary_stem if not self.is_target_instrument:
self.secondary_stem = model_data.ensemble_secondary_stem if process_data['is_ensemble_master'] else model_data.secondary_stem self.primary_stem = model_data.ensemble_primary_stem if process_data['is_ensemble_master'] else model_data.primary_stem
self.secondary_stem = model_data.ensemble_secondary_stem if process_data['is_ensemble_master'] else model_data.secondary_stem
else: else:
self.dim_f, self.dim_t = model_data.mdx_dim_f_set, 2**model_data.mdx_dim_t_set self.dim_f, self.dim_t = model_data.mdx_dim_f_set, 2**model_data.mdx_dim_t_set
@ -286,13 +290,10 @@ class SeperateAttributes:
'aggr_correction': self.mp.param.get('aggr_correction')} 'aggr_correction': self.mp.param.get('aggr_correction')}
def check_label_secondary_stem_runs(self): def check_label_secondary_stem_runs(self):
if (self.process_data['is_ensemble_master'] and not self.is_4_stem_ensemble and not self.is_mdx_c) or (self.process_data['is_ensemble_master'] and self.is_target_instrument):
# For ensemble master that's not a 4-stem ensemble, and not mdx_c
if self.process_data['is_ensemble_master'] and not self.is_4_stem_ensemble and not self.is_mdx_c:
if self.ensemble_primary_stem != self.primary_stem: if self.ensemble_primary_stem != self.primary_stem:
self.is_primary_stem_only, self.is_secondary_stem_only = self.is_secondary_stem_only, self.is_primary_stem_only self.is_primary_stem_only, self.is_secondary_stem_only = self.is_secondary_stem_only, self.is_primary_stem_only
# For secondary models
if self.is_pre_proc_model or self.is_secondary_model: if self.is_pre_proc_model or self.is_secondary_model:
self.is_primary_stem_only = False self.is_primary_stem_only = False
self.is_secondary_stem_only = False self.is_secondary_stem_only = False
@ -695,10 +696,14 @@ class SeperateMDXC(SeperateAttributes):
if stem == VOCAL_STEM and not self.is_sec_bv_rebalance: if stem == VOCAL_STEM and not self.is_sec_bv_rebalance:
self.process_vocal_split_chain({VOCAL_STEM:stem}) self.process_vocal_split_chain({VOCAL_STEM:stem})
else: else:
print(stem_list)
if len(stem_list) == 1: if len(stem_list) == 1:
source_primary = sources source_primary = sources
else: else:
source_primary = sources[stem_list[0]] if self.is_multi_stem_ensemble and len(stem_list) == 2 else sources[self.mdxnet_stem_select] if self.is_multi_stem_ensemble or len(stem_list) == 2:
source_primary = sources[stem_list[0]]
else:
sources[self.mdxnet_stem_select]
if self.is_secondary_model_activated and self.secondary_model: if self.is_secondary_model_activated and self.secondary_model:
self.secondary_source_primary, self.secondary_source_secondary = process_secondary_model(self.secondary_model, self.secondary_source_primary, self.secondary_source_secondary = process_secondary_model(self.secondary_model,
@ -748,7 +753,7 @@ class SeperateMDXC(SeperateAttributes):
return secondary_sources return secondary_sources
def overlap_add(self, result, x, l, j, start, window): def overlap_add(self, result, x, l, j, start, window):
if self.device == 'mps': if self.device == 'mps' or self.is_other_gpu:
x = x.to(self.device) x = x.to(self.device)
result[..., start:start + l] += x[j][..., :l] * window[..., :l] result[..., start:start + l] += x[j][..., :l] * window[..., :l]
return result return result
@ -808,7 +813,7 @@ class SeperateMDXC(SeperateAttributes):
batch_len = int(mix.shape[1] / step) batch_len = int(mix.shape[1] / step)
with torch.inference_mode(): with torch.no_grad() if self.is_using_opencl else torch.inference_mode():
req_shape = (S, ) + tuple(mix.shape) req_shape = (S, ) + tuple(mix.shape)
result = torch.zeros(req_shape, dtype=torch.float32, device=device) result = torch.zeros(req_shape, dtype=torch.float32, device=device)
counter = torch.zeros(req_shape, dtype=torch.float32, device=device) counter = torch.zeros(req_shape, dtype=torch.float32, device=device)