Cool_Tools/ultimatevocalremovergui
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Anjok07 2023-09-29 01:46:13 -05:00 committed by GitHub
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1 changed files with 6 additions and 7 deletions
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separate.py
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@ -26,11 +26,9 @@ import torch
import warnings
import pydub
import soundfile as sf
import traceback
import lib_v5.mdxnet as MdxnetSet
import math
#import random
from tqdm import tqdm
from onnx import load
from onnx2pytorch import ConvertModel
@ -231,6 +229,7 @@ class SeperateAttributes:
self.batch_size = model_data.batch_size
self.window_size = model_data.window_size
self.input_high_end_h = None
self.input_high_end = None
self.post_process_threshold = model_data.post_process_threshold
self.aggressiveness = {'value': model_data.aggression_setting,
'split_bin': self.mp.param['band'][1]['crop_stop'],
@ -454,9 +453,7 @@ class SeperateMDX(SeperateAttributes):
self.model_run = ConvertModel(load(self.model_path))
self.model_run.to(self.device).eval()
self.initialize_model_settings()
self.running_inference_console_write()
self.stft = STFT(self.n_fft, self.hop, self.dim_f)
mix = prepare_mix(self.audio_file)
source = self.demix(mix)
@ -499,9 +496,11 @@ class SeperateMDX(SeperateAttributes):
self.trim = self.n_fft//2
self.chunk_size = self.hop * (self.mdx_segment_size-1)
self.gen_size = self.chunk_size-2*self.trim
self.stft = STFT(self.n_fft, self.hop, self.dim_f)
def demix(self, mix, is_match_mix=False):
self.initialize_model_settings()
org_mix = mix
tar_waves_ = []
@ -1178,14 +1177,14 @@ class SeperateVR(SeperateAttributes):
return y_spec, v_spec
def spec_to_wav(self, spec):
if self.high_end_process.startswith('mirroring'):
if self.high_end_process.startswith('mirroring') and isinstance(self.input_high_end, np.ndarray) and self.input_high_end_h:
input_high_end_ = spec_utils.mirroring(self.high_end_process, spec, self.input_high_end, self.mp)
wav = spec_utils.cmb_spectrogram_to_wave(spec, self.mp, self.input_high_end_h, input_high_end_, is_v51_model=self.is_vr_51_model)
else:
wav = spec_utils.cmb_spectrogram_to_wave(spec, self.mp, is_v51_model=self.is_vr_51_model)
return wav
def process_secondary_model(secondary_model: ModelData,
process_data,
main_model_primary_stem_4_stem=None,