import os import shutil import sys from datetime import datetime from pathlib import Path from args import mdx23c_8kfft_instvoc_hq_process_data, htdemucs_ft_process_data, uvr_mdx_net_voc_ft_process_data from download import download_model, get_model_file from gui_data.constants import VR_ARCH_TYPE, MDX_ARCH_TYPE, DEMUCS_ARCH_TYPE, ENSEMBLE_MODE, TIME_STRETCH, \ MANUAL_ENSEMBLE, MATCH_INPUTS, ALIGN_INPUTS, ALL_STEMS, DEFAULT, VOCAL_STEM, MP3_BIT_RATES, WAV, DEMUCS_2_SOURCE, \ DEMUCS_2_SOURCE_MAPPER, INST_STEM, CKPT, ONNX, MDX_POP_NFFT, secondary_stem, PRIMARY_STEM, SECONDARY_STEM from lib_v5 import spec_utils from separate import ( SeperateDemucs, SeperateMDX, SeperateMDXC, SeperateVR, # Model-related save_format, clear_gpu_cache, # Utility functions cuda_available, mps_available, # directml_available, ) def run_ensemble_models(audio_path, export_path, format=WAV, clean=True): start = datetime.now() process_datas = [mdx23c_8kfft_instvoc_hq_process_data, uvr_mdx_net_voc_ft_process_data, htdemucs_ft_process_data] # download models for process_data in process_datas: download_model(process_data['model_name']) # create folder os.makedirs(export_path, exist_ok=True) temp_export_path = os.path.join(export_path, 'uvr5_' + datetime.now().strftime("%Y-%m-%d %H:%M:%S")) os.makedirs(temp_export_path, exist_ok=True) print(f'temp_export_path', temp_export_path) instrumental_export_paths = [] vocals_export_paths = [] for process_data in process_datas: current_model = process_data['model_data'] audio_file_base = Path(audio_path).stem + '_' + current_model.model_basename process_data['export_path'] = temp_export_path process_data['audio_file_base'] = audio_file_base process_data['audio_file'] = audio_path if current_model.process_method == VR_ARCH_TYPE: seperator = SeperateVR(current_model, process_data) elif current_model.process_method == MDX_ARCH_TYPE: seperator = SeperateMDXC(current_model, process_data) if current_model.is_mdx_c else SeperateMDX( current_model, process_data) elif current_model.process_method == DEMUCS_ARCH_TYPE: seperator = SeperateDemucs(current_model, process_data, vocal_stem_path=(audio_path, audio_file_base)) else: raise Exception(f'model not found') seperator.seperate() instrumental_path = Path(temp_export_path) / f"{audio_file_base}_(Instrumental).{format.lower()}" vocals_path = Path(temp_export_path) / f"{audio_file_base}_(Vocals).{format.lower()}" instrumental_export_paths.append(str(instrumental_path)) vocals_export_paths.append(str(vocals_path)) # merge each model outputs vocals_final_path = Path(export_path) / f"{Path(audio_path).stem}.vocal.{format.lower()}" instrumental_final_path = Path(export_path) / f"{Path(audio_path).stem}.instrumental.{format.lower()}" ensemble(vocals_export_paths, vocals_final_path) ensemble(instrumental_export_paths, instrumental_final_path) if clean: shutil.rmtree(temp_export_path) print(f'instrumental_final_path', instrumental_final_path) print(f'vocals_final_path', vocals_final_path) print(f'Finished in {datetime.now() - start}') return instrumental_final_path, vocals_final_path def ensemble(stem_outputs, stem_save_path, format=WAV): algorithm = 'Average' is_normalization = True spec_utils.ensemble_inputs(stem_outputs, algorithm, is_normalization, 'PCM_16', stem_save_path, is_wave=True) save_format(stem_save_path, format, '320k') # /Users/taoluo/Downloads/test/kimk_audio_MDX23C-8KFFT-InstVoc_HQ_(Instrumental).WAV # if __name__ == '__main__': audio_file = '/Users/taoluo/Downloads/assets/audio/kimk_audio.mp3' audio_file = sys.argv[1] if not os.path.isfile(audio_file): raise FileNotFoundError(f"File {audio_file} not exist.") output_dir = os.path.dirname(audio_file) print(output_dir) run_ensemble_models(audio_file, output_dir)