wehub-resource-sync
91 lines
2.9 KiB
Python
91 lines
2.9 KiB
Python
# coding=utf8
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import argparse
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import os
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import pathlib
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import sys
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root_dir = pathlib.Path(__file__).parent.parent.resolve()
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os.environ['PYTHONPATH'] = str(root_dir)
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sys.path.insert(0, str(root_dir))
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import numpy as np
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import torch
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import tqdm
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from inference.ds_acoustic import DiffSingerAcousticInfer
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from utils.infer_utils import cross_fade, save_wav
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from utils.hparams import set_hparams, hparams
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parser = argparse.ArgumentParser(description='Run DiffSinger vocoder')
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parser.add_argument('mel', type=str, help='Path to the input file')
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parser.add_argument('--exp', type=str, required=False, help='Read vocoder class and path from chosen experiment')
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parser.add_argument('--config', type=str, required=False, help='Read vocoder class and path from config file')
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parser.add_argument('--class', type=str, required=False, help='Specify vocoder class')
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parser.add_argument('--ckpt', type=str, required=False, help='Specify vocoder checkpoint path')
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parser.add_argument('--out', type=str, required=False, help='Path of the output folder')
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parser.add_argument('--title', type=str, required=False, help='Title of output file')
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args = parser.parse_args()
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mel = pathlib.Path(args.mel)
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name = mel.stem if not args.title else args.title
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config = None
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if args.exp:
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config = root_dir / 'checkpoints' / args.exp / 'config.yaml'
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elif args.config:
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config = pathlib.Path(args.config)
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else:
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assert False, 'Either argument \'--exp\' or \'--config\' should be specified.'
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sys.argv = [
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sys.argv[0],
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'--config',
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str(config)
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]
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set_hparams(print_hparams=False)
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cls = getattr(args, 'class')
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if cls:
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hparams['vocoder'] = cls
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if args.ckpt:
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hparams['vocoder_ckpt'] = args.ckpt
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out = args.out
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if args.out:
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out = pathlib.Path(args.out)
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else:
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out = mel.parent
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mel_seq = torch.load(mel)
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assert isinstance(mel_seq, list), 'Not a valid mel sequence.'
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assert len(mel_seq) > 0, 'Mel sequence is empty.'
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sample_rate = hparams['audio_sample_rate']
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infer_ins = DiffSingerAcousticInfer(load_model=False)
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def run_vocoder(path: pathlib.Path):
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result = np.zeros(0)
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current_length = 0
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for seg_mel in tqdm.tqdm(mel_seq, desc='mel segment', total=len(mel_seq)):
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seg_audio = infer_ins.run_vocoder(seg_mel['mel'].to(infer_ins.device), f0=seg_mel['f0'].to(infer_ins.device))
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seg_audio = seg_audio.squeeze(0).cpu().numpy()
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silent_length = round(seg_mel['offset'] * sample_rate) - current_length
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if silent_length >= 0:
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result = np.append(result, np.zeros(silent_length))
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result = np.append(result, seg_audio)
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else:
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result = cross_fade(result, seg_audio, current_length + silent_length)
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current_length = current_length + silent_length + seg_audio.shape[0]
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print(f'| save audio: {path}')
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save_wav(result, path, sample_rate)
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os.makedirs(out, exist_ok=True)
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try:
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run_vocoder(out / (name + '.wav'))
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except KeyboardInterrupt:
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exit(-1)
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