59 lines
2.4 KiB
Python
59 lines
2.4 KiB
Python
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import io
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import os.path
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from pathlib import Path
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import numpy as np
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import soundfile
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from infer_tools import infer_tool
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from infer_tools.infer_tool import Svc
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from utils.hparams import hparams
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def run_clip(raw_audio_path, svc_model, key, acc, use_crepe, spk_id=0, auto_key=False, units_mode=False):
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infer_tool.format_wav(raw_audio_path)
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key = svc_model.evaluate_key(raw_audio_path, key, auto_key)
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_f0_tst, _f0_pred, _audio = svc_model.infer(raw_audio_path, key=key, acc=acc, use_crepe=use_crepe, spk_id=spk_id,
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singer=not units_mode)
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if units_mode:
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out_path = io.BytesIO()
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soundfile.write(out_path, _audio, hparams["audio_sample_rate"], format='wav')
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out_path.seek(0)
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npy_path = Path(raw_audio_path).with_suffix(".npy")
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np.save(str(npy_path), svc_model.hubert.encode(out_path))
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else:
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out_path = f'./singer_data/{Path(raw_audio_path).name}'
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soundfile.write(out_path, _audio, hparams["audio_sample_rate"], 'PCM_16')
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if __name__ == '__main__':
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# 工程文件夹名，训练时用的那个
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project_name = "fox_cn"
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model_path = f'./checkpoints/{project_name}/model_ckpt_steps_370000.ckpt'
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config_path = f'./checkpoints/{project_name}/config.yaml'
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# 此脚本为批量导出短音频（30s内）使用，同时生成f0、mel供diffsinger使用。
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# 支持wav文件，放在batch文件夹下，带扩展名
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wav_paths = infer_tool.get_end_file("./batch", "wav")
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trans = -6 # 音高调整，支持正负（半音）
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spk_id = 0 # 非多人模型不改
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# 特化专用，开启此项后，仅导出变更音色的units至batch目录，其余项不输出；关闭此项则切换为对接diffsinger的套娃导出模式
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units = True
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# 自适应变调，不懂别开
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auto_key = False
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# 加速倍数
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accelerate = 10
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# 下面不动
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os.makedirs("./singer_data", exist_ok=True)
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model = Svc(project_name, config_path, hubert_gpu=True, model_path=model_path)
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count = 0
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for audio_path in wav_paths:
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count += 1
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if os.path.exists(Path(audio_path).with_suffix(".npy")) and units:
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print(f"{audio_path}:units已存在，跳过")
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continue
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run_clip(audio_path, model, trans, accelerate, spk_id=spk_id, auto_key=auto_key, use_crepe=False,
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units_mode=units)
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print(f"\r\nnum:{count}\r\ntotal process:{round(count * 100 / len(wav_paths), 2)}%\r\n")
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