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Retrieval-based-Voice-Conve.../tools/onnx_inference_demo.py

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import soundfile
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from ..lib.infer_pack.onnx_inference import OnnxRVC
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hop_size = 512
sampling_rate = 40000 # 采样率
f0_up_key = 0 # 升降调
sid = 0 # 角色ID
f0_method = "dio" # F0提取算法
model_path = "ShirohaRVC.onnx" # 模型的完整路径
vec_name = "vec-256-layer-9" # 内部自动补齐为 f"pretrained/{vec_name}.onnx" 需要onnx的vec模型
wav_path = "123.wav" # 输入路径或ByteIO实例
out_path = "out.wav" # 输出路径或ByteIO实例
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model = OnnxRVC(
model_path, vec_path=vec_name, sr=sampling_rate, hop_size=hop_size, device="cuda"
)
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audio = model.inference(wav_path, sid, f0_method=f0_method, f0_up_key=f0_up_key)
soundfile.write(out_path, audio, sampling_rate)