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optimize(onnx): move infer into rvc.onnx

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源文雨
2024-06-05 21:23:25 +09:00
parent 8dd06315ed
commit 6ff713c024
12 changed files with 39 additions and 127 deletions
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17
tools/onnx/onnx_inference_demo.py
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@@ -1,23 +1,24 @@
import soundfile
import librosa
from infer.lib.infer_pack.onnx_inference import OnnxRVC
from rvc.onnx.infer import RVC
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
)
model_path = "exported_model.onnx" # 模型的完整路径
vec_path = "vec-256-layer-9.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
model = OnnxRVC(
model_path, vec_path=vec_name, sr=sampling_rate, hop_size=hop_size, device="cuda"
model = RVC(
model_path, vec_path=vec_path, sr=sampling_rate, hop_size=hop_size, device="cuda"
)
audio = model.inference(wav_path, sid, f0_method=f0_method, f0_up_key=f0_up_key)
wav, sr = librosa.load(wav_path, sr=sampling_rate)
audio = model.inference(wav, sr, sid, f0_method=f0_method, f0_up_key=f0_up_key)
soundfile.write(out_path, audio, sampling_rate)