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from inference.infer_tool_grad import VitsSvc
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import gradio as gr
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import os
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class VitsGradio:
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def __init__(self):
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self.so = VitsSvc()
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self.lspk = []
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self.modelPaths = []
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for root,dirs,files in os.walk("checkpoints"):
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for dir in dirs:
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self.modelPaths.append(dir)
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with gr.Blocks() as self.Vits:
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with gr.Tab("VoiceConversion"):
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with gr.Row(visible=False) as self.VoiceConversion:
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with gr.Column():
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with gr.Row():
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with gr.Column():
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self.srcaudio = gr.Audio(label = "输入音频")
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self.btnVC = gr.Button("说话人转换")
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with gr.Column():
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self.dsid = gr.Dropdown(label = "目标角色", choices = self.lspk)
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self.tran = gr.Slider(label = "升降调", maximum = 60, minimum = -60, step = 1, value = 0)
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self.th = gr.Slider(label = "切片阈值", maximum = 32767, minimum = -32768, step = 0.1, value = -40)
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with gr.Row():
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self.VCOutputs = gr.Audio()
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self.btnVC.click(self.so.inference, inputs=[self.srcaudio,self.dsid,self.tran,self.th], outputs=[self.VCOutputs])
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with gr.Tab("SelectModel"):
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with gr.Column():
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modelstrs = gr.Dropdown(label = "模型", choices = self.modelPaths, value = self.modelPaths[0], type = "value")
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devicestrs = gr.Dropdown(label = "设备", choices = ["cpu","cuda"], value = "cpu", type = "value")
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btnMod = gr.Button("载入模型")
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btnMod.click(self.loadModel, inputs=[modelstrs,devicestrs], outputs = [self.dsid,self.VoiceConversion])
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def loadModel(self, path, device):
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self.lspk = []
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self.so.set_device(device)
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self.so.loadCheckpoint(path)
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for spk, sid in self.so.hps.spk.items():
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self.lspk.append(spk)
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VChange = gr.update(visible = True)
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SDChange = gr.update(choices = self.lspk, value = self.lspk[0])
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return [SDChange,VChange]
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grVits = VitsGradio()
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grVits.Vits.launch() |