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