Upload app.py

app.py

@@ -161,7 +161,7 @@ for dirpath, dirnames, filenames in os.walk("./N/"):
     for filename in filenames:
         modelPaths.append(os.path.join(dirpath, filename))
 
-pap = gr.Blocks()
+app = gr.Blocks()
 with app:
     with gr.Tabs():
         with gr.TabItem(" "):  
@@ -198,9 +198,9 @@ with app:
             with gr.Row():
                  slice_db = gr.Slider(label="切片阈值(较嘈杂时-30，保留呼吸声时-50)",maximum=-30, minimum=-70, step=1, value=-40)                              
                  vc_transform = gr.Slider(label="变调（整数，可以正负，半音数量，升高八度就是12）",maximum=16, minimum=-16, step=1, value=0)                       
-            f0_predictor = gr.Radio(label=base64.b64decode( b'ZjDpooTmtYvlmago5aaC6YGH5ZOR6Z+z5Y+v5Lul5bCd6K+V5pu05o2iZjAp5Yet5bmy5aOw5bmy5YeA56iL5bqm6YCJ5oup44CC5o6o6I2QZmNwZeWSjHJtdnBl' ).decode(), choices=["pm","dio","harvest","fcpe","rmvpe"], value="fcpe")
+            f0_predictor = gr.Radio(label="f0预测器(如遇哑音可以尝试更换f0)凭干声干净程度选择。推荐fcpe和rmvpe", choices=["pm","dio","harvest","fcpe","rmvpe"], value="fcpe")
             with gr.Row():    
-                cluster_ratio = gr.Number(label="聚类模型混合比例，0-1之间，默认为0不启用聚类，能提升音色相似度，但会导致咬字下降（如果使用建议0.5左右）", value=0)#聚
+                cluster_ratio = gr.Slider(label="聚类模型混合比例，0-1之间，默认为0不启用聚类，能提升音色相似度，但会导致咬字下降（如果使用建议0.5左右）",maximum=0, minimum=1, step=0.1, value=0)   
                 output_format = gr.Radio(label=base64.b64decode( b'6Z+z6aKR6L6T5Ye65qC85byPKE1QM+S8muWvvOiHtOaXtumXtOi9tOWkmjI3bXMs6ZyA5ZCI5oiQ6K+36YCJZmxhYyk=' ).decode(), choices=["flac", "mp3"], value = "mp3")#格式
             vc_submit = gr.Button("音频转换", variant="primary")