separate description from model name

app.py

@@ -7,6 +7,20 @@ import time
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 
+# Define model options with separate names and descriptions
+MODEL_OPTIONS = {
+    "": "Select a model",
+    "u2net": "A pre-trained model for general use cases (default)",
+    "isnet-general-use": "A new pre-trained model for general use cases",
+    "isnet-anime": "High-accuracy segmentation for anime characters",
+    "silueta": "A reduced-size version of u2net (43MB)",
+    "sam": "A pre-trained model for any use case",
+    "unet": "Lightweight version of u2net model",
+    "u2netp": "A lightweight version of u2net model",
+    "u2net_human_seg": "A pre-trained model for human segmentation",
+    "u2net_cloth_seg": "A pre-trained model for cloth parsing in human portraits",
+}
+
 def hex_to_rgba(hex_color):
     hex_color = hex_color.lstrip('#')
     if len(hex_color) == 6:
@@ -72,19 +86,12 @@ iface = gr.Interface(
     fn=remove_background,
     inputs=[
         gr.Image(type="pil"),
-        gr.ColorPicker(label="Background Color", value=None), # Background color picker
-        gr.Dropdown(choices=[
-                "",
-                "u2net (default) | A pre-trained model for general use cases",
-                "isnet-general-use | A new pre-trained model for general use cases",
-                "isnet-anime | High-accuracy segmentation for anime characters",
-                "silueta | A reduced-size version of u2net (43MB)",
-                "sam | A pre-trained model for any use case",
-                "unet | lightweight version of u2net model",
-                "u2netp | A lightweight version of u2net model",
-                "u2net_human_seg | A pre-trained model for human segmentation",
-                "u2net_cloth_seg | A pre-trained model for cloth parsing in human portraits",
-            ], label="Model Selection", value=""),
+        gr.ColorPicker(label="Background Color", value=None),
+        gr.Dropdown(choices=list(MODEL_OPTIONS.keys()),
+                    label="Model Selection",
+                    value="",
+                    type="value",
+                    info=lambda x: MODEL_OPTIONS[x] if x in MODEL_OPTIONS else ""),
         gr.Checkbox(label="Enable Alpha Matting", value=False),
         gr.Checkbox(label="Post-Process Mask (to post process the mask to get better results)", value=False),
         gr.Checkbox(label="Only Return Mask ", value=False)
@@ -93,10 +100,10 @@ iface = gr.Interface(
         gr.Image(type="pil", label="Output Image"), 
         gr.File(label="Download the output image")
     ],
-    title="Advanced Background Remover v2.2",
+    title="Advanced Background Remover v2.4",
     description="Upload an image to remove the background. Customize the result with different options, including background color, model selection, alpha matting, and more.",
     allow_flagging="never",
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()