Update app.py

app.py

@@ -422,7 +422,7 @@ with gr.Blocks() as demo:
                 
                 img_input = gr.ImageEditor()
                 model_select = gr.Dropdown(
-                                    ["GLEE-Lite (R50)", "GLEE-Plus (SwinL)"], value = "GLEE-Lite (R50)" , multiselect=False, label="Model",  
+                                    ["GLEE-Lite (R50)", "GLEE-Plus (SwinL)"], value = "GLEE-Plus (SwinL)" , multiselect=False, label="Model",  
                                 )
                 with gr.Row():
                     with gr.Column():
@@ -444,7 +444,14 @@ with gr.Blocks() as demo:
                         )
                     # with gr.Column(): 
                     with gr.Group():
-                        
+                        with gr.Accordion("Text based detection usage",open=False):
+                            gr.Markdown(
+                                'Press the "Detect & Segment" button directly to try the effect using the COCO category.<br />\
+                                GLEE supports three kind of object perception methods: category list, textual description, and class-agnostic.<br />\
+                                1.Select an existing category list from the "Categories" dropdown, like COCO or OBJ365, or customize your own list.<br />\
+                                2.Enter arbitrary object name in "Custom Category", or choose the expression model and describe the object in "Expression Textbox" for single object detection only.<br />\
+                                3.For class-agnostic mode, choose "Class-Agnostic" from the "Categories" dropdown.'
+                            )
                         with gr.Accordion("Interactive segmentation usage",open=False):
                             gr.Markdown(
                                 'For interactive segmentation:<br />\
@@ -452,13 +459,7 @@ with gr.Blocks() as demo:
                                     2.Point mode accepts a single point only; multiple points default to the centroid, so use boxes or scribbles for larger objects.<br />\
                                     3.After drawing, click green "√" on the right side of the image to preview the prompt visualization; the segmentation mask follows the chosen prompt colors.'
                                 )
-                        with gr.Accordion("Text based detection usage",open=False):
-                            gr.Markdown(
-                                'GLEE supports three kind of object perception methods: category list, textual description, and class-agnostic.<br />\
-                                1.Select an existing category list from the "Categories" dropdown, like COCO or OBJ365, or customize your own list.<br />\
-                                2.Enter arbitrary object name in "Custom Category", or choose the expression model and describe the object in "Expression Textbox" for single object detection only.<br />\
-                                3.For class-agnostic mode, choose "Class-Agnostic" from the "Categories" dropdown.'
-                            )
+
                         img_showbox = gr.Image(label="visual prompt area preview")