Update app.py

Updated demo descriptor. Change to extra class

app.py

@@ -388,13 +388,13 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, title="PEEB") as demo:
     
     with gr.Column():
         title_text = gr.Markdown("# A classifier with Part-based Explainable and Editable Bottleneck (PEEB) | Demo")
-        gr.Markdown("Here is a PEEB classifier pre-trained on Bird-11K and finetuned on CUB-200 (see our [NAACL 2024 paper](https://arxiv.org/abs/2403.05297) and [code](https://github.com/anguyen8/peeb/tree/inspect_ddp)).\n The demo shows how one runs PEEB on an existing image and edit descriptors to modify the classifier (without any re-training).")
+        gr.Markdown("Here is a PEEB bird classifier pre-trained on Bird-11K and finetuned on CUB-200 (see our [NAACL 2024 paper](https://arxiv.org/abs/2403.05297) and [code](https://github.com/anguyen8/peeb/tree/inspect_ddp)).\n This demo shows how to run PEEB on an existing image and edit descriptors to update the classifier to detect one new bird species (without any re-training).")
         gr.Markdown(
             """
             Steps:
             1. **Select an image**. Then, PEEB will show its grounded explanations and the top-1 predicted label with associated softmax confidence score.
             2. **Hover mouse over text descriptors** to see the corresponding region used to match to each text descriptor.
-            3. **Edit the text under [Custom Descriptions]()** which correspond to one extra, new class (i.e. 200+1 = 201). Further editing will overwrite this class' descriptors.
+            3. **Edit the text under [Extra class]()** which correspond to one extra, new class (i.e. 200+1 = 201). Further editing will overwrite this class' descriptors.
             4. **Click on Predict** to see the grounded explanations and the top-1 label for the newly modified CUB-201 classifier.            
             """
         )
@@ -404,7 +404,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, title="PEEB") as demo:
         
         gr.Markdown("## Select an image to start!")
         image_gallery = gr.Gallery(value=IMAGE_GALLERY, label=None, preview=False, allow_preview=False, columns=10, height=250)
-        gr.Markdown("### Custom descriptions: \n The first row should be **class name: {some name};**, the name of your 201th class. \n For the 12 part descriptors, please use **;** to separate the descriptions for each part, and use the format **{part name}: {descriptions}**. \n Note: you can delete a row for some part (e.g. *nape*) completely and that part will be removed from all 201 classes in the classifier.")
+        gr.Markdown("### Extra-class descriptors: \n The first row should be **class name: {some name};**, the name of your 201th class. \n For the 12 part descriptors, please use **;** to separate the descriptions for each part, and use the format **{part name}: {descriptions}**. \n Note: you can delete a row for some part (e.g. *nape*) completely and that part will be removed from all 201 classes in the classifier.")
         
         with gr.Row():
             with gr.Column():
@@ -415,14 +415,14 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, title="PEEB") as demo:
                 with gr.Row():
                     # xclip_predict_button = gr.Button(label="Predict", value="Predict")
                     xclip_predict_button = gr.Button(value="Predict")
-                xclip_pred_label = gr.Markdown("### PEEB:")
+                xclip_pred_label = gr.Markdown("### Top-1 class:")
                 xclip_explanation = gr.HTML()
 
             with gr.Column():
                 # xclip_edit_button = gr.Button(label="Edit", value="Reset Descriptions")
                 xclip_edit_button = gr.Button(value="Reset Descriptions")
                 custom_pred_label = gr.Markdown(
-                    "### Custom Descriptions:"
+                    "### Extra class:"
                 )
                 xclip_textbox = gr.Textbox(lines=12, placeholder="Edit the descriptions here", visible=False)
                 # ai_explanation = gr.Image(type="numpy", visible=True, show_label=False, height=500)