Update app.py

app.py

@@ -37,20 +37,6 @@ with gr.Blocks() as demo:
     gr.HTML("<h1 style='text-align: center;'>MedViT: A Vision Transformer-Driven Method for Generating Medical Reports 🏥🤖</h1>")
     gr.HTML("<p style='text-align: center;'>You can generate captions by uploading an X-Ray and selecting a model of your choice below</p>")
 
-       
-    examples_list = [
-        ['https://imgur.com/W1pIr9b', 'Caption for image 1'],
-        ['https://imgur.com/MLJaWnf', 'Caption for image 2']
-    ]
-    examples = gr.Examples(examples_list, 
-                           inputs="image",  
-                           outputs=["image", "text"], 
-                           label="Example Images",
-                           fn=render_image  
-                       ) 
-
-    image_table = gr.Dataframe(headers=['image', 'caption'], datatype=['html', 'str'])  
-
 
     with gr.Row():
         model_choice = gr.Radio(["CLIP-GPT2", "ViT-GPT2", "ViT-CoAttention"], label="Select Model")
@@ -59,14 +45,6 @@ with gr.Blocks() as demo:
     
     caption = gr.Textbox(label="Generated Caption") 
 
-    
-    # Function to populate table rows when an example image is clicked
-    def populate_table_from_example(image_path, caption):
-        new_row = [[render_image(image_path)], [caption]]
-        image_table.append(new_row) 
-
-    examples.click(populate_table_from_example, inputs=examples, outputs=image_table)
-
 
     def predict(img, model_name):
         if model_name == "CLIP-GPT2":
@@ -81,7 +59,6 @@ with gr.Blocks() as demo:
 
     # Event handlers
     generate_button.click(predict, [image, model_choice], caption)  # Trigger prediction on button click 
-    sample_images_gallery.change(predict, [sample_images_gallery, model_choice], caption)  # Handle sample images
 
 
 demo.launch()