Update app.py

app.py

@@ -24,29 +24,29 @@ sample_images = [
     "CXR195_IM-0618-1001.png"
 ]
 
-# Gradio interface 
 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>")
+
     with gr.Row():
-        image = gr.Image(label="Upload Chest X-ray") 
+        image = gr.Image(label="Upload Chest X-ray")
         sample_images_gallery = gr.Gallery(
-            sample_images, 
+            sample_images,
             label="Sample Images",
-        )  
-    with gr.Row():  
-        model_choice = gr.Radio(["CLIP-GPT2", "ViT-GPT2", "ViT-CoAttention"], label="Select Model")
+        )
     with gr.Row():
-        caption = gr.Textbox(label="Generated Caption") 
+        model_choice = gr.Radio(["CLIP-GPT2", "ViT-GPT2", "ViT-CoAttention"], label="Select Model")
+        generate_button = gr.Button("Generate Caption") 
+    caption = gr.Textbox(label="Generated Caption") 
 
     def predict(img, model_name):
         if model_name == "CLIP-GPT2":
-            return generate_caption_clipgpt(img)
-        # elif model_name == "ViT-GPT2":
-        #     return generate_caption_vitgpt(img)
+            return generate_caption_clipgpt(img)  
         else:
             return "Caption generation for this model is not yet implemented."
 
-    # Handle changes for both uploaded and sample images
-    image.change(predict, [image, model_choice], caption)
-    sample_images_gallery.change(predict, [sample_images_gallery, model_choice], caption)
+    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()