Update app.py

app.py

@@ -1,5 +1,3 @@
-
-
 import gradio as gr
 from PIL import Image
 import clipGPT
@@ -38,10 +36,6 @@ def generate_caption_vitgpt(image):
 
 with gr.Blocks() as demo:
     
-    generated_captions = {  
-    "CLIP-GPT2": "",
-    "ViT-GPT2": "",
-    }
 
     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>")
@@ -54,18 +48,23 @@ with gr.Blocks() as demo:
         "CXR194_IM-0609-1001.png",
         "CXR195_IM-0618-1001.png"
     ]
-        image = gr.Image(label="Upload Chest X-ray")
-        gr.Gallery(
-            value = sample_images,
-            label="Sample Images",
-        )
-        # sample_images_gallery = gr.Gallery(
-        #     value = sample_images,
-        #     label="Sample Images",
-        # )
+        
+    image = gr.Image(label="Upload Chest X-ray")
+    
+    gr.Gallery(
+    value = sample_images,
+    label="Sample Images",
+    )
+    
+    # sample_images_gallery = gr.Gallery(
+    #     value = sample_images,
+    #     label="Sample Images",
+    # )
+    
     with gr.Row():
         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):
@@ -75,19 +74,17 @@ with gr.Blocks() as demo:
             return generate_caption_vitgpt(img)
         else:
             return "Caption generation for this model is not yet implemented."     
-        generated_captions[model_name] = caption 
 
     with gr.Row():
-        caption1 = gr.Textbox(label="CLIP-GPT2")
-        caption2 = gr.Textbox(label="ViT-GPT2")
-        compare_button = gr.Button("Compare Captions")
+        text1 = gr.Textbox(label="Text 1")
+        text2 = gr.Textbox(label="Text 2")
+        compare_button = gr.Button("Compare Texts")
     with gr.Row():
         comparison_result = gr.Textbox(label="Comparison Result")
 
-    # Compare captions on button click
-    compare_button.click(lambda: compare_and_highlight(
-        generated_captions["CLIP-GPT2"], generated_captions["ViT-GPT2"]
-        ), [], comparison_result) 
+    # Event handlers
+    generate_button.click(predict, [image, model_choice], caption)  
+    compare_button.click(lambda: compare_and_highlight(text1.value, text2.value), [], comparison_result) 
 
 
     generate_button.click(predict, [image, model_choice], caption)  # Trigger prediction on button click