Update app.py

app.py

@@ -59,16 +59,25 @@ def predict(image, text_input):
     _, prediction = torch.max(outputs, dim=1)
     return prediction.item()  # 1 for Malignant, 0 for Benign
 
-# Enhanced UI with color-coded prediction display
+# Enhanced UI with background image and color-coded prediction display
 with gr.Blocks(css="""
-    .benign {background-color: white; border: 1px solid lightgray; padding: 10px; border-radius: 5px;}
-    .malignant {background-color: white; border: 1px solid lightgray; padding: 10px; border-radius: 5px;}
-    .benign.correct {background-color: lightgreen;}
-    .malignant.correct {background-color: lightgreen;}
+    body { 
+        background: url('./skin_cancer_detection/melanoma.png') no-repeat center center fixed; 
+        background-size: cover;
+    }
+    .benign, .malignant { 
+        background-color: white; 
+        border: 1px solid lightgray; 
+        padding: 10px; 
+        border-radius: 5px; 
+    }
+    .benign.correct, .malignant.correct { 
+        background-color: lightgreen; 
+    }
 """) as demo:
     gr.Markdown(
         """
-        # 🩺 SKIN LESION CLASSIFICATION 
+        # 🩺 SKIN LESION CLASSIFICATION
         Upload an image of a skin lesion and provide clinical details to get a prediction of benign or malignant.
         """
     )
@@ -82,8 +91,7 @@ with gr.Blocks(css="""
             benign_output = gr.HTML("<div class='benign'>Benign</div>")
             malignant_output = gr.HTML("<div class='malignant'>Malignant</div>")
             gr.Markdown("## Example:")
-            example_image = gr.Image(value="skin_cancer_detection/Unknown-4.png")  # Provide path to an example image
-            example_text = gr.Textbox(value="consistent with resolving/involuting keratoacanthoma 67", interactive=False)
+            example_image = gr.Image(value="./skin_cancer_detection/Unknown-4.png", interactive=False)
 
     def display_prediction(image, text_input):
         prediction = predict(image, text_input)
@@ -98,3 +106,4 @@ with gr.Blocks(css="""
 demo.launch()
 
 
+