Update app.py

app.py

@@ -11,6 +11,7 @@ def get_x(row):
 def get_y(row):
     return row['Buried ODD']
 
+
 # Load the models into a dictionary
 models = {
     'Ultrasound': load_learner('ODDUltrasound.pkl'),
@@ -24,17 +25,21 @@ modality_keys = ['Ultrasound', 'OCT', 'Fundus', 'Fluorescence']
 def classify_images(img_ultrasound, img_oct, img_fundus, img_fluorescence):
     imgs = [img_ultrasound, img_oct, img_fundus, img_fluorescence]
     predictions = []
+    detailed_predictions = []  # To store detailed predictions for each modality
     
     # Convert images to PILImage and predict with each model
     for img, key in zip(imgs, modality_keys):
         pil_img = PILImage.create(img)
         pred, _, _ = models[key].predict(pil_img)
         predictions.append(pred)
+        detailed_predictions.append(f"{key}: {pred}")  # Add the prediction with the modality name
     
     # Majority vote for final decision
     final_decision = max(set(predictions), key=predictions.count)
     
-    return f"ODD Detection: {final_decision}"
+    detailed_predictions.append(f"Final Decision: {final_decision}")  # Add the final decision
+    
+    return "\n".join(detailed_predictions)  # Return detailed predictions as a single string
 
 # Adjust the Gradio interface definition by removing 'shape' argument
 inputs = [gr.Image(label=f"{modality} Image") for modality in modality_keys]