Update app.py

app.py

@@ -9,21 +9,17 @@ def predict(img):
     try:
         # Create the image object
         img = PILImage.create(img)
-
         # Get predictions from the model
         pred, pred_idx, probs = learn.predict(img)
-
         # Fetch the labels dynamically from the model's vocabulary
         labels = learn.dls.vocab
-
-        # Convert probabilities to percentages and construct the output dictionary dynamically
-        return {labels[i]: f"{probs[i]*100:.2f}%" for i in range(len(labels))}
+        # Ensure probabilities are floats
+        return {labels[i]: {float(probs[i]) for i in range(len(labels))}
     except Exception as e:
         # Log the exception and return it as an error message
         print(f"An error occurred: {e}")
         return {"error": str(e)}
 
-
 # Define the Gradio interface
 title = "Interior Design Classifier"
 description = "Upload an image of an interior design and get a prediction of the design style."