interval prediction (#13)

- interval prediction (f489eb8fddff981cbfbf647eea7232e8eaf3b4a9)


Co-authored-by: Sandro Ferroni <[email protected]>

predictor.py

@@ -76,11 +76,26 @@ def decrypt_prediction():
 
         # Interpret the prediction
         binary_prediction = int(np.argmax(decrypted_prediction))
-        return "⚠️ Fraudulent ⚠️" if binary_prediction == 1 else "😊 Non-fraudulent 😊", gr.update(value="Decryption successful ✅")
+        # Ensure the prediction is a flat array
+        if isinstance(decrypted_prediction, np.ndarray) and decrypted_prediction.ndim > 1:
+            decrypted_prediction = decrypted_prediction.flatten()
+
+        # Generate the HTML for the percentage bar
+        bar_html = f"""
+        <div style="width: 100%; background-color: lightgray; border-radius: 5px; overflow: hidden; display: flex;">
+            <div style="width: {decrypted_prediction[0] * 100}%; background-color: green; color: white; text-align: center; padding: 5px 0;">
+                {decrypted_prediction[0] * 100:.1f}% Non-Fraud
+            </div>
+            <div style="width: {decrypted_prediction[1] * 100}%; background-color: red; color: white; text-align: center; padding: 5px 0;">
+                {decrypted_prediction[1] * 100:.1f}% Fraud
+            </div>
+        </div>
+        """
+        return "⚠️ Fraudulent ⚠️" if binary_prediction == 1 else "😊 Non-fraudulent 😊", gr.update(value="Decryption successful ✅"), bar_html
         
     except Exception as e:
         logging.error(f"Error during prediction: {e}")
-        return "Error during prediction❌", "Error during prediction❌"
+        return "Error during prediction❌", "Error during prediction❌","Error during prediction❌"
 
 def key_already_generated():
     """