model output

app.py

@@ -317,8 +317,7 @@ def decrypt_output(user_id):
         user_id (int): The current user's ID.
 
     Returns:
-        bool: The decrypted output (True if seizure detected, False otherwise)
-
+        str: The decrypted output message
     """
     if user_id == "":
         raise gr.Error("Please generate the private key first.")
@@ -345,14 +344,23 @@ def decrypt_output(user_id):
     # Deserialize, decrypt and post-process the encrypted output
     try:
         decrypted_output = client.deserialize_decrypt_post_process(encrypted_output)
+        
+        # The decrypted output should be a 1D array with 2 elements
+        if isinstance(decrypted_output, np.ndarray) and decrypted_output.shape == (2,):
+            predicted_class = np.argmax(decrypted_output)
+            confidence = decrypted_output[predicted_class]
+            result = "Seizure detected" if predicted_class == 1 else "No seizure detected"
+            return f"{result} (Confidence: {confidence:.2f})"
+        else:
+            logger.error(f"Unexpected decrypted output format: {decrypted_output}")
+            raise ValueError("Unexpected output format from the model")
+
     except RuntimeError as e:
         logger.error(f"Error during deserialization: {str(e)}")
         raise gr.Error("Failed to deserialize the encrypted output. The data might be corrupted or in an unexpected format.")
     except Exception as e:
         logger.error(f"Unexpected error during decryption: {str(e)}")
         raise gr.Error(f"An unexpected error occurred during decryption: {str(e)}")
-    
-    return "Seizure detected" if decrypted_output else "No seizure detected"
 
 def resize_img(img, width=256, height=256):
     """Resize the image."""

client_server_interface.py

@@ -146,6 +146,5 @@ class FHEClient:
         output = self.client.decrypt(encrypted_output)
 
         # Post-process the output (if needed)
-        seizure_detected = self.seizure_detector.post_processing(output)
-
-        return seizure_detected
+        # Assuming the output is already in the correct format (2-element array)
+        return output

server.py

@@ -114,7 +114,10 @@ def run_fhe(user_id: str = Form()):
         #     gc.collect()
 
         # Placeholder output
-        placeholder_output = np.random.randint(0, 2**64-1, size=(1, 2, 32769), dtype=np.uint64)
+        # Generate a random 2-element array with values between 0 and 1
+        placeholder_output = np.random.rand(2)
+        # Ensure the sum of the two elements is 1 (to mimic softmax output)
+        placeholder_output = placeholder_output / np.sum(placeholder_output)
         encrypted_output = placeholder_output.tobytes()
 
         fhe_execution_time = round(time.time() - start, 2)