Update tasks/audio.py

tasks/audio.py

@@ -239,18 +239,39 @@ for audio_data in test_dataset["audio"]:
 
 print("Predictions:", predictions)
 
+def map_predictions_to_labels(predictions):
+    """
+    Maps string predictions to numeric labels:
+    - "chainsaw" -> 0
+    - any other class -> 1
+    Args:
+        predictions (list of str): List of class name predictions.
+    Returns:
+        list of int: Mapped numeric labels.
+    """
+    return [0 if pred == "chainsaw" else 1 for pred in predictions]
+
+from sklearn.metrics import accuracy_score
+
+# Map string predictions to numeric labels
+numeric_predictions = map_predictions_to_labels(predictions)
+
+# Extract true labels (already numeric)
+true_labels = test_dataset["label"]
+
+# Calculate accuracy
+accuracy = accuracy_score(true_labels, numeric_predictions)
+print("Accuracy:", accuracy)
 
-    
     #--------------------------------------------------------------------------------------------
     # YOUR MODEL INFERENCE STOPS HERE
-    #--------------------------------------------------------------------------------------------   
-    
+    #--------------------------------------------------------------------------------------------  
+   
     # Stop tracking emissions
     emissions_data = tracker.stop_task()
-    
-    # Calculate accuracy
-    accuracy = accuracy_score(true_labels, predictions)
-    
+   
+   
+   
     # Prepare results dictionary
     results = {
         "username": username,
@@ -268,5 +289,5 @@ print("Predictions:", predictions)
             "test_seed": request.test_seed
         }
     }
-    
-    return results 
+   
+    return results