input: Write a python function to perform label detection and object localization using Google Cloud Vision API. 
  assert detect_labels_and_objects('park.jpg') == (['Label1', 'Label2'], ['Object1', 'Object2'])
  assert detect_labels_and_objects('forest.jpg') == (['Tree', 'Nature'], ['Tree', 'Animal'])
  assert detect_labels_and_objects('city.jpg') == (['Building', 'Road'], ['Car', 'Person'])
output: def detect_labels_and_objects(image_path):
      from google.cloud import vision
      from google.cloud.vision_v1 import types
  
      # Initialize the Google Cloud Vision client
      client = vision.ImageAnnotatorClient()
  
      # Load the image
      with open(image_path, 'rb') as image_file:
          content = image_file.read()
      image = types.Image(content=content)
  
      # Perform label detection
      response = client.label_detection(image=image)
      labels = [label.description for label in response.label_annotations]
  
      # Perform object localization
      response = client.object_localization(image=image)
      objects = [obj.name for obj in response.localized_object_annotations]
  
      return labels, objects