input: Write a python function to detect objects in a video stream using OpenCV and a given classifier file.
  assert isinstance(detect_objects('video.mp4', 'object.xml'), list)
  assert len(detect_objects('video.mp4', 'object.xml')) > 0
output: def detect_objects(video_path, classifier_path):
      import cv2
      
      # Load the classifier
      classifier = cv2.CascadeClassifier(classifier_path)
      
      # Open the video file
      cap = cv2.VideoCapture(video_path)
      
      detected_objects = []
      
      while cap.isOpened():
          ret, frame = cap.read()
          if not ret:
              break
          
          # Convert the frame to grayscale
          gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
          
          # Detect objects in the frame
          objects = classifier.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
          
          for (x, y, w, h) in objects:
              detected_objects.append((x, y, w, h))
      
      cap.release()
      
      return detected_objects