code: #!/usr/bin/env python
  import rospy
  from std_msgs.msg import Int32
  from geometry_msgs.msg import PoseStamped, Pose
  from styx_msgs.msg import TrafficLightArray, TrafficLight
  from styx_msgs.msg import Lane
  from sensor_msgs.msg import Image
  from cv_bridge import CvBridge
  from light_classification.tl_classifier import TLClassifier
  import tf
  import cv2
  import yaml
  from scipy.spatial import KDTree
  
  STATE_COUNT_THRESHOLD = 3
  
  class TLDetector(object):
      def __init__(self):
          rospy.init_node('tl_detector')
  
          self.pose = None
          self.waypoints = None
          self.waypoints_2d = None
          self.waypoint_tree = None
          self.camera_image = None
          self.lights = []
  
          sub1 = rospy.Subscriber('/current_pose', PoseStamped, self.pose_cb)
          sub2 = rospy.Subscriber('/base_waypoints', Lane, self.waypoints_cb)
  
          '''
          /vehicle/traffic_lights provides you with the location of the traffic light in 3D map space and
          helps you acquire an accurate ground truth data source for the traffic light
          classifier by sending the current color state of all traffic lights in the
          simulator. When testing on the vehicle, the color state will not be available. You'll need to
          rely on the position of the light and the camera image to predict it.
          '''
          sub3 = rospy.Subscriber('/vehicle/traffic_lights', TrafficLightArray, self.traffic_cb)
          sub6 = rospy.Subscriber('/image_color', Image, self.image_cb)
  
          config_string = rospy.get_param("/traffic_light_config")
          self.config = yaml.load(config_string)
  
          self.upcoming_red_light_pub = rospy.Publisher('/traffic_waypoint', Int32, queue_size=1)
  
          self.bridge = CvBridge()
          self.light_classifier = TLClassifier()
          self.listener = tf.TransformListener()
  
          self.state = TrafficLight.UNKNOWN
          self.last_state = TrafficLight.UNKNOWN
          self.last_wp = -1
          self.state_count = 0
  
          rospy.spin()
  
      def pose_cb(self, msg):
          self.pose = msg
  
      def waypoints_cb(self, waypoints):
          self.waypoints = waypoints
          if not self.waypoints_2d:
              self.waypoints_2d = [[w.pose.pose.position.x, w.pose.pose.position.y] for w in waypoints.waypoints]
              self.waypoint_tree = KDTree(self.waypoints_2d)
  
      def traffic_cb(self, msg):
          self.lights = msg.lights
  
      def image_cb(self, msg):
          """Identifies red lights in the incoming camera image and publishes the index
              of the waypoint closest to the red light's stop line to /traffic_waypoint
  
          Args:
              msg (Image): image from car-mounted camera
  
          """
          self.has_image = True
          self.camera_image = msg
          light_wp, state = self.process_traffic_lights()
  
          '''
          Publish upcoming red lights at camera frequency.
          Each predicted state has to occur `STATE_COUNT_THRESHOLD` number
          of times till we start using it. Otherwise the previous stable state is
          used.
          '''
          if self.state != state:
              self.state_count = 0
              self.state = state
          elif self.state_count >= STATE_COUNT_THRESHOLD:
              self.last_state = self.state
              light_wp = light_wp if state == TrafficLight.RED else -1
              self.last_wp = light_wp
              self.upcoming_red_light_pub.publish(Int32(light_wp))
          else:
              self.upcoming_red_light_pub.publish(Int32(self.last_wp))
          self.state_count += 1
  
      def get_closest_waypoint(self, x , y):
          """Identifies the closest path waypoint to the given position
              https://en.wikipedia.org/wiki/Closest_pair_of_points_problem
          Args:
              pose (Pose): position to match a waypoint to
  
          Returns:
              int: index of the closest waypoint in self.waypoints
  
          """
          #TODO implement
          closest_idx = self.waypoint_tree.query([x,y], 1)[1]
          return closest_idx
  
      def get_light_state(self, light):
          """Determines the current color of the traffic light
  
          Args:
              light (TrafficLight): light to classify
  
          Returns:
              int: ID of traffic light color (specified in styx_msgs/TrafficLight)
  
          """
  #         if(not self.has_image):
  #             self.prev_light_loc = None
  #             return False
  
  #         cv_image = self.bridge.imgmsg_to_cv2(self.camera_image, "bgr8")
  
  #         #Get classification
  #         return self.light_classifier.get_classification(cv_image)
          return light.state
  
      def process_traffic_lights(self):
          """Finds closest visible traffic light, if one exists, and determines its
              location and color
  
          Returns:
              int: index of waypoint closes to the upcoming stop line for a traffic light (-1 if none exists)
              int: ID of traffic light color (specified in styx_msgs/TrafficLight)
  
          """
          #light = None
          closest_light = None
          line_wp_idx = None
  
          # List of positions that correspond to the line to stop in front of for a given intersection
          stop_line_positions = self.config['stop_line_positions']
          if(self.pose):
              #car_position = self.get_closest_waypoint(self.pose.pose)
              car_wp_idx = self.get_closest_waypoint(self.pose.pose.position.x, self.pose.pose.position.y)
          
              #TODO find the closest visible traffic light (if one exists)
              diff = len(self.waypoints.waypoints)
              for i, light in enumerate(self.lights):
                  #Get stop line waypoint index
                  line = stop_line_positions[i]
                  temp_wp_idx = self.get_closest_waypoint(line[0], line[1])
                  #Find closest stop line waypoint index
                  d = temp_wp_idx - car_wp_idx
                  if d>=0 and d<diff:
                      diff = d
                      closest_light = light
                      line_wp_idx = temp_wp_idx
            
          if closest_light:
              state = self.get_light_state(closest_light)
              return line_wp_idx, state
          
          return -1, TrafficLight.UNKNOWN
              
  
          if light:
              state = self.get_light_state(light)
              return light_wp, state
          self.waypoints = None
          return -1, TrafficLight.UNKNOWN
  
  if __name__ == '__main__':
      try:
          TLDetector()
      except rospy.ROSInterruptException:
          rospy.logerr('Could not start traffic node.')
  
apis: scipy.spatial.KDTree