How to produce confidence score using Haar cascade

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I am new to ROS and python programming. I am doing face detection using haar cascade in python. It works fine, except for the confidence score, which shows a constant value of 6.9. Please help me.

The program code is shown below. I have tried tweaking the scale factor values, minimum neighbours, and flag from CASCADE_SCALE_IMAGE to HAAR_BIG_OBJECT. Yet the confidence value remains the same and doesn't change with distance. I have also tried doing it with "haarcascade_frontalface_default.xml" and "haarcascade_frontalface_alt.xml" but with no success.

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
import rospy

from sensor_msgs.msg import Image
# from std_msgs.msg import String

from cv_bridge import CvBridge, CvBridgeError

class face_detector:

    def __init__(self):
        self.image_sub = rospy.Subscriber("/xtion/rgb/image_raw", Image, self.callback)
        self.bridge = CvBridge()
        self.image_pub = rospy.Publisher("face_found", Image, queue_size=1)

    def callback(self, rgb_data):

        try:
            cv_image = self.bridge.imgmsg_to_cv2(rgb_data, desired_encoding="bgr8")

            # Trained xml file to detect face with its path
            # initialize the face recognizer
            face_cascade = cv2.CascadeClassifier("/home/rexrapier/tiago_public_ws/src/face_detector_py/scripts/haarcascade_frontalface_default.xml")

            # converting to grayscale
            image_gray = cv2.cvtColor(cv_image, cv2.COLOR_BGR2GRAY)

            # detect all the faces in the image
            [faces, neighbours, weights] = face_cascade.detectMultiScale3(image_gray, scaleFactor=1.3, minNeighbors=5 ,flags=cv2.CASCADE_SCALE_IMAGE , minSize=(10,10), outputRejectLevels = True)

            # for every face, draw a blue rectangle
            for (x, y, width, height) in faces:
                cv2.rectangle(cv_image, (x, y), (x + width, y + height), color=(255, 0, 0), thickness=2)
                roi_gray = image_gray[y:y + height, x:x + width]
                roi_color = cv_image[y:y + height, x:x + width]
                face_coords = [x, y]

            for conf in weights:
                print(conf)
                print(face_coords)

        except CvBridgeError as e:
            rospy.logerr(e)


        #convert opencv format back to ros format and publish result
        try:
            faces_message = self.bridge.cv2_to_imgmsg(cv_image, "bgr8")
            self.image_pub.publish(faces_message)
        except CvBridgeError as e:
            rospy.logerr(e)

    #to display image in a window
    #cv2.imshow("image", image)
    #if cv2.waitKey() == ord("q"):

def main():
    face_detector()
    rospy.init_node('face_detector_node', anonymous = True)

    try: 
        rospy.spin()
    except KeyboardInterrupt:
        rospy.loginfo("Shutting down")

    cv2.destroyAllWindows()

if __name__ == '__main__':
    main()