How to optimize this for tracking a finger on a touch screen from https://pyimagesearch.com/2018/07/23/simple-object-tracking-with-opencv/

track_finger_using_cv2.py

#https://pyimagesearch.com/2015/09/14/ball-tracking-with-opencv/
#https://pyimagesearch.com/2018/07/23/simple-object-tracking-with-opencv/

import cv2
import sys

(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')

if __name__ == '__main__':

    # Set up tracker.
    # Instead of CSRT, you can also use

    tracker_types = ['BOOSTING', 'MIL', 'KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']
    tracker_type = tracker_types[7]

    if int(minor_ver) < 3:
        tracker = cv2.Tracker_create(tracker_type)
    else:
        if tracker_type == 'BOOSTING':
            tracker = cv2.TrackerBoosting_create()
        elif tracker_type == 'MIL':
            tracker = cv2.TrackerMIL_create()
        elif tracker_type == 'KCF':
            tracker = cv2.TrackerKCF_create()
        elif tracker_type == 'TLD':
            tracker = cv2.TrackerTLD_create()
        elif tracker_type == 'MEDIANFLOW':
            tracker = cv2.TrackerMedianFlow_create()
        elif tracker_type == 'GOTURN':
            tracker = cv2.TrackerGOTURN_create()
        elif tracker_type == 'MOSSE':
            tracker = cv2.TrackerMOSSE_create()
        elif tracker_type == "CSRT":
            tracker = cv2.TrackerCSRT_create()  # Read video

video = cv2.VideoCapture(1)

if not video.isOpened():
    print("Could not open video")
    sys.exit()

# Read first frame.
ok, frame = video.read()
if not ok:
    print('Cannot read video file')
    sys.exit()
# Define an initial bounding box
bbox = (287, 23, 86, 320)

# Uncomment the line below to select a different bounding box
bbox = cv2.selectROI(frame, False)

# Initialize tracker with first frame and bounding box
ok = tracker.init(frame, bbox)

while True:
    # Read a new frame
    ok, frame = video.read()
    if not ok:
        break

    # Start timer
    timer = cv2.getTickCount()

    # Update tracker
    ok, bbox = tracker.update(frame)

    # Calculate Frames per second (FPS)
    fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);

    # Draw bounding box
    if ok:
        # Tracking success
        p1 = (int(bbox[0]), int(bbox[1]))
        p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
        cv2.rectangle(frame, p1, p2, (255, 0, 0), 2, 1)
    else:
        # Tracking failure
        cv2.putText(frame, "Tracking failure detected", (100, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)

    # Display tracker type on frame
    cv2.putText(frame, tracker_type + " Tracker", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2);

    # Display FPS on frame
    cv2.putText(frame, "FPS : " + str(int(fps)), (100, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2);
    # Display result
    cv2.imshow("Tracking", frame)

    # Exit if ESC pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):  # if press SPACE bar
        break

video.release()
cv2.destroyAllWindows()