GOTURN OpenCV Python Deep learning based Object Tracking Algorithm

import cv2

import numpy as np

# Load GOTURN model

tracker = cv2.TrackerGOTURN_create()

#live video camera

cap = cv2.VideoCapture(1)

if not cap.isOpened():

    print("Error: Could not open video.")

    exit()

# Read the first frame

ret, frame = cap.read()

if not ret:

    print("Error: Could not read video frame.")

    exit()

bbox = cv2.selectROI(frame, False)

#bbox = (282, 34, 124, 141)  # Adjust based on your object location and size

ok = tracker.init(frame, bbox)

while True:

    ret, frame = cap.read()

    if not ret:

        break

    # Start timer

    timer = cv2.getTickCount()

    # Update the tracker

    ok, bbox = tracker.update(frame)

    if ok:    

        fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)

        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)

    #display FPS

    cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2)

    cv2.imshow("Tracking", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):

        break

    

print(bbox)

cap.release()

cv2.destroyAllWindows()