31_Object_Tracking_Advanced.py

"""
Object tracking
Original url:
https://www.learnopencv.com/object-tracking-using-opencv-cpp-python/
 
Locating an object in successive frames of a video is called tracking.
    - BOOSTING
    - MIL
    - KCF
    - TLD
    - MEDIANFLOW
    - GOTURN
    - MOSSE 
    - CSRT

The motion model predicts the approximate location of the object. 

The appearance model fine tunes this estimate to provide a more accurate estimate based on appearance.

In machine learning, we use the word “online” to refer to algorithms that are trained on the fly at run time. An offline classifier may need thousands of examples to train a classifier, but an online classifier is typically trained using a very few examples at run time.

GOTURN
    Generic Object Tracking Using Regression Networks, is a Deep Learning based tracking algorithm.
    It learns the motion of an object in an offline manner. 
    Note:
        If you want to use the GOTURN method, you need to download the caffee model files from this link into the path of this script:
        https://www.dropbox.com/sh/77frbrkmf9ojfm6/AACgY7-wSfj-LIyYcOgUSZ0Ua?dl=0


"""

# Import the packages
import cv2
import sys

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

if __name__ == '__main__':

    # Set up tracker.
    # Instead of MIL, you can also use
    tracker_types = ['BOOSTING', 'MIL', 'KCF',
                     'TLD', 'MEDIANFLOW', 'GOTURN', 'CSRT', "MOSSE"]
    tracker_type = tracker_types[-3]

    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 == "CSRT":
        tracker = cv2.TrackerCSRT_create()
    elif tracker_type == "MOSSE":
        tracker = cv2.TrackerMOSSE_create()

    # Read video
    video = cv2.VideoCapture("./images/chaplin.mp4")

    # Exit if video not opened.
    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:
            # The tracker failed to track the object, here you can add some object detection methods
            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
        k = cv2.waitKey(1) & 0xff
        if k == 27:
            break

    # Destroy all the windows opened before
    cv2.destroyAllWindows()