Object Tracking Concept

import cv2

def track_object(video_path, initial_bbox=None):
    """
    Track an object across video frames using CSRT tracker.
    initial_bbox: (x, y, w, h) of the object in the first frame.
    If None, user can select the object interactively.
    """
    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        print("Could not open video")
        return

    ret, first_frame = cap.read()
    if not ret:
        return

    # Initialise tracker
    # Available trackers: CSRT (accurate), KCF (fast), MOSSE (fastest)
    tracker = cv2.TrackerCSRT_create()

    if initial_bbox is None:
        # Let user select the region to track
        print("Select object to track, press ENTER when done")
        initial_bbox = cv2.selectROI("Select Object", first_frame, fromCenter=False)
        cv2.destroyWindow("Select Object")

    # Initialise tracker with first frame and bounding box
    tracker.init(first_frame, initial_bbox)
    print(f"Tracking started: initial box = {initial_bbox}")

    frame_count = 0
    success_count = 0

    while frame_count < 500:
        ret, frame = cap.read()
        if not ret:
            break

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

        if success:
            x, y, w, h = [int(v) for v in bbox]
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
            cv2.putText(frame, "Tracking", (x, y-10),
                       cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
            success_count += 1
        else:
            cv2.putText(frame, "Tracking lost", (50, 50),
                       cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255), 2)

        frame_count += 1

    cap.release()
    success_rate = success_count / frame_count * 100 if frame_count > 0 else 0
    print(f"Tracking success rate: {success_rate:.1f}% ({success_count}/{frame_count})")

track_object("video.mp4", initial_bbox=(100, 50, 80, 120))