main.py

import time
import cv2
from tracker import processLiveFeed, startVideoWriter, endVideoWriter

"""
Implements an ORB-based object tracker as specified by the paper:
   Object Tracking Based on ORB and Temporal-Spacial Constraint by Shuang Wu,
   IEEE Student Member, Yawen Fan, Shibao Zheng, IEEE Member and Hua Yang, IEEE
   Member

Authors: Alberto Serrano, Stephen Kim
"""

def main():
    cap = cv2.VideoCapture("IMG_3385.MOV")
    frame_width = int(cap.get(3))
    frame_height = int(cap.get(4))
    time.sleep(0.3)
    prevImg = None

    # always comparing two frames, so do something else seeing first frame
    # prompt for ROI, then set to cframe
    ret,img = cap.read()
    bbox    = cv2.selectROI(img, False)
    prevImg = img

    # Extract Bounding Box features
    x   = int(bbox[0])
    y   = int(bbox[1])
    w   = int(bbox[2])
    h   = int(bbox[3])
    x_i = x + w/2
    y_i = y + h/2

    # Define current and past frame
    cframe = (x_i, y_i, w, h)
    pframe = cframe

    while(True):
        # Capture frame-by-frame
        ret, img = cap.read()

        # Constraint to end when reading from a video file instead of a device
        # video stream.
        if img is None:
            return

        else:
            # prevImg will be None for first iteration (first frame)
            pframe, cframe = processLiveFeed(prevImg, img, pframe, cframe)
            prevImg = img

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

    # When everything done, release the capture
    cap.release()
    endVideoWriter()
    # cv2.destryoAllWindows()


if __name__ == "__main__":
    main()