OpenCV 3 Computer Vision with Python Cookbook

How to do it...

The steps for this recipe are:

1. Import all of the necessary modules:

import cv2import numpy as np

2. Open a video file, read its frame, and select an object to track:

cap = cv2.VideoCapture("../data/traffic.mp4")_, frame = cap.read()bbox = cv2.selectROI(frame, False, True)cv2.destroyAllWindows()

3. Create the Median Flow tracker and initialize it with the first frame from the video and the bounding box we've selected. Then, read the remaining frames one-by-one, feed them into the tracker, and get a new bounding box for each frame. Display the bounding box, as well as the number of frames that the Median Flow algorithm is able to process each second:

tracker = cv2.TrackerMedianFlow_create()status_tracker = tracker.init(frame, ...