import numpy as np

import cv2

# Define path to video

video_path = 'video/iphonecase.mov'

# Define the upper and lower boundaries the colour 'blue'

blue_lower = np.array([100, 67, 0], dtype="uint8")

blue_upper = np.array([255, 128, 50], dtype="uint8")

# Load the video

camera = cv2.VideoCapture(video_path)

while True:

# Grab the current frame

(ok, frame) = camera.read()

# Check to see if at the end of the video

if not ok:

break

# Determine which pixels fall within the blue boundaries and blur the binary image

blue = cv2.inRange(frame, blue_lower, blue_upper)

blue = cv2.GaussianBlur(blue, (3, 3), 0)

# Find contours in the image

(_, contours, _) = cv2.findContours(blue.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Check to see if any contours were found

if len(contours) > 0:

# Sort the contours and find the largest one (area)

contour = sorted(contours, key=cv2.contourArea, reverse=True)[0]

# Compute the minimum bounding box around then contour and then draw it

box = np.int32(cv2.boxPoints(cv2.minAreaRect(contour)))

cv2.drawContours(frame, [box], -1, (0, 255, 0), 2)

# Show the frame and the binary image

cv2.imshow("Tracking", frame)

cv2.imshow("Binary", blue)

# If the 'q' key is pressed, stop the loop

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

break

# Cleanup the camera and close any open windows

camera.release()

cv2.destroyAllWindows()