VidStream.py

from collections import deque
import numpy as np
import cv2
import imutils
import time
'''
The following was taken from our other repository: https://github.com/KingTarrion/HKN-ASME-Curiosity-Jr
This is an excerpt from Tracking.py
'''


cap = cv2.VideoCapture(0)

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()
    frame = imutils.resize(frame, width=600)
    #blurred = cv2.GaussianBlur( frame, (11, 11), 0)
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # construct a mask for the color "blue", then perform
    # a series of dilations and erosions to remove any small
    # blobs left in the mask
    lowblue = np.array([91,100,100])
    highblue = np.array([110,255,255])

    mask = cv2.inRange(hsv, lowblue, highblue)
    mask = cv2.erode(mask, None, iterations=2)
    mask = cv2.dilate(mask, None, iterations=2)

    # find contours in the mask and initialize the current
    # (x, y) center of the ball
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]

    center = None
    # initialize currentX for x coordinate of center of the object
    currentX = None

    # onlly proceed if at least one contour was found
    if len(cnts) > 0:
        # find the largest contour in the mask, then use
        # it to compute the minimum enclosing circle and
        # centroid
        c = max(cnts, key=cv2.contourArea)
        ((x, y), radius) = cv2.minEnclosingCircle(c)
        M = cv2.moments(c)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
        currentX = (int(M["m10"] / M["m00"]))

        # only proceed if the radius meets a minimum size
        if radius > 10:
            # draw the circle and centroid on the frame,
            # then update the list of tracked points
            cv2.circle(frame, (int(x), int(y)), int(radius),
                       (0, 255, 255), 2)
            cv2.circle(frame, center, 5, (0, 0, 255), -1)

    # update the points queue


    # Our operations on the frame come here

    # Display the resulting frame
    cv2.imshow('frame',frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

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