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tracking.py
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tracking.py
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# USAGE
# python ball_tracking.py --video ball_tracking_example.mp4
# python ball_tracking.py
# This script is configured to
# import the necessary packages
from collections import deque
import numpy as np
import argparse
import imutils
import cv2
import time
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help="path to the (optional) video file")
ap.add_argument("-b", "--buffer", type=int, default=64,
help="max buffer size")
args = vars(ap.parse_args())
# Parameters for operation
camera_address = 0 # 1 for the USB webcam, 0 for the onboard webcam
radius_min = 4 # Minimum radius size of tracking circle to consider an object
# define the lower and upper boundaries of the "green"
# ball in the HSV (RGB??) color space, then initialize the
# list of tracked points
# HSV Values for table covered with white poster, LED Lighting. 20170710
# greenLower = (25,108,15)
# greenUpper = (65,255,57)
# HSV for ambient fluorescent lighting on yellow breadboard
greenLower = (6,95,97)
greenUpper = (26,255,174)
# Values for Red tracker at home, daytime, july 22
# greenLower = (0, 200, 101)
# greenUpper = (21, 253, 177)
pts = deque(maxlen=args["buffer"])
#Green Egg Works better than the Pink one
# if a video path was not supplied, grab the reference
# to the webcam
if not args.get("video", False):
camera = cv2.VideoCapture(camera_address)
# otherwise, grab a reference to the video file
else:
camera = cv2.VideoCapture(args["video"])
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')
#size = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)), int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT)))
size = (640,480)
video = cv2.VideoWriter('output.avi',fourcc, 30.0, size)
# Define and Open coordinates text file
filepath = "C:\labview\OutputTest.txt"
text_file = open(filepath, "w")
# text_file = open("OutputTest.txt", "w")
text_file.close()
time.sleep(2.5)
# keep looping
while True:
# grab the current frame
(grabbed, frame) = camera.read()
text_file = open(filepath, "a")
# if we are viewing a video and we did not grab a frame,
# then we have reached the end of the video
if args.get("video") and not grabbed:
break
#Flip the frame
# Try disabling the flipping, so we get less confused. 20170627
# frame = cv2.flip(frame, 1)
# write the frame
#video.write(frame)
# resize the frame, blur it, and convert it to the HSV
# color space
#frame = imutils.resize(frame, width=600) #This line of code seems to prevent the video.write from working later on
# blurred = cv2.GaussianBlur(frame, (11, 11), 0)
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# write the frame
#video.write(frame)
# construct a mask for the color "green", then perform
# a series of dilations and erosions to remove any small
# blobs left in the mask
mask = cv2.inRange(hsv, greenLower, greenUpper)
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
# only 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"]))
print((x, y))
text_file.write("{X: %.3f, Y: %.3f} \n" % (x, y))
# only proceed if the radius meets a minimum size
if radius > radius_min:
# 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
pts.appendleft(center)
# loop over the set of tracked points
for i in xrange(1, len(pts)):
# if either of the tracked points are None, ignore
# them
if pts[i - 1] is None or pts[i] is None:
continue
# otherwise, compute the thickness of the line and
# draw the connecting lines
thickness = int(np.sqrt(args["buffer"] / float(i + 1)) * 2.5)
cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
# show the frame to our screen
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# write the frame
video.write(frame)
text_file.close()
time.sleep(0.07725) # Original sleep time
# time.sleep(0.02)
# if the 'q' key is pressed, stop the loop
if key == ord("q"):
break
# cleanup the camera and close any open windows
camera.release()
video.release()
cv2.destroyAllWindows()
text_file.close()