# import the necessary packages
import numpy as np
import argparse
import cv2
import time

cap = cv2.VideoCapture(0) # Set Capture Device, in case of a USB Webcam try 1, or give -1 to get a list of available devices

#Set Width and Height 
# cap.set(3,1280)
# cap.set(4,720)

# The above step is to set the Resolution of the Video. The default is 640x480.
# This example works with a Resolution of 640x480.

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

	# load the image, clone it for output, and then convert it to grayscale
			
	output = frame.copy()
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
	
	# apply GuassianBlur to reduce noise. medianBlur is also added for smoothening, reducing noise.
	gray = cv2.GaussianBlur(gray,(5,5),0);
	gray = cv2.medianBlur(gray,5)
	
	# Adaptive Guassian Threshold is to detect sharp edges in the Image. For more information Google it.
	gray = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,\
            cv2.THRESH_BINARY,11,3.5)
	
	kernel = np.ones((2.6,2.7),np.uint8)
	gray = cv2.erode(gray,kernel,iterations = 1)
	# gray = erosion
	
	gray = cv2.dilate(gray,kernel,iterations = 1)
	# gray = dilation

	# get the size of the final image
	# img_size = gray.shape
	# print img_size
	
	# detect circles in the image
	circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 260, param1=30, param2=65, minRadius=0, maxRadius=0)
	# print circles
	
	# ensure at least some circles were found
	if circles is not None:
		# convert the (x, y) coordinates and radius of the circles to integers
		circles = np.round(circles[0, :]).astype("int")
		
		# loop over the (x, y) coordinates and radius of the circles
		for (x, y, r) in circles:
			# draw the circle in the output image, then draw a rectangle in the image
			# corresponding to the center of the circle
			cv2.circle(output, (x, y), r, (0, 255, 0), 4)
			cv2.rectangle(output, (x - 5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)
			#time.sleep(0.5)
			print "Column Number: "
			print x
			print "Row Number: "
			print y
			print "Radius is: "
			print r

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

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