return x,y,angle of goal, code cleaned
added a try-except for the cv2.videoCapture
changed video port index to = 1
added a 10ms delay before retrying camera intialise
put visual feedback inside a try-except so it doesn't fail
rearranged def absolute, returns x, y, angle
fixed equation to calculate asin of angle
import cv2
import cv2.cv as cv
import numpy as np
import math

kernel = cv2.getStructuringElement (cv2.MORPH_ELLIPSE,(4, 4))

class BallFinder:
    def __init__(self, colour='r', width = 640, height = 480): # Constructor to get the video capture set up
        self._vc = cv2.VideoCapture(-1)
        self._width = 1.0 * width # Force a float
        self._height = 1.0 * height

        #Set Video Capture properties
        self._vc.set(cv.CV_CAP_PROP_BRIGHTNESS, 0.5)
        self._vc.set(cv.CV_CAP_PROP_SATURATION, 0.5)  #0.125
        self._vc.set(cv.CV_CAP_PROP_CONTRAST, 0.5)   #0.01

        #Max. distance the camera can detect is 13 feet
		#DistanceThreshold is the distance threshold
		#It is the maximum distance that the camera will detect
        self.DistanceThreshold = 13 #ft

        #distance formula from width of ball
	    #distance = 1661.5*w**-1.075
        self._MaxWidth = (1661.5/self.DistanceThreshold)**(1/1.075)*width/640.0 #pixels

        #squareness ratio
        self.target_ratio = 0.6

        # Public member variables to store the last calculated values
        # Invalid values indicate ball not found
        self.xbar = 99.0 # xbar, ybar should be in the range [-1.0, 1.0]
        self.ybar = 99.0
        self.diam = 99.0 # diam should be in the range (0.0, 2.0]

        self._is_red = (colour[0] == 'r' or colour[0] == 'R')
        self._vc.set(cv.CV_CAP_PROP_FRAME_WIDTH, self._width)
        self._vc.set(cv.CV_CAP_PROP_FRAME_HEIGHT, self._height)

    def setColour(self, colour):
        self._is_red = (colour[0].lower() == 'r')

    def find(self):
        if not self._vc:
            # Try to reinitialise, but still return None
            self.__init__()
            return None
        # We have a video capture object so we can proceed
        retval, frame = self._vc.read()
        if not retval:
            return None
        # The capture was successful. Start processing
        hsv_image = cv2.cvtColor(frame, cv.CV_BGR2HSV)
        # Choose mask based on self._is_red
        if self._is_red:
            # Red alliance
            mask_neg = cv2.inRange(hsv_image, (0, 50, 50), (10, 255, 255))
            mask_pos = cv2.inRange(hsv_image, (170, 50, 50), (180, 255, 255))
            mask = mask_pos | mask_neg
        else:
            # Blue alliance
            mask = cv2.inRange(hsv_image, (105, 50, 50), (130, 255, 255))

        #Eroding and Dilating mask
        opened = cv2.erode(mask, kernel, iterations = 7)
        opened = cv2.dilate(opened, kernel, iterations = 7)

        contours, hierarchy = cv2.findContours(opened, cv.CV_RETR_EXTERNAL, cv.CV_CHAIN_APPROX_NONE)
        largest_size = 0
        largest_index = 0

        ball_found = False
        if contours:
            for index, contour in enumerate(contours):
                if cv2.contourArea(contour) > largest_size:

					#get co-ordinates and dimensions
					x,y,w,h = cv2.boundingRect(contours[largest_index])

					#ball squareness
					ballratio = 1.0 * w/h

					if ballratio > self.target_ratio and ballratio < 1.0/self.target_ratio:
						largest_size = cv2.contourArea(contour)
						largest_index = index

            if largest_size > 0:
				if w > self._MaxWidth:
					moments = cv2.moments(contours[largest_index])
					if moments['m00'] != 0:
						self.xbar = 2.0*moments['m10']/moments['m00']/self._width - 1.0
						self.ybar = 2.0*moments['m01']/moments['m00']/self._height - 1.0
						x,y,w,h = cv2.boundingRect(contours[largest_index])
						self.diam = (w + h)/ self._width
						ball_found = True

        if not ball_found:
            # No ball found so set the member variables to invalid values
            self.xbar = 99.0
            self.ybar = 99.0
            self.diam = 99.0
        # Return the frame, the contours and largest image in case we
        # want to show them on the screen
        return (frame, contours, largest_index)

    def absolute(self):
        # Convert xbar, ybar and diam to absolute values for showing on screen
        return (int((self.xbar+1.0)*self._width/2.0),
            int((self.ybar+1.0)*self._height/2.0),
            int(self.diam*self._width/2.0))

if __name__ == "__main__":
    bf = BallFinder('r', 640, 480)
    cv2.namedWindow("preview")

    result = bf.find()
    while result != None:
        frame, contours, largest_index = result

        if bf.diam >= 0.0 and bf.diam <= 2.0:
            # Check that we found the ball

            # Draw what we think is the ball outline
            x, y, diam = bf.absolute() # Get screen plottable values

            cv2.circle(frame, (x, y), diam/2, (200,255,0), 3)
			# Draw the largest contour
            cv2.drawContours(frame, contours, largest_index, (0,255,0), 2)

        cv2.imshow("preview", frame)

        key = cv2.waitKey (20)
        if key != -1: # Exit on any key
            break
        # Get the next frame, and loop forever
        result = bf.find()