import numpy as np
import cv2.cv as cv
import cv2
import numpy as np
font = cv2.FONT_HERSHEY_SIMPLEX
a0=0
a1=218
a2=117
a3=17
a4=255
a5=255
a6=6
a7=49
a8=0
a9=108
a10=5
def updateValue(new_value):
    # make sure to write the new value into the global variable
    global a0
    a0 = new_value
    return
def updateValue1(new_value):
    # make sure to write the new value into he global variable
    global a1
    a1 = new_value
    return
def updateValue2(new_value):
    # make sure to write the new value into the global variable
    global a2
    a2 = new_value
    return
def updateValue3(new_value):
    # make sure to write the new value into the global variable
    global a3
    a3 = new_value
    return
def updateValue4(new_value):
    # make sure to write the new value into the global variable
    global a4
    a4 = new_value
    return
def updateValue5(new_value):
    # make sure to write the new value into the global variable
    global a5
    a5 = new_value
    return
def updateValue6(new_value):
    # make sure to write the new value into the global variable
    global a6
    a6 = new_value
    return
def updateValue7(new_value):
    # make sure to write the new value into the global variable
    global a7
    a7 = new_value
    return
def updateValue8(new_value):
    # make sure to write the new value into the global variable
    global a8
    a8 = new_value
    return
def updateValue9(new_value):
    # make sure to write the new value into the global variable
    global a9
    a9 = new_value
    return
def updateValue10(new_value):
    # make sure to write the new value into the global variable
    global a10
    a10 = new_value
    return

cv2.namedWindow("OutputImage")
cv2.createTrackbar("1", "OutputImage", a0, 255, updateValue)
cv2.createTrackbar("2", "OutputImage", a1, 255, updateValue1)
cv2.createTrackbar("3", "OutputImage", a2, 255, updateValue2)
cv2.createTrackbar("4", "OutputImage", a3, 255, updateValue3)
cv2.createTrackbar("5", "OutputImage", a4, 255, updateValue4)
cv2.createTrackbar("6", "OutputImage", a5, 255, updateValue5)
cv2.createTrackbar("param1", "OutputImage", a6, 255, updateValue6)
cv2.createTrackbar("param2", "OutputImage", a7, 255, updateValue7)
cv2.createTrackbar("minRadius", "OutputImage", a8, 255, updateValue8)
cv2.createTrackbar("maxRadius", "OutputImage", a9, 255, updateValue9)
cv2.createTrackbar("maxDist", "OutputImage", a10, 255, updateValue10)
# open the camera
cap = cv2.VideoCapture(0)

while True:
    #read the image from the camera
    ret, frame = cap.read()

    #You will need this later
    #frame = cv2.GaussianBlur(frame,(5,5),0)
    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # color detection limits
    lowerLimits = np.array([a0, a1, a2])
    upperLimits = np.array([a3, a4, a5])

    # Our operations on the frame come here
    thresholded = cv2.inRange(frame, lowerLimits, upperLimits)
    outimage = cv2.bitwise_and(frame, frame, mask = thresholded)

    circles = cv2.HoughCircles(thresholded,cv.CV_HOUGH_GRADIENT,2,a10,
                            param1=a6+1,param2=a7+1,minRadius=a8,maxRadius=a9)
    if circles != None:
        for i in circles[0,:]:
            cv2.circle(frame,(i[0],i[1]),i[2],(0,255,0),2)
            cv2.putText(frame,"x: " + str(i[0])+ " y:" + str(i[1]),(i[0],i[1]), font, 0.5,(255,255,255),2)
    cv2.imshow('original', frame)

    # Display the resulting frame
    cv2.imshow('processed',outimage)

    # Quit the program when Q is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
print 'closing program'
cap.release()
cv2.destroyAllWindows()