def broke():
#read the frames
_,frame = cap.read()
#convert to hsv and find range of colors
hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
thresh = cv2.inRange(hsv,np.array((66,64,233)), np.array((92,255,255)))
thresh2 = thresh.copy()
#erode and dilate
thresh = cv2.erode(thresh, (2,2))
thresh = cv2.dilate(thresh, (2,2))
(cnts, _) = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = sorted(cnts, key = cv2.contourArea, reverse = True)[:10]
goalCnt = None
#filter by area
min_area = 2000
best_cnt = None
#max_area = 4000
for i, cnt in enumerate(cnts):
if i > 100:
break
area = cv2.contourArea(cnt)
if area > min_area:
min_area = area
goalCnt = cnt
if goalCnt == None:
cx = cy = -1
print "Nothing Found"
#filter by number of vertices
for c in cnts:
perimeter = cv2.arcLength(c, True)
#change 0.02 for precision value
approx = cv2.approxPolyDP(c, 0.02 * perimeter, True)
#check if shape has 8 vertices
if len(approx) > 8:
goalCnt == approx
break
#find the centroid
moment = cv2.moments(goalCnt)
hull_cnt = cv2.convexHull(goalCnt)
#set x and y and draw on frame
cv2.drawContours(thresh, hull_cnt, -1, (0,255,0), 3)
cx,cy = int(M['m10']/M['m00']), int(M['m01']/M['m00'])
cv2.circle(thresh,(cx,cy),5,255,-1)
#show the final processed image
cv2.imshow("contours", frame)
#find the error, distance, and angle
error = cx-320
#make sure there is an object before finding distance and angle
if (cy > -1 and cx > -1):
dist = distance.findDistance(cy)
ang = angle.getAngle(dist, error)
else:
#return -1 if no object is found
ang = dist = -1
#give values to server
serialserver.putData(error, ang, distance)
#print for testing
#print cx
print cy
import distance import angle y = 400 distance = distance.findDistance(y) # print distance error = 100 angle = angle.getAngle(distance, angle)
import distance import angle y = 400 distance = distance.findDistance(y) #print distance error = 100 angle = angle.getAngle(distance, angle)