def get_face(frame):
# print frame
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)
if len(faces) == 0:
if C.Debug:
# print frame
cv2.imshow('face', frame)
return None
else:
# Draw a rectangle around the faces
mx = my = mh = mw = 0
mh = 1
mw = 256
for (x, y, w, h) in faces:
if w*h > mh*mw:
if C.Debug:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
mx = x
my = y
mh = h
mw = w
if C.Debug:
# print frame
cv2.imshow('face', frame)
if mx == my and mx == 0:
return None
msg = CVMessage()
shape = frame.shape
msg.x,msg.y,msg.width,msg.height = util.scaled_rect_coords(mx,my,mw,mh,shape[0],shape[1])
if C.Debug:
# print "face height: ",msg.height
pass
return msg
def get_cone(cv_image):
msg = CVMessage()
msg.x = 0
msg.y = 0
msg.height = 0
hsv = cv2.cvtColor(cv_image, cv2.COLOR_BGR2HSV)
lower_green = np.array([60, 50, 0], dtype=np.uint8)
upper_green = np.array([100, 200, 200], dtype=np.uint8)
mask = cv2.inRange(hsv, lower_green, upper_green).astype(np.uint8)
kernel = np.ones((11,11), np.uint8)
denoised = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
denoised = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
allContours, hierarchy = cv2.findContours(denoised, cv2.cv.CV_RETR_EXTERNAL, cv2.cv.CV_CHAIN_APPROX_SIMPLE)
if len(allContours) == 0:
if C.Debug:
cv2.imshow('cone',cv_image)
return None
else:
largestContour = allContours[0]
largestArea = cv2.contourArea(largestContour)
for i in range (1, len(allContours)):
area = cv2.contourArea(allContours[i])
if area > largestArea:
largestContour = allContours[i]
largestArea = area
x, y, w, h = cv2.boundingRect(largestContour)
if C.Debug:
cv2.rectangle(cv_image, (x, y), (x+w, y+h), (0, 255, 0), 4)
cv2.imshow('cone',cv_image)
if (w*h > 512):
nRows_nCols = cv_image.shape
msg.x, msg.y,msg.width, msg.height = util.scaled_rect_coords(x, y, w, h, nRows_nCols[0], nRows_nCols[1])
else:
return None
return msg;
