def detect_and_draw(img, cascade):
# allocate temporary images
global var2
gray = cv.CreateImage((img.width,img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
cv.Round (img.height / image_scale)), 8, 1)
# convert color input image to grayscale
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
if(cascade):
t = cv.GetTickCount()
faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0),
haar_scale, min_neighbors, haar_flags, min_size)
t = cv.GetTickCount() - t
# print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.))
if faces:
for ((x, y, w, h), n) in faces:
# the input to cv.HaarDetectObjects was resized, so scale the
# bounding box of each face and convert it to two CvPoints
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
print pt1
var2=var2+1
if (var2==10):
led.face()
var2=0
emotion.happy()
cv.ShowImage("result", img)
def detect_and_draw(img, cascade):
# allocate temporary images
global var2
gray = cv.CreateImage((img.width, img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(
img.width / image_scale), cv.Round(img.height / image_scale)), 8, 1)
# convert color input image to grayscale
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
if (cascade):
t = cv.GetTickCount()
faces = cv.HaarDetectObjects(small_img, cascade,
cv.CreateMemStorage(0), haar_scale,
min_neighbors, haar_flags, min_size)
t = cv.GetTickCount() - t
# print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.))
if faces:
for ((x, y, w, h), n) in faces:
# the input to cv.HaarDetectObjects was resized, so scale the
# bounding box of each face and convert it to two CvPoints
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
print pt1
var2 = var2 + 1
if (var2 == 10):
led.face()
var2 = 0
emotion.happy()
cv.ShowImage("result", img)
elif data.startswith("red"):
data="i found a red object"
no_words=len(data)
no_char=0
sa.stmt=data
sa.speak=True
speech.say(data)
elif data.startswith("blue"):
data="i found a blue object"
no_words=len(data.split())
no_char=0
sa.stmt=data
sa.speak=True
speech.say(data)
elif data.startswith("love"):
emotion.happy()
#while 1:
# data = raw_input ( "SEND( TYPE q or Q to Quit):" )
# if (data == 'Q' or data == 'q'):
# client_socket.send (data)
# client_socket.close()
# break;
# else:
# client_socket.send(data)
# data = client_socket.recv(512)
# if ( data == 'q' or data == 'Q'):
# client_socket.close()
# break;
