def detect(image):
image_size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(image_size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect objects
cascade = cv.LoadHaarClassifierCascade('haarcascade_frontalface_alt.xml',
cv.Size(1, 1))
faces = cv.HaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.HAAR_DO_CANNY_PRUNING, cv.Size(50, 50))
if faces:
print 'face detected!'
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
def preRender(self):
frame = self.getFrame()
capture = self.getCapture()
#print _AR.GetMultiMV('data/19_20_21_22_23_24.cfg')
#_AR.GetMultiMV('data/13_14_15_16_17_18.cfg')
#if 'darwin' in os.uname()[0].lower():
if 0:
settings = [
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_FOURCC),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_SATURATION),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_HUE),
]
print settings
size = cv.GetSize(frame)
fsize = size.width, size.height
size = cv.GetSize(self.image)
isize = size.width, size.height
if fsize == isize:
cv.Copy(frame, self.image)
else:
cv.Resize(
frame,
self.image,
CVtypes.CV_INTER_LINEAR,
#CVtypes.CV_INTER_CUBIC,
)
cv.CvtColor(self.image, self.hsvImage, CVtypes.CV_RGB2HSV)
cv.Split(self.hsvImage, self.hsvPlanes[0], self.hsvPlanes[1],
self.hsvPlanes[2], 0)
cv.CvtColor(self.image, self.grayImage, CVtypes.CV_RGB2GRAY)
if 1:
#cv.EqualizeHist(self.hsvPlanes[0],self.hsvPlanes[0])
#cv.EqualizeHist(self.hsvPlanes[2],self.hsvPlanes[2])
#cv.Merge(self.hsvPlanes[0],self.hsvPlanes[1],
# self.hsvPlanes[2],0, self.hsvImage)
#cv.CvtColor(self.hsvImage,self.image,CVtypes.CV_HSV2RGB)
cv.EqualizeHist(self.grayImage, self.grayImage)
cv.Split(self.image, self.rgbPlanes[0], self.rgbPlanes[1],
self.rgbPlanes[2], 0)
cv.Copy(self.image, self.modifiedImage)
def detect(self, image):
size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create and clear storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect faces
faces = cv.HaarDetectObjects(grayscale, self.face_cascade, storage,
1.2, 2, cv.HAAR_DO_CANNY_PRUNING,
self.face_size)
if faces:
# faces detected
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
detected = True
is_face = True
else:
# detect body
bodies = cv.HaarDetectObjects(grayscale, self.body_cascade,
storage, 1.1, 3, 0, self.body_size)
if bodies:
# body detected
for i in bodies:
cv.Rectangle(
image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
detected = True
is_face = False
else:
detected = False
is_face = False
# release resources we don't need any more
cv.ReleaseImage(grayscale)
cv.ReleaseMemStorage(storage)
return (detected, is_face)
#create window and move to screen position
cv.NamedWindow ('Camera', cv.WINDOW_AUTOSIZE)
if len (sys.argv) == 1:
# no argument on the command line, try to use the camera
capture = cv.CreateCameraCapture (0)
#
### check that capture device is OK
if not capture:
print "Error opening capture device"
sys.exit (1)
#
### capture the 1st frame to get some propertie on it
frame = cv.QueryFrame (capture)
#
### get size of the frame
frame_size = cv.GetSize (frame)
gray = cv.CreateImage( frame_size, 8, 1 )
small_img = cv.CreateImage( cv.Size( int(frame_size.width/image_scale),int(frame_size.height/image_scale)), 8, 1 )
cascade = cv.LoadHaarClassifierCascade( cascade_name, cv.Size(1,1) )
#
while 1: # do forever
# capture the current image
frame = cv.QueryFrame (capture)
if frame is None:
# no image captured... end the processing
break
#
### check OS
if (osName == "nt"):
cv.Flip(frame, frame, 0)
else:
def detect(image):
image_size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(image_size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect objects
cascade = cv.LoadHaarClassifierCascade('haarcascade_frontalface_alt.xml',
cv.Size(1, 1))
faces = cv.HaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.HAAR_DO_CANNY_PRUNING, cv.Size(50, 50))
if faces:
print 'face detected!'
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
# create windows
cv.NamedWindow('Camera', cv.WINDOW_AUTOSIZE)
# create capture device
device = 0 # assume we want first device
capture = cv.CreateCameraCapture(0)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_WIDTH, 640)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_HEIGHT, 480)
# check if capture device is OK
if not capture:
print "Error opening capture device"
sys.exit(1)
while 1:
# do forever
# capture the current frame
frame = cv.QueryFrame(capture)
if frame is None:
break
# mirror
cv.Flip(frame, None, 1)
# face detection
detect(frame)
# display webcam image
cv.ShowImage('Camera', frame)
# handle events
k = cv.WaitKey(10)
if k == 0x1b: # ESC
print 'ESC pressed. Exiting ...'
break