from CVtypes import cv
win = 'Show Cam'
cv.NamedWindow(win)
cap = cv.CreateCameraCapture(0)
while cv.WaitKey(1) != 27:
img = cv.QueryFrame(cap)
cv.ShowImage(win, img)
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:
cv.Flip(frame, None, 1)
#
### detecting faces here
detect_and_draw(frame, cascade)
#
### handle key events
k = cv.WaitKey (5)
if k % 0x100 == 27:
# user has press the ESC key, so exit
cv.DestroyWindow('Camera');
break
cv.SetZero(histimg)
# compute the width for each bin do display
bin_w = histimg[0].width / hdims
for i in range(hdims):
# for all the bins
# get the value, and scale to the size of the hist image
val = int(
round(cv.GetReal1D(hist[0].bins, i) * histimg[0].height / 255))
# compute the color
color = hsv2rgb(i * 180. / hdims)
# draw the rectangle in the wanted color
cv.Rectangle(histimg, cv.Point(i * bin_w, histimg[0].height),
cv.Point((i + 1) * bin_w, histimg[0].height - val),
color, -1, 8, 0)
# we can now display the images
cv.ShowImage('Camera', frame)
cv.ShowImage('Histogram', histimg)
# handle events
k = cv.WaitKey(10)
if k == 0x1b:
# user has press the ESC key, so exit
break
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
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
# 02110-1301, USA.
import sys
from CVtypes import cv
from facedetection import FaceDetector
d = FaceDetector(show_cam=True)
key = 0
escape = 27
while key != escape:
(present, is_face) = d.fetch_and_detect()
if present:
print "Available"
else:
print "Away"
key = cv.WaitKey(1) # needed for event loop
print 'Cleaning up resources ...'
del d
print 'Done, exiting now ...'
sys.exit(0)