def __init__(self,prescale=0.25,weights=WEIGHTS,default=True):
''' Initialize the detector with default parameters. '''
# Look for very small faces
self.fd = cd.CascadeDetector(min_size=(30,30))
# Look for larger heads and shoulders
self.hd = cd.CascadeDetector(cd.UPPERBODY_MCS_CASCADE,min_size=(60,60))
# Scale
self.prescale = prescale
# Returns a detection that can be used as a default if no other detections are avalible
self.default = default
# This regression will provide a quality score for the detector.
self.quality = pv.LogisticRegression()
self.quality.params = weights
def facedetect():
faceDetector = cd.CascadeDetector()
eyeDetector = ed.FilterEyeLocator()
im = pv.Image("testImage.jpg", bw_annotate=True)
faces = faceDetector(im)
eyes = eyeDetector(im, faces)
for face, eye1, eye2 in eyes:
im.annotatePolygon(face.asPolygon(), width=4)
im.annotatePoints([eye1, eye2])
im.show(delay=0)
def pyvision_detect_faces(image):
global face_detect
if face_detect is None:
face_detect = cd.CascadeDetector()
# print "DETECTING FACES"
if not hasattr(image, "asOpenCV"):
if hasattr(image,
"shape"): # numpy ndarray, assuming it comes from cv2
image = cvu.cv2ndarray_to_iplimage(image)
image = pv.Image(image, bw_annotate=True)
faces = face_detect(image)
# print "DETECTING FACES DONE."
return faces
def test_ASEFEyeLocalization(self):
'''
This trains the FaceFinder on the scraps database.
'''
# Load a face database
ssdb = ScrapShotsDatabase()
# Create a face detector
face_detector = cd.CascadeDetector()
# Create an eye locator
eye_locator = FilterEyeLocator()
# Create an eye detection test
edt = EyeDetectionTest(name='asef_scraps')
#print "Testing..."
for face_id in ssdb.keys():
face = ssdb[face_id]
im = face.image
# Detect the faces
faces = face_detector.detect(im)
# Detect the eyes
pred_eyes = eye_locator(im,faces)
truth_eyes = [[face.left_eye,face.right_eye]]
pred_eyes = [ [leye,reye] for _,leye,reye in pred_eyes]
# Add to eye detection test
edt.addSample(truth_eyes, pred_eyes, im=im, annotate=False)
edt.createSummary()
self.assertAlmostEqual( edt.face_rate , 0.97109826589595372, delta = 0.01 ) # Updated numbers for OpenCV 2.0
self.assertAlmostEqual( edt.both25_rate , 0.82658959537572252, delta = 0.01 )
self.assertAlmostEqual( edt.both10_rate , 0.47976878612716761, delta = 0.01 )
self.assertAlmostEqual( edt.both05_rate , 0.30635838150289019, delta = 0.01 )
import pyvision as pv
import pyvision.face.CascadeDetector as cd
if __name__ == '__main__':
detector = cd.CascadeDetector()
cam = pv.Webcam()
for frame in cam:
rects = detector(frame)
for rect in rects:
frame.annotateRect(rect)
frame.show(delay=30)