def smile_detection(self):
x1,y1,x2,y2 = self.mouth_rect()
mouth_rect = self.img[y1:y2, x1:x2]
smiles = d.get('haarcascade_smile').detectMultiScale(mouth_rect, 1.1, 4)
#mouthes = d.get('haarcascade_mcs_mouth').detectMultiScale(mouth_rect, 1.5, 2)
i = None
if len(smiles) != 0:
i = self.check_mouth_distance(smiles, x1, y1)
if i != None:
self.organs_dict["smile"] = Mouth(smiles[i],True)
def face_detection(self, prev_faces):
# find faces
faces = d.get('haarcascade_frontalface_default').detectMultiScale(self.frame, 1.5, 2)
p_faces = d.get('haarcascade_profileface').detectMultiScale(self.frame, 1.85, 2)
if len(faces) == 0:
faces = p_faces
elif len(p_faces) != 0:
faces = np.concatenate((faces, p_faces), 0)
# choose the face with most face-organs
for i,face in enumerate(faces):
x,y,w,h = face.ravel()
face_object = Face(face, self.frame, prev_faces,(255,0,0))
if face_object.organs_counter > 0:
if not self.is_face_exists(face):
self.faces.append(face_object)
else:
face1,j = self.search_face(face_object)
if face_object.organs_counter > face1.organs_counter:
self.faces[j] = face_object
def eye_detection(self, p_r_eye, p_l_eye):
# define the eyes rectangle
x1 = self.x
x2 = x1 + self.w
y1 = self.y
y2 = y1 + self.h*2/3
eye_rect = self.img[y1:y2, x1:x2]
#eyes1 = d.get('haarcascade_mcs_eyepair_big').detectMultiScale(self.eye_rect, 1.2, 1)
eyes = d.get('haarcascade_eye').detectMultiScale(eye_rect, 1.1, 1)
for eye in eyes:
eye[0] += x1
eye[1] += y1
r_eye = self.search_eye(eyes,p_r_eye,p_l_eye,"r")
l_eye = self.search_eye(eyes,p_l_eye,p_r_eye,"l")
# search for eyes pair
if r_eye is None and l_eye is None:
for i,eye in enumerate(eyes):
x,y,w,h = eye.ravel()
eye_center = (x+w/2,y+h/2)
for j in range(i+1,len(eyes)):
x1,y1,w1,h1 = eyes[j].ravel()
eye1_center = (x1+w1/2,y1+h1/2)
dx = abs(x1-x)
dy = abs(y1-y)
if dx > (w+w1)/2 and dx < 2*self.w/3 and dy < (h+h1)/2:
if x < x1:
r_eye = eye
l_eye = eyes[j]
else:
r_eye = eyes[j]
l_eye = eye
if r_eye is not None:
self.organs_dict["r_eye"] = Eye(self.img,r_eye,'r')
self.organs_counter += 1
if l_eye is not None:
self.organs_dict["l_eye"] = Eye(self.img,l_eye,'l')
self.organs_counter += 1
def nose_detection(self, prev_nose,frame):
# define the nose rectangle
N = 6
x1,y1,x2,y2 = self.nose_rect(N)
nose_rect = self.img[y1:y2, x1:x2]
noses = d.get('haarcascade_mcs_nose').detectMultiScale(nose_rect, 1.2, 1)
distance = self.h
s = self.w*self.h
index = 0
for i,nose in enumerate(noses):
nose[0] += x1
nose[1] += y1
nose_d = self.w/2
new_nose = None
# search for the best nose
for nose in noses:
x,y,w,h = nose.ravel()
nose_center = (x+w/2,y+h/2)
# find nose using the previous nose location
if prev_nose is not None:
if self.is_contain_point((x,y,w,h),prev_nose):
new_d = calc_d(nose_center,prev_nose)
if new_d < nose_d:
nose_d = new_d
new_nose = nose
# find nose using the face forizontal line
else:
new_d = abs(self.y+self.h/2 - y)
if new_d < distance:
new_nose = nose
distance = new_d
if new_nose is not None:
self.organs_dict["nose"] = Nose(new_nose)
self.organs_counter += 1
self.center = self.organs_dict["nose"].get_center()
