def cutFace(real_path, face, img):
box = numpy.int0([[face.left(), face.top()], [face.right(),
face.top()],
[face.right(), face.bottom()],
[face.left(), face.bottom()]])
points = common.cutImg("face.jpg", real_path, box,
(face.right() - face.left()),
(face.bottom() - face.top()), 1.1, img)
return points
def cutBrow(shape, img, real_path):
# Save the feature points to array
brow = numpy.array([[shape.part(17).x, shape.part(17).y],
[shape.part(18).x, shape.part(18).y],
[shape.part(19).x, shape.part(19).y],
[shape.part(20).x, shape.part(20).y],
[shape.part(21).x, shape.part(21).y],
[shape.part(22).x, shape.part(22).y],
[shape.part(23).x, shape.part(23).y],
[shape.part(24).x, shape.part(24).y],
[shape.part(25).x, shape.part(25).y],
[shape.part(26).x, shape.part(26).y]
], numpy.int32)
# Get the minimum rectangle
rect = cv2.minAreaRect(brow)
box = cv2.boxPoints(rect)
box = numpy.int0(box)
# Cut eyebrows from iamge
points = common.cutImg("brow.jpg", real_path, box, 7, 1 , 1.1, img)
return points
def cutLip(real_path, box, img):
points = common.cutImg("lip.jpg", real_path, box, 21, 9, 1.5, img)
return points
def cutRightEye(real_path, box, img):
points = common.cutImg("right_eye.jpg", real_path, box, 16, 9, 1.5, img)
return points