def read_and_crop_cv2_img(path):
'''
Read color images
:param path: Path to image
:return: Only returns color images
'''
img = cv2.imread(path, -1)
if img is not None:
if len(img.shape) != 3:
return None
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
'''bbs = cnn_face_detector(img, 1)
if len(bbs) > 0:
r = bbs[0].rect
x = int(r.left())
y = int(r.top())
right = int(r.right())
bottom = int(r.bottom())
#y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
img = face_utils.crop_face_with_bb(img, bb)'''
bbs = face_recognition.face_locations(img)
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
img = face_utils.crop_face_with_bb(img, bb)
return img
def _img_morph(self, img, expresion):
bbs = face_recognition.face_locations(img)
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
face = face_utils.crop_face_with_bb(img, bb)
face = face_utils.resize_face(face)
else:
face = face_utils.resize_face(img)
morphed_face = self._morph_face(face, expresion)
return morphed_face
def _img_morph(self, img, expresion):
bbs = face_recognition.face_locations(img)
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
face = face_utils.crop_face_with_bb(img, bb)
face = face_utils.resize_face(face)
else:
face = face_utils.resize_face(img)
morphed_face = self._morph_face(face, expresion)
return morphed_face
def modify_face(self, img, expresion):
# get face part
bbs = face_recognition.face_locations(img)
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
face = face_utils.crop_face_with_bb(img, bb)
face = face_utils.resize_face(face)
else:
face = face_utils.resize_face(img) # 128x128
# modify face by expression
morphed_face = self._morph_face(face, expresion)
return morphed_face
def _img_morph(self, img, expression):
bbs = face_recognition.face_locations(img)
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
bb = x, y, (right - x), (bottom - y)
face = face_utils.crop_face_with_bb(img, bb)
face = face_utils.resize_face(face)
else:
face = face_utils.resize_face(img)
img_cond = self.find_disriminator_regression(face)
print('from discriminator: ', img_cond)
morphed_face = self._morph_face(face, expression, img_cond)
return morphed_face