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
def _overlay_fake_img(self, img, face, bbs):
overlay_copy = img
if len(bbs) > 0:
y, right, bottom, x = bbs[0]
ratio = ((bottom - y) / face.shape[0], (right - x) / face.shape[0])
face = face_utils.resize_face(face, (int(face.shape[0]*ratio[0]), int(face.shape[1]*ratio[1])))
#print(y, right, bottom, x)
#print(overlay_copy.shape)
overlay_copy[y:y + face.shape[0], x:x +face.shape[1]] = face
return overlay_copy