【围观】麒麟芯片遭打压成绝版，华为亿元投入又砸向了哪里？>>>
1.检测脸部 def read_im_and_landmarks(fname): if not osp.exists(fname): raise Exception('Cannot find image file: {}'.format(fname)) im = cv2.imread(fname, cv2.IMREAD_COLOR) im = cv2.resize(im, (im.shape[1] * SCALE_FACTOR, im.shape[0] * SCALE_FACTOR)) s = get_landmarks(im) return im, s
2.校正脸部 def calibrate(frame): frame_new = numpy.clip(frame,0,255) frame_new = numpy.uint8(frame_new) frame_new = cv2.cvtColor(frame_new,cv2.COLOR_BGR2RGB) dets = predictor_calibrate(frame_new, 1) num_faces = len(dets) if num_faces == 0: print("Sorry, there were no faces found in current frame") return None faces = dlib.full_object_detections() for detection in dets: faces.append(sp(frame_new, detection)) images = dlib.get_face_chips(frame_new, faces, size=150) return images

3.脸部分割效果：

4.脸部校正效果