r,g,b,a = cv2.split(hat_img) 
 rgb_hat = cv2.merge((r,g,b))
 cv2.imwrite("hat_alpha.jpg",a)

# dlib人脸关键点检测器 predictor_path = "shape_predictor_5_face_landmarks.dat" predictor = dlib.shape_predictor(predictor_path)

 # dlib正脸检测器
 detector = dlib.get_frontal_face_detector()

 # 正脸检测
 dets = detector(img, 1)

 # 如果检测到人脸
 if len(dets)>0: 
   for d in dets:
     x,y,w,h = d.left(),d.top(), d.right()-d.left(), d.bottom()-d.top()
     # x,y,w,h = faceRect 
     cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2,8,0)

     # 关键点检测，5个关键点
     shape = predictor(img, d)
     for point in shape.parts():
       cv2.circle(img,(point.x,point.y),3,color=(0,255,0))

     cv2.imshow("image",img)
     cv2.waitKey() 

# 选取左右眼眼角的点 point1 = shape.part(0) point2 = shape.part(2)
     # 求两点中心
     eyes_center = ((point1.x+point2.x)//2,(point1.y+point2.y)//2)
     # cv2.circle(img,eyes_center,3,color=(0,255,0)) 
     # cv2.imshow("image",img)
     # cv2.waitKey()
     # 根据人脸大小调整帽子大小
     factor = 1.5
     resized_hat_h = int(round(rgb_hat.shape[0]*w/rgb_hat.shape[1]*factor))
     resized_hat_w = int(round(rgb_hat.shape[1]*w/rgb_hat.shape[1]*factor))
     if resized_hat_h > y:
       resized_hat_h = y-1
     # 根据人脸大小调整帽子大小
     resized_hat = cv2.resize(rgb_hat,(resized_hat_w,resized_hat_h))

     mask = cv2.resize(a,(resized_hat_w,resized_hat_h))
     mask_inv = cv2.bitwise_not(mask)

# 帽子相对与人脸框上线的偏移量 dh = 0 dw = 0 # 原图ROI # bg_roi = img[y+dh-resized_hat_h:y+dh, x+dw:x+dw+resized_hat_w] bg_roi = img[y+dh-resized_hat_h:y+dh,(eyes_center[0]-resized_hat_w//3):(eyes_center[0]+resized_hat_w//3*2)]
     # 原图ROI中提取放帽子的区域
     bg_roi = bg_roi.astype(float)
     mask_inv = cv2.merge((mask_inv,mask_inv,mask_inv))
     alpha = mask_inv.astype(float)/255

     # 相乘之前保证两者大小一致（可能会由于四舍五入原因不一致）
     alpha = cv2.resize(alpha,(bg_roi.shape[1],bg_roi.shape[0]))
     # print("alpha size: ",alpha.shape)
     # print("bg_roi size: ",bg_roi.shape)
     bg = cv2.multiply(alpha, bg_roi)
     bg = bg.astype('uint8')

# 提取帽子区域 hat = cv2.bitwise_and(resized_hat,resized_hat,mask = mask)

# 相加之前保证两者大小一致（可能会由于四舍五入原因不一致） hat = cv2.resize(hat,(bg_roi.shape1,bg_roi.shape[0])) # 两个ROI区域相加 add_hat = cv2.add(bg,hat) # cv2.imshow("add_hat",add_hat)
     # 把添加好帽子的区域放回原图
     img[y+dh-resized_hat_h:y+dh,(eyes_center[0]-resized_hat_w//3):(eyes_center[0]+resized_hat_w//3*2)] = add_hat