r,g,b,a = cv2.split(hat_img) 
rgb_hat = cv2.merge((r,g,b))

cv2.imwrite("hat_alpha.jpg",a)

 # dlib人臉關(guān)鍵點(diǎn)檢測(cè)器
 predictor_path = "shape_predictor_5_face_landmarks.dat"
 predictor = dlib.shape_predictor(predictor_path) 

 # dlib正臉檢測(cè)器
 detector = dlib.get_frontal_face_detector()

 # 正臉檢測(cè)
 dets = detector(img, 1)

 # 如果檢測(cè)到人臉
 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)

   # 關(guān)鍵點(diǎn)檢測(cè)，5個(gè)關(guān)鍵點(diǎn)
   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() 

# 選取左右眼眼角的點(diǎn)
 point1 = shape.part(0)
 point2 = shape.part(2)

 # 求兩點(diǎn)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()

 # 根據(jù)人臉大小調(diào)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

 # 根據(jù)人臉大小調(diào)整帽子大小
resized_hat = cv2.resize(rgb_hat,(resized_hat_w,resized_hat_h))

# 用alpha通道作為mask
mask = cv2.resize(a,(resized_hat_w,resized_hat_h))
mask_inv = cv2.bitwise_not(mask)

 # 帽子相對(duì)與人臉框上線的偏移量
 dh = 0
 dw = 0
 # 原圖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)]

 # 原圖ROI中提取放帽子的區(qū)域
 bg_roi = bg_roi.astype(float)
 mask_inv = cv2.merge((mask_inv,mask_inv,mask_inv))
 alpha = mask_inv.astype(float)/255

 # 相乘之前保證兩者大小一致（可能會(huì)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')

# 提取帽子區(qū)域
hat = cv2.bitwise_and(resized_hat,resized_hat,mask = mask)

# 相加之前保證兩者大小一致（可能會(huì)由于四舍五入原因不一致）
  hat = cv2.resize(hat,(bg_roi.shape[1],bg_roi.shape[0]))
  # 兩個(gè)ROI區(qū)域相加
  add_hat = cv2.add(bg,hat)
  # cv2.imshow("add_hat",add_hat) 

  # 把添加好帽子的區(qū)域放回原圖
 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