拿到一张图片后，想不采用机器学习就对其高光部分进行识别，采取 Specular Reflections Removal for Endoscopic Image Sequences With Adaptive-Rpca Decomposition 提出的方法，得到高光掩码矩阵，设定阈值后即可判定高光部分

# 设置的参数
threshold = 0.5 # 0-1之间
area = 0.01 # 高光的占比
ts = 0.35
tv = 0.85
def function_A(x):
  return (1-np.exp(-2*pow(np.maximum(x, 0),2)/(0.01)))
def function_B(x):
  return 1-np.exp(-2*pow(np.maximum(x, 0),2)/(0.01))
def function_C(x):
  return (ts - x/256)
def function_D(x):
  return (x/256 - tv)
def test(x):
  return x * 256

def detect_highlight(path):
  img = cv2.imread(path)
  size = img.shape
  w = size[1]
  h = size[0]
  # Convert BGR to HSV
  hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
  saturation=hsv[:,:,1]
  value=hsv[:,:,2]
  a = function_A(function_C(saturation))
  b = function_B(function_D(value))

  res = a*b
  return res