class_docstr: Only calculate the unknown region if trimap provided.
  Refer to: https://github.com/open-mlab/mmediting/blob/master/mmedit/core/evaluation/metrics.py
code: def gauss_filter(self, sigma, epsilon=1e-2):
      half_size = np.ceil(
          sigma
          * np.sqrt(-2 * np.log(np.sqrt(2 * np.pi) * sigma * epsilon))
      )
      size = int(2 * half_size + 1)
  
      # create filter in x axis
      filter_x = np.zeros((size, size))
      for i in range(size):
          for j in range(size):
              filter_x[i, j] = self.gaussian(
                  i - half_size, sigma
              ) * self.dgaussian(j - half_size, sigma)
  
      # normalize filter
      norm = np.sqrt((filter_x**2).sum())
      filter_x = filter_x / norm
      filter_y = np.transpose(filter_x)
  
      return filter_x, filter_y
  
imports: import cv2
  import numpy
  from scipy.ndimage.filters import convolve
  from scipy.special import gamma
  from skimage.measure import label
label_desc: Use image node_id 4 for calling the Grad obj's underlying member method code with example usage: obj.gauss_filter(sigma, epsilon) and returns: filter_x,  filter_y