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  1. ROI_min_blue_crop = self.crop_image_to_box_region(ROI_min_blue, mask=True)
  2.         if ROI_min_blue_crop is not None:
  3.             ROI_min_blue = ROI_min_blue_crop
  4.  
  5.  
  6.         im2 = np.mean(ROI_min_blue, axis=2)
  7.         im2 = [im2, im2, im2]
  8.         im2 = np.stack(im2, axis=2)
  9.         ROI_min_blue[im2 > 100] = 0
  10.         im2 = np.subtract(ROI_min_blue, im2)
  11.         im2 = np.abs(im2)
  12.         im1 = np.mean(im2, axis=2)
  13.         im2 = [im1,im1,im1]
  14.         im2 = np.stack(im2, axis=2)
  15.         ROI_min_blue[im2 > 12] = 0
  16.         ROI_min_blue_mask = self.threshold_color(ROI_min_blue, self.white_threshold_values)
  17.         ROI_min_blue = cv2.bitwise_and(ROI_min_blue, cv2.cvtColor(ROI_min_blue_mask, cv2.COLOR_GRAY2RGB))
  18.         ROI_gray = cv2.cvtColor(ROI_min_blue, cv2.COLOR_RGB2GRAY)
  19.  
  20.         sumGray = np.sum(ROI_gray)
  21.         #print("Gray= " + str(sumGray))
  22.  
  23.         colorHist = [sumGray, sumRed, sumBlue]
  24.         classify = self.threshold_hist(colorHist)
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