class_docstr: crop an image from four forwards.
  
  Args:
      up_h_off (int, optional): The cut height for image from up to down. Default: 0.
      down_h_off (int, optional): The cut height for image from down to up . Default: 0.
      left_w_off (int, optional): The cut height for image from left to right. Default: 0.
      right_w_off (int, optional): The cut width for image from right to left. Default: 0.
class_docstr_tok: ["crop","an","image","from","four","forwards",".","Args",":","up_h_off","(","int",",","optional",")",":","The","cut","height","for","image","from","up","to","down",".","Default",":","0.","down_h_off","(","int",",","optional",")",":","The","cut","height","for","image","from","down","to","up",".","Default",":","0.","left_w_off","(","int",",","optional",")",":","The","cut","height","for","image","from","left","to","right",".","Default",":","0.","right_w_off","(","int",",","optional",")",":","The","cut","width","for","image","from","right","to","left",".","Default",":","0","."]
code: def __init__(
      self,
      up_h_off: int = 0,
      down_h_off: int = 0,
      left_w_off: int = 0,
      right_w_off: int = 0,
  ):
      self.up_h_off = up_h_off
      self.down_h_off = down_h_off
      self.left_w_off = left_w_off
      self.right_w_off = right_w_off
  
file_path: PaddleHub/modules/image/semantic_segmentation/bisenet_lane_segmentation/processor.py
imports: import base64
  import collections.abc
  from itertools import combinations
  from typing import Union, List, Tuple, Callable
  import numpy
  import cv2
  import paddle
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new Crop object  with example: obj = Crop(up_h_off, down_h_off, left_w_off, right_w_off)