class_docstr: Crop images at the center to have a region of
  the given size. size can be a tuple (target_height, target_width)
  or an integer, in which case the target will be of a square shape (size, size)
  
  Parameters:
  ----------
  size : int
      height and width required by network input, e.g., (224, 224)
  
  Inputs:
      - **data**: a list of frames with shape [H x W x C]
  
  Outputs:
      - **out**: a list of cropped frames with shape [size x size x C]
class_docstr_tok: ["Crop","images","at","the","center","to","have","a","region","of","the","given","size",".","size","can","be","a","tuple","(","target_height",",","target_width",")","or","an","integer",",","in","which","case","the","target","will","be","of","a","square","shape","(","size",",","size",")","Parameters",":","--","--","--","--","--","size",":","int","height","and","width","required","by","network","input",",","e.g.",",","(","224",",","224",")","Inputs",":","-","*","*","data","*","*",":","a","list","of","frames","with","shape","[","H","x","W","x","C","]","Outputs",":","-","*","*","out","*","*",":","a","list","of","cropped","frames","with","shape","[","size","x","size","x","C","]"]
code: def __init__(self, size):
      super(VideoCenterCrop, self).__init__()
      if isinstance(size, numbers.Number):
          self.size = (int(size), int(size))
      else:
          self.size = size
  
imports: from __future__ import division
  import random
  import math
  import numbers
  import numpy
  from mxnet.gluon import Block
label_desc: Use image node_id 1 to create a new VideoCenterCrop object from inherited base classes: Block with example: obj = VideoCenterCrop(size)