code: def crop(image, center, scale, resolution=256.0):
      """Center crops an image or set of heatmaps
  
      Arguments:
          image {numpy.array} -- an rgb image
          center {numpy.array} -- the center of the object, usually the same as of the bounding box
          scale {float} -- scale of the face
  
      Keyword Arguments:
          resolution {float} -- the size of the output cropped image (default: {256.0})
  
      Returns:
          [type] -- [description]
      """  # Crop around the center point
      """ Crops the image around the center. Input is expected to be an np.ndarray """
      ul = transform([1, 1], center, scale, resolution, True)
      br = transform(
          [resolution, resolution], center, scale, resolution, True
      )
      # pad = math.ceil(torch.norm((ul - br).float()) / 2.0 - (br[0] - ul[0]) / 2.0)
      if image.ndim > 2:
          newDim = np.array(
              [br[1] - ul[1], br[0] - ul[0], image.shape[2]],
              dtype=np.int32,
          )
          newImg = np.zeros(newDim, dtype=np.uint8)
      else:
          newDim = np.array(
              [br[1] - ul[1], br[0] - ul[0]], dtype=np.int
          )
          newImg = np.zeros(newDim, dtype=np.uint8)
      ht = image.shape[0]
      wd = image.shape[1]
      newX = np.array(
          [max(1, -ul[0] + 1), min(br[0], wd) - ul[0]], dtype=np.int32
      )
      newY = np.array(
          [max(1, -ul[1] + 1), min(br[1], ht) - ul[1]], dtype=np.int32
      )
      oldX = np.array(
          [max(1, ul[0] + 1), min(br[0], wd)], dtype=np.int32
      )
      oldY = np.array(
          [max(1, ul[1] + 1), min(br[1], ht)], dtype=np.int32
      )
      newImg[newY[0] - 1 : newY[1], newX[0] - 1 : newX[1]] = image[
          oldY[0] - 1 : oldY[1], oldX[0] - 1 : oldX[1], :
      ]
      newImg = cv2.resize(
          newImg,
          dsize=(int(resolution), int(resolution)),
          interpolation=cv2.INTER_LINEAR,
      )
      return newImg
  
imports: import os
  import sys
  import errno
  import torch
  import math
  import numpy
  import cv2
  from skimage import io
  from skimage import color
  from numba import jit
  from urllib.parse import urlparse
  from torch.hub import download_url_to_file, HASH_REGEX
label_desc: Use image node_id 4 for calling a global function with example usage: crop(image, center, scale, resolution) and returns: newImg