class_docstr: Remove the padding values.
  
  Args:
      stride(int): Scales for resizing the images.
code: def __call__(
      self,
      data: np.ndarray,
      imageToTest_padded: np.ndarray,
      oriImg: np.ndarray,
      pad: list,
  ) -> np.ndarray:
      heatmap = np.transpose(np.squeeze(data), (1, 2, 0))
      heatmap = cv2.resize(
          heatmap,
          (0, 0),
          fx=self.stride,
          fy=self.stride,
          interpolation=cv2.INTER_CUBIC,
      )
      heatmap = heatmap[
          : imageToTest_padded.shape[0] - pad[2],
          : imageToTest_padded.shape[1] - pad[3],
          :,
      ]
      heatmap = cv2.resize(
          heatmap,
          (oriImg.shape[1], oriImg.shape[0]),
          interpolation=cv2.INTER_CUBIC,
      )
  
      return heatmap
  
imports: import base64
  import math
  from typing import Callable
  import cv2
  import numpy
  from scipy.ndimage import gaussian_filter
label_desc: Use image node_id 2 for calling the RemovePadding obj's underlying member method code with example usage: obj.__call__(data, imageToTest_padded, oriImg, pad) and returns: heatmap