code: def get_closer(img):
      rows = []
      cols = []
      for x in range(16):
          no = 0
          for col in range(
              x * img.shape[0] // 16, (x + 1) * img.shape[0] // 16
          ):
              for row in range(img.shape[1]):
                  if img[col][row] == 0:
                      no += 1
          if no >= 0.01 * img.shape[1] * img.shape[0] // 16:
              rows.append(x * img.shape[0] // 16)
      for x in range(16):
          no = 0
          for row in range(
              x * img.shape[1] // 16, (x + 1) * img.shape[1] // 16
          ):
              for col in range(img.shape[0]):
                  if img[col][row] == 0:
                      no += 1
          if no >= 0.01 * img.shape[0] * img.shape[1] // 16:
              cols.append(x * img.shape[1] // 16)
      new_img = img[
          rows[0] : min(img.shape[0], rows[-1] + img.shape[0] // 16),
          cols[0] : min(img.shape[1], cols[-1] + img.shape[1] // 16),
      ]
      return new_img
  
file_path: Mozart/src/pre_processing.py
imports: from commonfunctions import *
  from skimage.transform import probabilistic_hough_line, hough_line, rotate, hough_line_peaks
  from skimage.feature import corner_harris
  import cv2
  from staff import *
label_desc: Use image node_id 3 for calling a global function with example usage: get_closer(img) and returns: new_img