code: def verify_apply_bounding_box(img, box):
      import skimage.util
  
      if any(
          type(box[f]) is not int or np.isnan(box[f] or box[f] < 0)
          for f in range(0, 4)
      ):
          return img
      # Box is ymin, xmin, bound_height, bound_width
      y_bounds = (box[0], img.shape[0] - box[0] - box[2])
      x_bounds = (box[1], img.shape[1] - box[1] - box[3])
      c_bounds = (0, 0)
  
      if any(
          el < 0
          for el in list(y_bounds) + list(x_bounds) + list(c_bounds)
      ):
          return img
  
      bboxed = skimage.util.crop(img, (y_bounds, x_bounds, c_bounds))
      return bboxed
  
imports: import unittest
  from PIL import Image
  import numpy
  import shutil
  import io
  import sys
  import tempfile
  from hypothesis import given, settings, Verbosity
  import hypothesis.strategies
  from caffe2.proto import caffe2_pb2
  import caffe2.python.hypothesis_test_util
  from caffe2.python import workspace, core
label_desc: Use image node_id 1 for calling a global function with example usage: verify_apply_bounding_box(img, box) and returns: bboxed, img, img