class_docstr: The ILSVRC12 classification dataset, aka the commonly used 1000 classes ImageNet subset.
  This dataflow produces uint8 images of shape [h, w, 3(BGR)], and a label between [0, 999].
  The label map follows the synsets.txt file in
  http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz,
  which can also be queried using :class:`ILSVRCMeta`.
class_docstr_tok: ["The","ILSVRC12","classification","dataset",",","aka","the","commonly","used","1000","classes","ImageNet","subset",".","This","dataflow","produces","uint8","images","of","shape","[","h",",","w",",","3","(","BGR",")","]",",","and","a","label","between","[","0",",","999","]",".","The","label","map","follows","the","synsets.txt","file","in","http",":","\/\/dl.caffe.berkeleyvision.org\/caffe_ilsvrc12.tar.gz",",","which","can","also","be","queried","using",":","class",":","`","ILSVRCMeta","`","."]
code: def __iter__(self):
      for fname, label in super(ILSVRC12, self).__iter__():
          im = cv2.imread(fname, cv2.IMREAD_COLOR)
          assert im is not None, fname
          yield [im, label]
  
imports: import numpy
  import os
  import tarfile
  import tqdm
  from pathlib import Path
  from ...utils import logger
  from ...utils.fs import download, get_dataset_path, mkdir_p
  from ...utils.loadcaffe import get_caffe_pb
  from ...utils.timer import timed_operation
  from ..base import RNGDataFlow
label_desc: Use image node_id 2 for calling the ILSVRC12 obj's underlying member method code with example usage: obj.__iter__() without return types