class_docstr: Describes backbone information and provides utility functions.
      
class_docstr_tok: ["Describes","backbone","information","and","provides","utility","functions","."]
docstr: Downloads ImageNet weights and returns path to weights file.
  Weights can be downloaded at https://github.com/fizyr/keras-models/releases .
docstr_tok: ["Downloads","ImageNet","weights","and","returns","path","to","weights","file",".","Weights","can","be","downloaded","at","https",":","\/\/github.com\/fizyr\/keras-models\/releases","."]
code: def download_imagenet(self):
      """Downloads ImageNet weights and returns path to weights file.
      Weights can be downloaded at https://github.com/fizyr/keras-models/releases .
      """
      if self.backbone == "vgg16":
          resource = keras.applications.vgg16.vgg16.WEIGHTS_PATH_NO_TOP
          checksum = "6d6bbae143d832006294945121d1f1fc"
      elif self.backbone == "vgg19":
          resource = keras.applications.vgg19.vgg19.WEIGHTS_PATH_NO_TOP
          checksum = "253f8cb515780f3b799900260a226db6"
      else:
          raise ValueError(
              "Backbone '{}' not recognized.".format(self.backbone)
          )
  
      return keras.utils.get_file(
          "{}_weights_tf_dim_ordering_tf_kernels_notop.h5".format(
              self.backbone
          ),
          resource,
          cache_subdir="models",
          file_hash=checksum,
      )
  
file_path: ImageAI/imageai_tf_deprecated/Detection/keras_retinanet/models/vgg.py
imports: from tensorflow import keras
  from .None import retinanet
  from .None import Backbone
  from ..utils.image import preprocess_image
label_desc: Use image node_id 2 for calling the VGGBackbone obj's underlying member method code with example usage: obj.download_imagenet() and returns: keras