tf.keras.applications.regnet.RegNetY006

Instantiates the RegNetY006 architecture.

tf.keras.applications.regnet.RegNetY006(
    model_name='regnety006',
    include_top=True,
    include_preprocessing=True,
    weights='imagenet',
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000,
    classifier_activation='softmax'
)

For image classification use cases, see this page for detailed examples.

For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning.

The naming of models is as follows: RegNet<block_type><flops> where block_type is one of (X, Y) and flops signifies hundred million floating point operations. For example RegNetY064 corresponds to RegNet with Y block and 6.4 giga flops (64 hundred million flops).

include_top Whether to include the fully-connected layer at the top of the network. Defaults to True.
weights One of None (random initialization), "imagenet" (pre-training on ImageNet), or the path to the weights file to be loaded. Defaults to "imagenet".
input_tensor Optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model.
input_shape Optional shape tuple, only to be specified if include_top is False. It should have exactly 3 inputs channels.
pooling Optional pooling mode for feature extraction when include_top is False.

  • None means that the output of the model will be the 4D tensor output of the last convolutional layer.
  • avg means that global average pooling will be applied to the output of the last convolutional layer, and thus the output of the model will be a 2D tensor.
  • max means that global max pooling will be applied. Defaults to None.
classes Optional number of classes to classify images into, only to be specified if include_top is True, and if no weights argument is specified. 1000 is how many ImageNet classes there are. Defaults to 1000.
classifier_activation A str or callable. The activation function to use on the "top" layer. Ignored unless include_top=True. Set classifier_activation=None to return the logits of the "top" layer. When loading pretrained weights, classifier_activation can only be None or "softmax". Defaults to "softmax".

A keras.Model instance.