tf.keras.applications.EfficientNetB4

Instantiates the EfficientNetB4 architecture.

View aliases

Main aliases

tf.keras.applications.efficientnet.EfficientNetB4

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.applications.EfficientNetB4, tf.compat.v1.keras.applications.efficientnet.EfficientNetB4

tf.keras.applications.EfficientNetB4(
    include_top=True, weights='imagenet', input_tensor=None,
    input_shape=None, pooling=None, classes=1000,
    classifier_activation='softmax', **kwargs
)

Reference:

• EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (ICML 2019)

Optionally loads weights pre-trained on ImageNet. Note that the data format convention used by the model is the one specified in your Keras config at ~/.keras/keras.json. If you have never configured it, it defaults to "channels_last".

Arguments
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. Defaults to None. 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.
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. Defaults to 1000 (number of ImageNet classes).
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. Defaults to 'softmax'.

Returns
A keras.Model instance.