application_densenet: Instantiates the DenseNet architecture.

Description Usage Arguments Details

View source: R/applications.R

Description

Instantiates the DenseNet architecture.

Usage

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application_densenet(
  blocks,
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000
)

application_densenet121(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000
)

application_densenet169(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000
)

application_densenet201(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000
)

densenet_preprocess_input(x, data_format = NULL)

Arguments

blocks

numbers of building blocks for the four dense layers.

include_top

whether to include the fully-connected layer at the top of the network.

weights

one of NULL (random initialization), 'imagenet' (pre-training on ImageNet), or the path to the weights file to be loaded.

input_tensor

optional Keras tensor (i.e. output of layer_input()) to use as image input for the model.

input_shape

optional shape list, only to be specified if include_top is FALSE (otherwise the input shape has to be (224, 224, 3) (with channels_last data format) or (3, 224, 224) (with channels_first data format). It should have exactly 3 inputs channels.

pooling

optional pooling mode for feature extraction when include_top is FALSE. - NULL 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.

x

a 3D or 4D array consists of RGB values within [0, 255].

data_format

data format of the image tensor.

Details

Optionally loads weights pre-trained on ImageNet. Note that when using TensorFlow, for best performance you should set image_data_format='channels_last' in your Keras config at ~/.keras/keras.json.

The model and the weights are compatible with TensorFlow, Theano, and CNTK. The data format convention used by the model is the one specified in your Keras config file.


keras documentation built on Feb. 10, 2022, 1:08 a.m.