application_vgg: VGG16 and VGG19 models for Keras.

In keras: R Interface to 'Keras'

VGG16 and VGG19 models for Keras.

Description

VGG16 and VGG19 models for Keras.

Usage

application_vgg16(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000,
  classifier_activation = "softmax"
)

application_vgg19(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000,
  classifier_activation = "softmax"
)

Arguments

include_top	whether to include the 3 fully-connected layers 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. Defaults to 'imagenet'.
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)⁠ It should have exactly 3 inputs channels, and width and height should be no smaller than 32. E.g. ⁠(200, 200, 3)⁠ would be one valid value.
pooling	Optional pooling mode for feature extraction when include_top is FALSE. Defaults to NULL. 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. Defaults to 1000 (number of ImageNet classes).
classifier_activation	A string or callable. The activation function to use on the "top" layer. Ignored unless include_top = TRUE. Set classifier_activation = NULL to return the logits of the "top" layer. Defaults to 'softmax'. When loading pretrained weights, classifier_activation can only be NULL or "softmax".

Details

Optionally loads weights pre-trained on ImageNet.

The imagenet_preprocess_input() function should be used for image preprocessing.

Value

Keras model instance.

Reference

- Very Deep Convolutional Networks for Large-Scale Image Recognition

Examples

## Not run: 
library(keras)

model <- application_vgg16(weights = 'imagenet', include_top = FALSE)

img_path <- "elephant.jpg"
img <- image_load(img_path, target_size = c(224,224))
x <- image_to_array(img)
x <- array_reshape(x, c(1, dim(x)))
x <- imagenet_preprocess_input(x)

features <- model %>% predict(x)

## End(Not run)

keras documentation built on May 29, 2024, 3:20 a.m.