R/applications.R

application_vgg

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

Arguments Description
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.

Section

Reference

Value

Keras model instance.

Examples

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)