application_inception_resnet_v2

Inception-ResNet v2 model, with weights trained on ImageNet

Description

Inception-ResNet v2 model, with weights trained on ImageNet

Usage

 
application_inception_resnet_v2( 
  include_top = TRUE, 
  weights = "imagenet", 
  input_tensor = NULL, 
  input_shape = NULL, 
  pooling = NULL, 
  classes = 1000, 
  classifier_activation = "softmax", 
  ... 
) 
 
inception_resnet_v2_preprocess_input(x)

Arguments

Arguments	Description
include_top	Whether to include the fully-connected layer at the top of the network. Defaults to `TRUE`.
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 `(299, 299, 3)`. It should have exactly 3 inputs channels, and width and height should be no smaller than 71. E.g. `(150, 150, 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"`.
…	For backwards and forwards compatibility
x	`preprocess_input()` takes an array or floating point tensor, 3D or 4D with 3 color channels, with values in the range `[0, 255]`.

Details

Do note that the input image format for this model is different than for the VGG16 and ResNet models (299x299 instead of 224x224). The inception_resnet_v2_preprocess_input() function should be used for image preprocessing.

Section

Reference

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning(https://arxiv.org/abs/1512.00567)

Value

A Keras model instance.