application_inception_v3: Inception V3 model, with weights pre-trained on ImageNet.

In keras: R Interface to 'Keras'

Inception V3 model, with weights pre-trained on ImageNet.

Description

Inception V3 model, with weights pre-trained on ImageNet.

Usage

application_inception_v3(
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  input_shape = NULL,
  pooling = NULL,
  classes = 1000,
  classifier_activation = "softmax",
  ...
)

inception_v3_preprocess_input(x)

Arguments

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_v3_preprocess_input() function should be used for image preprocessing.

Value

A Keras model instance.

Reference

• Rethinking the Inception Architecture for Computer Vision

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