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

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].

Value

A Keras model instance.

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.