application_inception_v3 {keras3} | R Documentation |
Instantiates the Inception v3 architecture.
Description
Instantiates the Inception v3 architecture.
Usage
application_inception_v3(
include_top = TRUE,
weights = "imagenet",
input_tensor = NULL,
input_shape = NULL,
pooling = NULL,
classes = 1000L,
classifier_activation = "softmax"
)
Arguments
include_top |
Boolean, whether to include the fully-connected
layer at the top, as the last layer 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 layers.Input() )
to use as image input for the model. input_tensor is useful for
sharing inputs between multiple different networks.
Defaults to NULL .
|
input_shape |
Optional shape tuple, only to be specified
if include_top is FALSE (otherwise the input shape
has to be (299, 299, 3) (with channels_last data format)
or (3, 299, 299) (with channels_first data format).
It should have exactly 3 inputs channels,
and width and height should be no smaller than 75.
E.g. (150, 150, 3) would be one valid value.
input_shape will be ignored if the input_tensor is provided.
|
pooling |
Optional pooling mode for feature extraction
when include_top is FALSE .
-
NULL (default) means that the output of the model will be
the 4D tensor output of the last convolutional block.
-
avg means that global average pooling
will be applied to the output of the
last convolutional block, 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.
|
classifier_activation |
A str 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. When loading pretrained weights, classifier_activation
can only be NULL or "softmax" .
|
Value
A model instance.
Reference
This function returns a Keras image classification model,
optionally loaded with weights pre-trained on ImageNet.
For image classification use cases, see
this page for detailed examples.
For transfer learning use cases, make sure to read the
guide to transfer learning & fine-tuning.
Note
Each Keras Application expects a specific kind of input preprocessing.
For InceptionV3
, call
application_preprocess_inputs()
on your inputs
before passing them to the model.
application_preprocess_inputs()
will scale input pixels between -1
and 1
.
See Also
[Package
keras3 version 1.0.0
Index]