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",
name = "inception_v3"
)
Arguments
include_top |
Boolean, whether to include the fully-connected
layer at the top, as the last layer of the network.
Defaults to |
weights |
One of |
input_tensor |
Optional Keras tensor (i.e. output of |
input_shape |
Optional shape tuple, only to be specified
if |
pooling |
Optional pooling mode for feature extraction
when
|
classes |
optional number of classes to classify images
into, only to be specified if |
classifier_activation |
A |
name |
The name of the model (string). |
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
.