application_inception_v3 {keras} | R Documentation |
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
[Package
keras version 2.15.0
Index]