Instantiates the Densenet169 architecture.
View aliases
Main aliases
tf.keras.applications.DenseNet169(
include_top=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
classifier_activation='softmax'
)
Reference:
- Densely Connected Convolutional Networks (CVPR 2017)
Optionally loads weights pre-trained on ImageNet.
Note that the data format convention used by the model is
the one specified in your Keras config at ~/.keras/keras.json
.
Args | |
---|---|
include_top
|
whether to include the fully-connected layer at the top of the network. |
weights
|
one of None (random initialization),
"imagenet" (pre-training on ImageNet),
or the path to the weights file to be loaded.
|
input_tensor
|
optional Keras tensor
(i.e. output of layers.Input() )
to use as image input for the model.
|
input_shape
|
optional shape tuple, only to be specified
if include_top is False (otherwise the input shape
has to be (224, 224, 3) (with 'channels_last' data format)
or (3, 224, 224) (with 'channels_first' data format).
It should have exactly 3 inputs channels,
and width and height should be no smaller than 32.
E.g. (200, 200, 3) would be one valid value.
|
pooling
|
Optional pooling mode for feature extraction
when include_top is False .
|
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.
|
classifier_activation
|
A str or callable.
The activation function to use
on the "top" layer. Ignored unless include_top=True . Set
classifier_activation=None to return the logits
of the "top" layer. When loading pretrained weights,
classifier_activation can only be None or "softmax" .
|
Returns | |
---|---|
A Keras model instance. |