Instantiates the Densenet121 architecture.
application_densenet121(
include_top = TRUE,
weights = "imagenet",
input_tensor = NULL,
input_shape = NULL,
pooling = NULL,
classes = 1000L,
classifier_activation = "softmax",
name = "densenet121"
)A Keras model instance.
whether to include the fully-connected layer at the top of the network.
one of NULL (random initialization),
"imagenet" (pre-training on ImageNet),
or the path to the weights file to be loaded.
optional Keras tensor
(i.e. output of keras_input())
to use as image input for the model.
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.
Optional pooling mode for feature extraction
when include_top is FALSE.
NULL 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.
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.
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".
The name of the model (string).
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.