tf.keras.applications.DenseNet121
tf.keras.applications.densenet.DenseNet121
tf.keras.applications.DenseNet121( include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000 )
Defined in tensorflow/python/keras/_impl/keras/applications/densenet.py
.
Instantiates the DenseNet architecture.
Optionally loads weights pre-trained on ImageNet. Note that when using TensorFlow, for best performance you should set image_data_format='channels_last'
in your Keras config at ~/.keras/keras.json.
The model and the weights are compatible with TensorFlow, Theano, and CNTK. The data format convention used by the model is the one specified in your Keras config file.
blocks
: numbers of building blocks for the four dense layers.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.pooling
: optional pooling mode for feature extraction when include_top
is False
. - None
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.A Keras model instance.
ValueError
: in case of invalid argument for weights
, or invalid input shape.
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/applications/DenseNet121