DenseNet

applications.densenet.DenseNet121

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applications.densenet.DenseNet121(
    include_top=True, weights='hasc', input_shape=None, 
    pooling=None, classes=6, classifier_activation='softmax')

Reference: - Densely Connected Convolutional Networks (CVPR 2017)

By default, it loads weights pre-trained on HASC. Check 'weights' for other options.

The default input size for this model is 768 (256 * 3).

Arguments

include_top : whether to include the fully-connected layer at the top of the network.
weights : one of 'None' (random initialization), 'hasc' (pre-training on HASC), or the path to the weights file to be loaded.
input_shape : optional shape tuple, default (768, 1) (with channels_last data format).
pooling : optional pooling mode for feature extraction when include_top is False.
- None means that the output of the model will be applied to the 3D tensor output of the last convolutional block.
- avg means that global average pooling will be applied to the output of the last convolutioinal block, 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, default 6.
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, default 'softmax'.

Returns

tensorflow.keras.Model instance.

applications.densenet.DenseNet169

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applications.densenet.DenseNet169(
    include_top=True, weights='hasc', input_shape=None, 
    pooling=None, classes=6, classifier_activation='softmax')

Reference: - Densely Connected Convolutional Networks (CVPR 2017)

By default, it loads weights pre-trained on HASC. Check 'weights' for other options.

The default input size for this model is 768 (256 * 3).

Arguments

include_top : whether to include the fully-connected layer at the top of the network.
weights : one of 'None' (random initialization), 'hasc' (pre-training on HASC), or the path to the weights file to be loaded.
input_shape : optional shape tuple, default (768, 1) (with channels_last data format).
pooling : optional pooling mode for feature extraction when include_top is False.
- None means that the output of the model will be applied to the 3D tensor output of the last convolutional block.
- avg means that global average pooling will be applied to the output of the last convolutioinal block, 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, default 6.
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, default 'softmax'.

Returns

tensorflow.keras.Model instance.

applications.densenet.DenseNet201

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applications.densenet.DenseNet201(
    include_top=True, weights='hasc', input_shape=None, 
    pooling=None, classes=6, classifier_activation='softmax')

Reference: - Densely Connected Convolutional Networks (CVPR 2017)

By default, it loads weights pre-trained on HASC. Check 'weights' for other options.

The default input size for this model is 768 (256 * 3).

Arguments

include_top : whether to include the fully-connected layer at the top of the network.
weights : one of 'None' (random initialization), 'hasc' (pre-training on HASC), or the path to the weights file to be loaded.
input_shape : optional shape tuple, default (768, 1) (with channels_last data format).
pooling : optional pooling mode for feature extraction when include_top is False.
- None means that the output of the model will be applied to the 3D tensor output of the last convolutional block.
- avg means that global average pooling will be applied to the output of the last convolutioinal block, 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, default 6.
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, default 'softmax'.

Returns

tensorflow.keras.Model instance.