tf.keras.applications.Xception( include_top=True, weights="imagenet", input_tensor=None, input_shape=None, pooling=None, classes=1000, classifier_activation="softmax", )
Instantiates the Xception architecture.
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
Note that the default input image size for this model is 299x299.
Caution: Be sure to properly pre-process your inputs to the application.
applications.xception.preprocess_input for an example.
None(random initialization), 'imagenet' (pre-training on ImageNet), or the path to the weights file to be loaded.
layers.Input()) to use as image input for the model.
include_topis 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.
Nonemeans that the output of the model will be the 4D tensor output of the last convolutional block.
avgmeans 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.
maxmeans that global max pooling will be applied.
include_topis True, and if no
weightsargument is specified.
stror callable. The activation function to use on the "top" layer. Ignored unless
classifier_activation=Noneto return the logits of the "top" layer.
weights, or invalid input shape.
Nonewhen using a pretrained top layer.