tf.keras.applications.InceptionV3
Instantiates the Inception v3 architecture.
tf.keras.applications.InceptionV3(
include_top=True, weights='imagenet', input_tensor=None,
input_shape=None, pooling=None, classes=1000,
classifier_activation='softmax'
)
Reference:
Optionally loads weights pre-trained on ImageNet. Note that the data format convention used by the model is the one specified in the tf.keras.backend.image_data_format().
Note: each Keras Application expects a specific kind of input preprocessing. For InceptionV3, call tf.keras.applications.inception_v3.preprocess_input on your inputs before passing them to the model.
| Arguments |
|---|
include_top | Boolean, whether to include the fully-connected layer at the top, as the last layer of the network. Default to True. |
weights | One of None (random initialization), imagenet (pre-training on ImageNet), or the path to the weights file to be loaded. Default to imagenet. |
input_tensor | Optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model. input_tensor is useful for sharing inputs between multiple different networks. Default to None. |
input_shape | Optional shape tuple, only to be specified if include_top is False (otherwise the input shape has to be (299, 299, 3) (with channels_last data format) or (3, 299, 299) (with channels_first data format). It should have exactly 3 inputs channels, and width and height should be no smaller than 75. E.g. (150, 150, 3) would be one valid value. input_shape will be ignored if the input_tensor is provided. |
pooling | Optional pooling mode for feature extraction when include_top is False. -
None (default) 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.
|
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 to 1000. |
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. |
| Raises |
|---|
ValueError | in case of invalid argument for weights, or invalid input shape. |
ValueError | if classifier_activation is not softmax or None when using a pretrained top layer. |