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Instantiates the MobileNet architecture.
tf.keras.applications.mobilenet.MobileNet(
input_shape=None,
alpha=1.0,
depth_multiplier=1,
dropout=0.001,
include_top=True,
weights='imagenet',
input_tensor=None,
pooling=None,
classes=1000,
classifier_activation='softmax',
**kwargs
)
Reference:
This function returns a Keras image classification model, optionally loaded with weights pre-trained on ImageNet.
For image classification use cases, see this page for detailed examples.
For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning.
Args | |
---|---|
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, and width and
height should be no smaller than 32. E.g. (200, 200, 3) would be one
valid value. Default to None .
input_shape will be ignored if the input_tensor is provided.
|
alpha
|
Controls the width of the network. This is known as the width
multiplier in the MobileNet paper. - If alpha < 1.0, proportionally
decreases the number of filters in each layer. - If alpha > 1.0,
proportionally increases the number of filters in each layer. - If
alpha = 1, default number of filters from the paper are used at each
layer. Default to 1.0.
|
depth_multiplier
|
Depth multiplier for depthwise convolution. This is called the resolution multiplier in the MobileNet paper. Default to 1.0. |
dropout
|
Dropout rate. Default to 0.001. |
include_top
|
Boolean, whether to include the fully-connected layer at the
top 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.
|
pooling
|
Optional pooling mode for feature extraction when include_top
is False .
|
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. Defaults 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.
When loading pretrained weights, classifier_activation can only
be None or "softmax" .
|
**kwargs
|
For backwards compatibility only. |
Returns | |
---|---|
A keras.Model instance.
|