Instantiates the MobileNetV2 architecture.
tf.keras.applications.MobileNetV2(
input_shape=None, alpha=1.0, include_top=True, weights='imagenet',
input_tensor=None, pooling=None, classes=1000,
classifier_activation='softmax', **kwargs
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
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Reference:
Optionally loads weights pre-trained on ImageNet.
Arguments |
|---|
input_shape
|
Optional shape tuple, to be specified if you would
like to use a model with an input image resolution that is not
(224, 224, 3).
It should have exactly 3 inputs channels (224, 224, 3).
You can also omit this option if you would like
to infer input_shape from an input_tensor.
If you choose to include both input_tensor and input_shape then
input_shape will be used if they match, if the shapes
do not match then we will throw an error.
E.g. (160, 160, 3) would be one valid value.
|
alpha
|
Float between 0 and 1. controls the width of the network.
This is known as the width multiplier in the MobileNetV2 paper,
but the name is kept for consistency with applications.MobileNetV1
model in Keras.
- 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.
|
include_top
|
Boolean, whether to include the fully-connected
layer at the top of the network. Defaults to True.
|
weights
|
String, 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.
|
pooling
|
String, 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 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
|
Integer, optional number of classes to classify images
into, only to be specified if include_top is True, and
if no weights argument is specified.
|
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.
|
**kwargs
|
For backwards compatibility only.
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Raises |
|---|
ValueError
|
in case of invalid argument for weights,
or invalid input shape or invalid alpha, rows when
weights='imagenet'
|
ValueError
|
if classifier_activation is not softmax or None when
using a pretrained top layer.
|
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TensorFlow 1 version
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