tf.contrib.keras.applications.VGG19

tf.contrib.keras.applications.VGG19

tf.contrib.keras.applications.vgg19.VGG19

VGG19(
    include_top=True,
    weights='imagenet',
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000
)

Defined in tensorflow/contrib/keras/python/keras/applications/vgg19.py.

Instantiates the VGG19 architecture.

Optionally loads weights pre-trained on ImageNet. Note that when using TensorFlow, for best performance you should set image_data_format="channels_last" in your Keras config at ~/.keras/keras.json.

The model and the weights are compatible with both TensorFlow and Theano. The data format convention used by the model is the one specified in your Keras config file.

Arguments:

include_top: whether to include the 3 fully-connected
    layers at the top of the network.
weights: one of `None` (random initialization)
    or "imagenet" (pre-training on ImageNet).
input_tensor: optional Keras tensor (i.e. output of `layers.Input()`)
    to use as image input for the model.
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, 244)` (with `channels_first` data format).
    It should have exactly 3 inputs channels,
    and width and height should be no smaller than 48.
    E.g. `(200, 200, 3)` would be one valid value.
pooling: 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 layer.
    - `avg` means that global average pooling
        will be applied to the output of the
        last convolutional layer, 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.

Returns:

A Keras model instance.

Raises:

ValueError: in case of invalid argument for `weights`,
    or invalid input shape.