larq_zoo.sota

QuickNet

QuickNet(input_shape=None,
         input_tensor=None,
         weights='imagenet',
         include_top=True,
         num_classes=1000)
Instantiates the QuickNet architecture.

Optionally loads weights pre-trained on ImageNet.

Interactive architecture diagram

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.
  • input_tensor: optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model.
  • weights: one of None (random initialization), "imagenet" (pre-training on ImageNet), or the path to the weights file to be loaded.
  • include_top: whether to include the fully-connected layer at the top of the network.
  • num_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.

QuickNetLarge

QuickNetLarge(input_shape=None,
              input_tensor=None,
              weights='imagenet',
              include_top=True,
              num_classes=1000)
Instantiates the QuickNetLarge architecture.

Optionally loads weights pre-trained on ImageNet.

Interactive architecture diagram

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.
  • input_tensor: optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model.
  • weights: one of None (random initialization), "imagenet" (pre-training on ImageNet), or the path to the weights file to be loaded.
  • include_top: whether to include the fully-connected layer at the top of the network.
  • num_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.

QuickNetXL

QuickNetXL(input_shape=None,
           input_tensor=None,
           weights='imagenet',
           include_top=True,
           num_classes=1000)
Instantiates the QuickNetXL architecture.

Optionally loads weights pre-trained on ImageNet.

Interactive architecture diagram

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.
  • input_tensor: optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model.
  • weights: one of None (random initialization), "imagenet" (pre-training on ImageNet), or the path to the weights file to be loaded.
  • include_top: whether to include the fully-connected layer at the top of the network.
  • num_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.