StyleTransfer

class flash.image.style_transfer.model.StyleTransfer(style_image=None, model=None, backbone='vgg16', content_layer='relu2_2', content_weight=100000.0, style_layers=['relu1_2', 'relu2_2', 'relu3_3', 'relu4_3'], style_weight=10000000000.0, optimizer='Adam', lr_scheduler=None, learning_rate=None)

StyleTransfer is a Task for transferring the style from one image onto another. For more details, see Style Transfer.

Parameters

• style_image (Union[str, Tensor, None]) – Image or path to an image to derive the style from.

• model (Optional[Module]) – The model by the style transfer task.

• backbone (str) – A string or model to use to compute the style loss from.

• content_layer (str) – Which layer from the backbone to extract the content loss from.

• content_weight (float) – The weight associated with the content loss. A lower value will lose content over style.

• style_layers (Union[Sequence[str], str]) – Layers from the backbone to derive the style loss from.

• style_weight (float) – The weight associated with the style loss. A lower value will lose style over content.

• optimizer (TypeVar(OPTIMIZER_TYPE, str, Callable, Tuple[str, Dict[str, Any]], None)) – Optimizer to use for training.

• lr_scheduler (Optional[TypeVar(LR_SCHEDULER_TYPE, str, Callable, Tuple[str, Dict[str, Any]], Tuple[str, Dict[str, Any], Dict[str, Any]], None)]) – The LR scheduler to use during training.

• learning_rate (Optional[float]) – Learning rate to use for training, defaults to 1e-3.

classmethod available_finetuning_strategies(cls)

Returns a list containing the keys of the available Finetuning Strategies.

Return type

List[str]

classmethod available_lr_schedulers(cls)

Returns a list containing the keys of the available LR schedulers.

Return type

List[str]

classmethod available_optimizers(cls)

Returns a list containing the keys of the available Optimizers.

Return type

List[str]

classmethod available_outputs(cls)

Returns the list of available outputs (that can be used during prediction or serving) for this Task.

Examples

..testsetup:

>>> from flash import Task

>>> print(Task.available_outputs())
['preds', 'raw']

Return type

List[str]