ImageEmbedder¶
- class flash.image.embedding.model.ImageEmbedder(training_strategy='default', head=None, pretraining_transform=None, backbone='resnet18', pretrained=False, optimizer='Adam', lr_scheduler=None, learning_rate=None, backbone_kwargs=None, training_strategy_kwargs=None, pretraining_transform_kwargs=None)[source]¶
The
ImageEmbedder
is aTask
for obtaining feature vectors (embeddings) from images. For more details, see Image Embedder.- Parameters
training_strategy¶ (
str
) – Training strategy from VISSL, select between ‘simclr’, ‘swav’, or ‘barlow_twins’.head¶ (
Optional
[str
]) – projection head used for task, select between ‘simclr_head’, ‘swav_head’, or ‘barlow_twins_head’.pretraining_transform¶ (
Optional
[str
]) – transform applied to input image for pre-training SSL model. Select between ‘simclr_transform’, ‘swav_transform’, or ‘barlow_twins_transform’.pretrained¶ (
bool
) – Use a pretrained backbone, defaults toFalse
.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 to1e-3
.backbone_kwargs¶ (
Optional
[Dict
[str
,Any
]]) – arguments to be passed to VISSL backbones, i.e.vision_transformer
andresnet
.training_strategy_kwargs¶ (
Optional
[Dict
[str
,Any
]]) – arguments passed to VISSL loss function, projection head and training hooks.pretraining_transform_kwargs¶ (
Optional
[Dict
[str
,Any
]]) – arguments passed to VISSL transforms.
- classmethod available_finetuning_strategies(cls)¶
Returns a list containing the keys of the available Finetuning Strategies.
- classmethod available_lr_schedulers(cls)¶
Returns a list containing the keys of the available LR schedulers.
- classmethod available_optimizers(cls)¶
Returns a list containing the keys of the available Optimizers.
- 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']