fiftyone.core.models.EmbeddingsMixin

class documentation

class EmbeddingsMixin(object): (source)

Known subclasses: fiftyone.utils.eta.ETAModel, fiftyone.utils.torch.TorchEmbeddingsMixin, fiftyone.utils.transformers.TransformerEmbeddingsMixin, fiftyone.utils.transformers.ZeroShotTransformerEmbeddingsMixin

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Mixin for Model classes that can generate embeddings for their predictions.

This mixin allows for the possibility that only some instances of a class are capable of generating embeddings, per the value of the has_embeddings property.

Method	`embed`	Generates an embedding for the given data.
Method	`embed_all`	Generates embeddings for the given iterable of data.
Method	`get_embeddings`	Returns the embeddings generated by the last forward pass of the model.
Property	`has_embeddings`	Whether this instance has embeddings.

def embed(self, arg): (source) ¶

overridden in fiftyone.utils.eta.ETAModel, fiftyone.utils.torch.TorchEmbeddingsMixin, fiftyone.utils.transformers.TransformerEmbeddingsMixin, fiftyone.utils.transformers.ZeroShotTransformerEmbeddingsMixin

Generates an embedding for the given data.

Subclasses can override this method to increase efficiency, but, by default, this method simply calls predict and then returns get_embeddings.

Parameters
arg	the data. See `predict` for details
Returns
a numpy array containing the embedding

def embed_all(self, args): (source) ¶

Generates embeddings for the given iterable of data.

Subclasses can override this method to increase efficiency, but, by default, this method simply iterates over the data and applies embed to each.

Parameters
args	an iterable of data. See `predict_all` for details
Returns
a numpy array containing the embeddings stacked along axis 0

def get_embeddings(self): (source) ¶

overridden in fiftyone.utils.eta.ETAModel, fiftyone.utils.torch.TorchEmbeddingsMixin

Returns the embeddings generated by the last forward pass of the model.

By convention, this method should always return an array whose first axis represents batch size (which will always be 1 when predict was last used).

Returns
a numpy array containing the embedding(s)

@property
has_embeddings = (source) ¶

Whether this instance has embeddings.