class documentation

FiftyOne wrapper around an Ultralytics YOLO pose model.

Parameters
configa FiftyOneYOLOPoseModelConfig
Method predict_all Performs prediction on the given iterable of data.
Method _format_predictions Undocumented

Inherited from FiftyOneYOLOModel:

Method __init__ Undocumented
Method predict Performs prediction on the given data.
Instance Variable config Undocumented
Instance Variable device Undocumented
Instance Variable model Undocumented
Property media_type The media type processed by the model.
Property preprocess Whether to apply transforms during inference (True) or to assume that they have already been applied (False).
Property ragged_batches True/False whether transforms may return tensors of different sizes. If True, then passing ragged lists of data to predict_all is not allowed.
Property transforms The preprocessing function that will/must be applied to each input before prediction, or None if no preprocessing is performed.
Method _load_model Undocumented

Inherited from Model (via FiftyOneYOLOModel):

Method __enter__ Undocumented
Method __exit__ Undocumented
Method preprocess.setter Undocumented
Property can_embed_prompts Whether this instance can generate prompt embeddings.
Property has_embeddings Whether this instance can generate embeddings.
Property has_logits Whether this instance can generate logits for its predictions.
def predict_all(self, args): (source)

Performs prediction on the given iterable of data.

Image models should support, at minimum, processing args values that are either lists of uint8 numpy arrays (HWC) or numpy array tensors (NHWC).

Video models should support, at minimum, processing args values that are lists of eta.core.video.VideoReader instances.

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

Parameters
argsan iterable of data
Returns
a list of fiftyone.core.labels.Label instances or a list of dicts of fiftyone.core.labels.Label instances containing the predictions
def _format_predictions(self, predictions): (source)