fiftyone.core.models.SamplesMixin

class documentation

class SamplesMixin(object): (source)

Mixin for Model classes that need samples for prediction.

Models can implement this mixin to declare that they require one or more fields of the current sample when performing inference on its media.

The fields are get/set via needs_fields, which is a dict that maps model-specific keys to sample field names:

model.needs_fields = {"key1": "field1", "key2": "field2", ...}

Method	`__init__`	Undocumented
Method	`needs_fields.setter`	Undocumented
Method	`predict`	Performs prediction on the given data.
Method	`predict_all`	Performs prediction on the given iterable of data.
Property	`needs_fields`	A dict mapping model-specific keys to sample field names.
Instance Variable	`_fields`	Undocumented

overridden in fiftyone.utils.sam.SegmentAnythingModel, fiftyone.utils.sam2.SegmentAnything2VideoModel

Undocumented

Undocumented

def predict(self, arg, sample=None): (source) ¶

overridden in fiftyone.utils.sam2.SegmentAnything2VideoModel, fiftyone.utils.torch.TorchSamplesMixin

Performs prediction on the given data.

Image models should support, at minimum, processing arg values that are uint8 numpy arrays (HWC).

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

Parameters
arg	the data
sample:`None`	the `fiftyone.core.sample.Sample` associated with the data
Returns
a `fiftyone.core.labels.Label` instance or dict of `fiftyone.core.labels.Label` instances containing the predictions

def predict_all(self, args, samples=None): (source) ¶

overridden in fiftyone.utils.sam.SegmentAnythingModel

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
args	an iterable of data
samples:`None`	an iterable of `fiftyone.core.sample.Sample` instances associated with the data
Returns
a list of `fiftyone.core.labels.Label` instances or a list of dicts of `fiftyone.core.labels.Label` instances containing the predictions

A dict mapping model-specific keys to sample field names.

overridden in fiftyone.utils.sam2.SegmentAnything2VideoModel

Undocumented