ExtractBatch

class lib.infer.objects.ExtractBatch(filenames: list[str] = <factory>, images: list[np.ndarray] = <factory>, sources: list[str | None] = <factory>, is_aligned: bool = False, frame_sizes: list[tuple[int, int]] | None=None, frame_metadata: list[PNGSource] | None = None, passthrough: bool = False)

Bases: object

Dataclass for holding a batch flowing through Extraction plugins.

The batch size for post Detector plugins is not the same as the overall batch size. An image may contain 0 or more detected faces, and these need to be split and recombined to be able to utilize a plugin’s internal batch size.

Parameters:

filenames (list[str]) – The original frame filenames for the batch
images (list[np.ndarray]) – The original frames
sources (list[str | None]) – The full path to the source folder or video file. Default: [] (Not provided)
is_aligned (bool) – True if images contains aligned faces. False if it contains full frames. Default: False
frame_sizes (list[tuple[int, int]] | None) – The original frame (height, width) dimensions that contained the aligned images when images are aligned faces. Default: None
frame_metadata (list[PNGSource] | None) – The original frame meta data when aligned faces is True otherwise None
passthrough (bool) – True` if the contents of this item are meant to pass straight through the extraction pipeline for immediate return

Attributes Summary

`frame_metadata`	The original frame metadata when aligned faces is `True` otherwise `None`
`frame_sizes`	The original frame (heights, widths) when the images are aligned faces
`is_aligned`	`True` if `images` contains aligned faces.
`landmark_type`	The landmark type found for this batch or `None` if not populated
`landmarks`	The face landmarks found for this batch in frame space or `None` if not populated
`lengths`	The number of bboxes that belong to each frame
`passthrough`	Whether this item should pass straight through the pipeline for immediate return

Methods Summary

`append`(batch)	Append the data from the given batch object to this batch object
`apply_mask`(mask)	Apply a boolean mask to the batch object.
`from_detected_faces`(faces)	Populate an ExtractBatch with the contents of a DetectedFace object.
`from_frame_faces`(media)	Populate a new ExtractBatch with the contents of an FrameFaces object.

Attributes Documentation

frame_metadata: list[PNGSource] | None = None: The original frame metadata when aligned faces is True otherwise None

frame_sizes: list[tuple[int, int]] | None = None: The original frame (heights, widths) when the images are aligned faces

is_aligned: bool = False: True if images contains aligned faces. False for full frames

landmark_type: The landmark type found for this batch or None if not populated

landmarks: The face landmarks found for this batch in frame space or None if not populated

lengths: The number of bboxes that belong to each frame

passthrough: bool = False: Whether this item should pass straight through the pipeline for immediate return

Methods Documentation

append(batch: ExtractBatch) → None

Append the data from the given batch object to this batch object

Parameters:: batch (ExtractBatch) – The object containing data to be appended to this object
Return type:: None

apply_mask(mask: ndarray[tuple[Any, ...], dtype[bool]]) → None

Apply a boolean mask to the batch object. True values are kept, False values are discarded

Parameters:: mask (ndarray[tuple[Any, ...], dtype[bool]]) – The boolean mask to apply to the object. Must be of size (num_boxes, )
Return type:: None

from_detected_faces(faces: list[DetectedFace]) → None

Populate an ExtractBatch with the contents of a DetectedFace object.

Parameters:: faces (list[DetectedFace]) – The DetectedFace objects to populate this batch
Raises:: ValueError – If attempting to add detected faces without pre-populating filename and image or if bounding boxes pre-exist or if more than one frame is held in this batch
Return type:: None

classmethod from_frame_faces(media: FrameFaces) → ExtractBatch

Populate a new ExtractBatch with the contents of an FrameFaces object.

Parameters:: media (FrameFaces) – The FrameFaces to populate this batch from
Return type:: A new ExtractBatch object populated from the given FrameFaces object

aligned: ExtractBatchAligned = <dataclasses._MISSING_TYPE object>: Holds the face landmarks found for this batch any any aligned data