delta.pipeline.ROI¶

class delta.pipeline.ROI(roi_nb: int, box: CroppingBox, crop_windows: bool = False)¶

ROI processor object

__init__(roi_nb: int, box: CroppingBox, crop_windows: bool = False)¶

Initialize ROI

Parameters

roi_nbint: ROI index.
boxdict: Crop box for ROI, formatted as in the utilities.py cropbox function input dict.
crop_windowsbool, optional: Flag to crop and stitch back windows for segmentation and tracking. The default is False.

Returns

Attributes

`roi_nb`	The ROI index number
`box`	ROI crop box
`img_stack`	Input images stack
`seg_stack`	Segmentation images stack
`lineage`	Lineage object for ROI
`label_stack`	Labelled images stack
`crop_windows`	Flag to crop overlapping windows for segmentation
`verbose`	Console outputs verbosity

Methods

`__init__`(roi_nb, box[, crop_windows])	Initialize ROI
`extract_features`([frame, fluo_frames, features])	Extract single cell features
`get_segmentation_inputs`(img)	Compile segmentation inputs for ROI
`get_tracking_inputs`([frame])	Compile tracking inputs for ROI
`process_segmentation_outputs`(y[, frame, windows])	Process outputs after they have been segmented.
`process_tracking_outputs`(y[, frame, boxes])	Process output from tracking U-Net

DeLTA