loops.plate_loop()

Main loop to process a plate.

Usage

Source

loops.plate_loop(
    conn,
    plate_id,
    segmentation_mode=False,
    stitch_mode=False,
    delete_existing=False
)

Parameters

conn: BlitzGateway

Connection to OMERO

plate_id: int

ID of the plate

segmentation_mode: bool = False

Only perform image segmentation

stitch_mode: bool = False

Run stitched-well segmentation instead of per-field

delete_existing: bool = False

Delete the plate’s stored segmentation masks before running, forcing a fresh segmentation. Without this, both the stitched and per-field paths reuse whatever masks are already in the dataset and only recompute the measurements.

Returns

pd.DataFrame

Tuple[DataFrame, DataFrame, DataFrame, Dict]: Three DataFrames containing the final data and quality control data;

pd.DataFrame | None

dictionary of matplotlib figures of the inference gallery keyed by class (can be None)