bioimageflow-segmentation-tools

Segmentation-focused tool package for BioImageFlow.

Tools

• Cellpose3: Cellpose v3 pretrained model wrapper.
• StarDistSegmenter: StarDist 2D pretrained model wrapper.
• ThresholdSegment: threshold an intensity image and label connected foreground objects.
• OtsuThresholdSegment: compute a global Otsu threshold and label foreground objects.
• LocalThresholdSegment: compute a Sauvola local threshold and label foreground objects.
• WatershedSegment: split foreground regions from marker labels or connected components.
• DistanceWatershedSegment: split foreground with marker-free distance-transform watershed.
• SplitTouchingObjects: split clumped labels using distance-transform watershed.
• FilterLabels: remove labels by area, border contact, intensity, and shape constraints.
• PostprocessLabels: remove small labels and relabel label images sequentially.

Heavy model dependencies are declared in isolated EnvironmentSpec objects and imported only inside process_row. Importing this package does not require Cellpose, TensorFlow, StarDist, or other model packages to be installed in the main process. Cellpose3, CellposeSAM, and StarDistSegmenter lazily keep one model per worker-side tool instance. Repeated calls with the same model selection reuse the weights; changing model_type or model_name replaces the cached model, and clear_model_cache() releases it explicitly. Applications can invalidate remote worker caches by stopping the corresponding Wetlands environment.

Example

from bioimageflow_core import Arguments
from bioimageflow_segmentation_tools import ThresholdSegment

segment = ThresholdSegment()
result = segment.process_row(
    Arguments(
        input_image="input.tif",
        threshold=128.0,
        labels="labels.tif",
        above=True,
    )
)

Workflow graph construction with segment(...) requires installing the main-process bioimageflow orchestrator alongside this package.