preprocessing.morphology

Functions

threshold_binary_mask: Thresholds a selected NDArray bands to yield a binary mask.
binary_watershed: Performs watershed on a binary mask to yield a mapped label classification

Usage

Perform auto-segmentation on a dataset to yield a label classification.

from frdc.load.preset import FRDCDatasetPreset
from frdc.preprocess.morphology import (
    threshold_binary_mask, binary_watershed
)

ds = FRDCDatasetPreset.chestnut_20201218()
ar, order = ds._get_ar_bands()
mask = threshold_binary_mask(ar, order.index('NIR'), 90 / 256)
ar_label = binary_watershed(mask)

API

threshold_binary_mask(ar, band_idx, threshold_value)

Thresholds a selected NDArray bands to yield a binary mask as np.ndarray

This is equivalent to

ar[..., band_idx] > threshold_value

binary_watershed(ar_mask, peaks_footprint, watershed_compactness)

Performs watershed on a binary mask to yield a mapped label classification as a np.ndarray

peaks_footprint is the footprint of skimage.feature.peak_local_max
watershed_compactness is the compactness of skimage.morphology.watershed

Last modified: 26 June 2024