segments stats toy example

README

A toy script to demonstrate generating statistics across array segments/blobs/labels.
The context for the example is 2D imagery.
It'll compare two methods:

1. reverse indices provided by <https://github.com/sixy6e/idl-functions> and wrapped by <https://github.com/sixy6e/image-processing> to for ease of use in an image processing context
2. loop through id's and do a bool lookup

toy_segments.py

#!/usr/bin/env python

from datetime import datetime
from typing import Tuple
import numpy
import structlog

from image_processing.segmentation import Segments

DIMS = (8000, 8000)
BANDS = 4
LOG = structlog.get_logger()


def data() -> Tuple[numpy.ndarray, numpy.ndarray]:
    """Generate sample data."""
    # simulate a segmented image with random ID's between 0 and 60000
    seg_ids = numpy.random.randint(0, 60001, DIMS)

    # simulate some landsat spectral bands
    spectral = numpy.random.ranf((BANDS, *DIMS))

    return seg_ids, spectral


def reverse_indices():
    """Test segmentwise stats using a reverse indices method."""
    seg_ids, spectral = data()

    start = datetime.now()
    segments = Segments(seg_ids)

    results = {f"band_{i}": segments.mean(spectral[i]) for i in range(BANDS)}
    finish = datetime.now()

    LOG.info("reverse_indices", time_taken=finish-start)


def basic_bool():
    """
    Test segmentwise the mean using a basic numpy bool method.
    Also, only the first 50 segments will calculated.
    """
    seg_ids, spectral = data()

    start = datetime.now()

    results = {}
    for i in range(BANDS):
        for seg in range(50):
            results[f"band_{i}"] = [numpy.mean(spectral[i][seg_ids == seg])]

    finish = datetime.now()
    LOG.info("bool method for only 50 segments", time_taken=finish-start)


def main():
    """ main """
    LOG.info("running reverse indices")
    reverse_indices()

    LOG.info("running bool method")
    basic_bool()


if __name__ == "__main__":
    main()