RSGISLib Tiled Segmentation

run_tiled_segmentation.py

#!/usr/bin/env python
"""
Apply RSGISLib segmentation to image
using standard or tiled approach.

For more details see:

https://spectraldifferences.wordpress.com/2016/07/09/scalable-image-segmentation-using-rsgislib/

Dan Clewley (09/07/2016)
"""

from __future__ import print_function
import argparse
import shutil
import sys
import tempfile
from rsgislib.segmentation import tiledsegsingle
from rsgislib.segmentation import segutils

# Set values for clustering
NUM_CLUSTERS = 60
MIN_PIXELS = 100
DIST_THRESHOLD = 100

# Set values for tiles segmentation
TILE_WIDTH = 2000
TILE_HEIGHT = 2000

if __name__ == "__main__":

    parser = argparse.ArgumentParser()
    parser.add_argument("inputimage", nargs=1,
                        type=str, help="Input Image")
    parser.add_argument("outputclumps", nargs=1,
                        type=str, help="Output clumps")
    parser.add_argument("--tiled",
                        default=False,
                        action="store_true",
                        help="Use tiled segmentation")
    args = parser.parse_args()

    # Make temp directory for intermediate files
    temp_dir = tempfile.mkdtemp(prefix='rsgislib_seg_')
    try:
        if args.tiled:
            # If requested run tiled segmentation
            tiledsegsingle.performTiledSegmentation(args.inputimage[0], args.outputclumps[0],
                                                    tmpDIR=temp_dir,
                                                    tileWidth=TILE_WIDTH, tileHeight=TILE_HEIGHT,
                                                    validDataThreshold=0.3,
                                                    numClusters=NUM_CLUSTERS,
                                                    minPxls=MIN_PIXELS,
                                                    distThres=DIST_THRESHOLD,
                                                    sampling=100, kmMaxIter=200)
        else:
            # If not run standard
            segutils.runShepherdSegmentation(args.inputimage[0], args.outputclumps[0],
                                             tmpath=temp_dir,
                                             numClusters=NUM_CLUSTERS,
                                             minPxls=MIN_PIXELS,
                                             distThres=DIST_THRESHOLD,
                                             sampling=100, kmMaxIter=200)

    except KeyboardInterrupt:
        sys.exit(2)
    except Exception as err:
        print("Segmentation failed: {}".format(err), file=sys.stderr)
        sys.exit(1)
    finally:
        # Remove temp directory
        shutil.rmtree(temp_dir)