comparison binary2label.py @ 5:7f8102bdbfa1 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/binary2labelimage/ commit 48df7d9c58fb88e472caeb4d4a1e14170d79b643

4:984358e43242

import argparse
import sys

import skimage.io
import skimage.util
from PIL import Image
from skimage.measure import label

parser = argparse.ArgumentParser()
parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')
parser.add_argument('out_file', type=argparse.FileType('w'), default=sys.stdin, help='out file (TIFF)')
args = parser.parse_args()

img_in = skimage.io.imread(args.input_file.name) > 0
res = label(img_in)
res = skimage.util.img_as_uint(res)

res = Image.fromarray(res)
res.save(args.out_file.name, "tiff")

5:7f8102bdbfa1

import argparse

import giatools
import scipy.ndimage as ndi
import tifffile


# Parse CLI parameters
parser = argparse.ArgumentParser()
parser.add_argument('input', type=str, help='input file')
parser.add_argument('output', type=str, help='output file (TIFF)')
args = parser.parse_args()

# Read the input image with the original axes
img = giatools.Image.read(args.input)
img = img.normalize_axes_like(
    img.original_axes,
)

# Make sure the image is truly binary
img_arr_bin = (img.data > 0)

# Perform the labeling
img.data = ndi.label(img_arr_bin)[0]

# Write the result image (same axes as input image)
tifffile.imwrite(args.output, img.data, metadata=dict(axes=img.axes))