comparison histogram_equalization.py @ 4:99e0ef91ea5e draft default tip

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_histogram_equalization/ commit 558152251d5d7a1bf77db91aa5388aca7a68ae62

3:b1c2c210813c

import argparse
import sys

import giatools.io
import skimage.exposure
import skimage.io
import skimage.util

hOptions = {
    'default': lambda img_raw: skimage.exposure.equalize_hist(img_raw),
    'clahe': lambda img_raw: skimage.exposure.equalize_adapthist(img_raw)
}

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Histogram equalization')
    parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')

4:99e0ef91ea5e

import argparse
import sys

import giatools.io
import numpy as np
import skimage.exposure
import skimage.io
import skimage.util


def rescale(img):
    assert np.issubdtype(img.dtype, np.floating), str(img.dtype)  # sanity check
    img = img - img.min()
    return img / img.max() if img.max() != 0 else 1


hOptions = {
    'default': lambda img_raw: rescale(skimage.exposure.equalize_hist(img_raw)),  # rescale needed for values to be in [0, 1]
    'clahe': lambda img_raw: skimage.exposure.equalize_adapthist(img_raw),  # produces image with values in [0, 1]
}

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Histogram equalization')
    parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')