comparison anisotropic_diffusion.py @ 0:9a30c8f0f651 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/anisotropic-diffusion/ commit 3036169a656a17a8c73a93241e375693f281bce8
author thomaswollmann
date Tue, 21 Feb 2017 09:11:07 -0500
parents
children 6be26440a8ec
comparison
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-1:000000000000 0:9a30c8f0f651
1 import argparse
2 import sys
3 import warnings
4 import numpy as np
5 import skimage.io
6 import skimage.util
7 from medpy.filter.smoothing import anisotropic_diffusion
8
9 parser = argparse.ArgumentParser()
10 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')
11 parser.add_argument('out_file', type=argparse.FileType('w'), default=sys.stdin, help='out file (TIFF)')
12 parser.add_argument('niter', type=int, help='Number of iterations', default=1)
13 parser.add_argument('kappa', type=int, help='Conduction coefficient', default=50)
14 parser.add_argument('gamma', type=float, help='Speed of diffusion', default=0.1)
15 parser.add_argument('eqoption', type=int, choices=[1,2], help='Perona Malik diffusion equation', default=1)
16 args = parser.parse_args()
17
18 img_in = skimage.io.imread(args.input_file.name)
19 res = anisotropic_diffusion(img_raw, niter=args.niter, kappa=args.kappa, gamma=args.gamma, option=args.eqoption)
20 res[res<-1]=-1
21 res[res>1]=1
22
23 with warnings.catch_warnings():
24 warnings.simplefilter("ignore")
25 res = skimage.util.img_as_uint(res) #Attention: precision loss
26 skimage.io.imsave(args.out_file.name, res, plugin='tifffile')