Mercurial > repos > thomaswollmann > color_deconvolution

comparison color_deconvolution.py @ 2:8fcbcf6509d8 draft

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/color-deconvolution commit 92068c64f9a6c3cf59f756b9efc2d561196c6873
author thomaswollmann
date Thu, 09 Feb 2017 04:36:37 -0500
parents d7bd56ed3d85
children 85185e9a50a7
comparison
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1:e5d95eb1daad 2:8fcbcf6509d8
3 import warnings 3 import warnings
4 import numpy as np 4 import numpy as np
5 import skimage.io 5 import skimage.io
6 import skimage.color 6 import skimage.color
7 import skimage.util 7 import skimage.util
8 from sklearn.decomposition import PCA 8 from sklearn.decomposition import PCA, NMF, FastICA, FactorAnalysis
9 9
10 convOptions = { 10 convOptions = {
11 'hed2rgb' : lambda img_raw: skimage.color.hed2rgb(img_raw), 11 'hed2rgb' : lambda img_raw: skimage.color.hed2rgb(img_raw),
12 'hsv2rgb' : lambda img_raw: skimage.color.hsv2rgb(img_raw), 12 'hsv2rgb' : lambda img_raw: skimage.color.hsv2rgb(img_raw),
13 'lab2lch' : lambda img_raw: skimage.color.lab2lch(img_raw), 13 'lab2lch' : lambda img_raw: skimage.color.lab2lch(img_raw),
59 'bpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bpx_from_rgb), 59 'bpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bpx_from_rgb),
60 'ahx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.ahx_from_rgb), 60 'ahx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.ahx_from_rgb),
61 'hpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hpx_from_rgb), 61 'hpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hpx_from_rgb),
62 62
63 'pca' : lambda img_raw: np.reshape(PCA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 63 'pca' : lambda img_raw: np.reshape(PCA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
64 [img_raw.shape[0],img_raw.shape[1],-1]),
65 'nmf' : lambda img_raw: np.reshape(NMF(n_components=3, init='nndsvda').fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
66 [img_raw.shape[0],img_raw.shape[1],-1]),
67 'ica' : lambda img_raw: np.reshape(FastICA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
68 [img_raw.shape[0],img_raw.shape[1],-1]),
69 'fa' : lambda img_raw: np.reshape(FactorAnalysis(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
64 [img_raw.shape[0],img_raw.shape[1],-1]) 70 [img_raw.shape[0],img_raw.shape[1],-1])
65 } 71 }
66 72
67 parser = argparse.ArgumentParser() 73 parser = argparse.ArgumentParser()
68 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file') 74 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')