| Next changeset 1:4853fc2b50bf (2019-07-23) |
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Commit message:
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_auto_threshold/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581 |
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added:
auto_threshold.py auto_threshold.xml test-data/out.tif test-data/out2.tif test-data/sample.tif |
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| diff -r 000000000000 -r d4da97f51700 auto_threshold.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/auto_threshold.py Sat Feb 09 14:27:36 2019 -0500 |
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| @@ -0,0 +1,38 @@ +import argparse +import numpy as np +import os +import sys +import warnings +import skimage.io +import skimage.filters +import skimage.util + +threshOptions = { + 'otsu' : lambda img_raw: skimage.filters.threshold_otsu(img_raw), + 'gaussian_adaptive' : lambda img_raw: skimage.filters.threshold_local(img_raw.reshape(img_raw.shape[0], img_raw.shape[1]), 3, method='gaussian'), # todo reshape 2d + 'mean_adaptive' : lambda img_raw: skimage.filters.threshold_local(img_raw.reshape(img_raw.shape[0], img_raw.shape[1]), 3, method='mean'), # todo reshape 2d + 'isodata' : lambda img_raw: skimage.filters.threshold_isodata(img_raw), + 'li' : lambda img_raw: skimage.filters.threshold_li(img_raw), + 'yen' : lambda img_raw: skimage.filters.threshold_yen(img_raw), +} + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description='Segment Foci') + 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)') + parser.add_argument('thresh_type', choices=threshOptions.keys(), help='thresholding method') + parser.add_argument('dark_background', default=True, type=bool, help='True if background is dark') + args = parser.parse_args() + + img_in = skimage.io.imread(args.input_file.name) + thresh = threshOptions[args.thresh_type](img_in) + + if args.dark_background: + res = img_in > thresh + else: + res = img_in <= thresh + + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + res = skimage.util.img_as_uint(res) + skimage.io.imsave(args.out_file.name, res, plugin="tifffile") |
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| diff -r 000000000000 -r d4da97f51700 auto_threshold.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/auto_threshold.xml Sat Feb 09 14:27:36 2019 -0500 |
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| @@ -0,0 +1,49 @@ +<tool id="ip_threshold" name="Auto Threshold" version="0.0.3"> + <description>applies a standard threshold algorithm to an image</description> + <requirements> + <requirement type="package" version="0.14.2">scikit-image</requirement> + <requirement type="package" version="1.15.4">numpy</requirement> + <requirement type="package" version="5.3.0">pillow</requirement> + <requirement type="package" version="0.15.1">tifffile</requirement> + </requirements> + <command detect_errors="aggressive"> + <![CDATA[ + python '$__tool_directory__/auto_threshold.py' '$input' '$output' $thresh_type $dark_background + ]]> + </command> + <inputs> + <param name="input" type="data" format="tiff" label="Source file" /> + <param name="thresh_type" type="select" label="Threshold Algorithm"> + <option value="otsu" selected="True">Otsu</option> + <option value="li">Li’s Minimum Cross Entropy</option> + <option value="isodata">Isodata</option> + <option value="gaussian_adaptive">Adaptive (Gauss)</option> + <option value="mean_adaptive">Adaptive (Mean)</option> + <option value="yen">Yen</option> + </param> + <param name="dark_background" type="boolean" checked="true" truevalue="True" falsevalue="False" label="Dark Background" /> + </inputs> + <outputs> + <data format="tiff" name="output" /> + </outputs> + <tests> + <test> + <param name="input" value="sample.tif"/> + <output name="output" value="out.tif" ftype="tiff" compare="sim_size"/> + <param name="thresh_type" value="gaussian_adaptive"/> + <param name="dark_backgroud" value="True"/> + </test> + <test> + <param name="input" value="sample.tif"/> + <output name="output" value="out2.tif" ftype="tiff" compare="sim_size"/> + <param name="thresh_type" value="otsu"/> + <param name="dark_backgroud" value="True"/> + </test> + </tests> + <help> + Applies a standard threshold algorithm to an image. + </help> + <citations> + <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation> + </citations> +</tool> |
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