Mercurial > repos > thomaswollmann > binaryimage2points
comparison binaryimage2points.py @ 0:c983b2d2cdd7 draft default tip
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/binaryimage2points/ commit 27a6350188f687411bdd6bfe0d569c0803389ca0
| author | thomaswollmann |
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| date | Wed, 12 Dec 2018 04:49:24 -0500 |
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| -1:000000000000 | 0:c983b2d2cdd7 |
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| 1 import argparse | |
| 2 import sys | |
| 3 import pandas as pd | |
| 4 import skimage.io | |
| 5 from skimage.measure import label | |
| 6 from skimage.data import checkerboard | |
| 7 import numpy as np | |
| 8 import warnings | |
| 9 | |
| 10 | |
| 11 | |
| 12 def binaryimage2points(input_file): | |
| 13 # ignore warnings that arise when importing a package that was compiled against an older version of numpy than installed; https://github.com/numpy/numpy/pull/432 | |
| 14 warnings.filterwarnings("ignore") | |
| 15 | |
| 16 img_in = skimage.io.imread(input_file, plugin='tifffile') | |
| 17 | |
| 18 #make label image | |
| 19 label = skimage.measure.label(img_in) | |
| 20 | |
| 21 #amount of regions | |
| 22 amount_label = np.max(label) | |
| 23 | |
| 24 # iterate over all regions in order to calc center of mass | |
| 25 center_mass = [] | |
| 26 for i in range(1,amount_label+1): | |
| 27 #get coordinates of region | |
| 28 coord = np.where(label==i) | |
| 29 # be carefull with x,y coordinates | |
| 30 center_mass.append([np.mean(coord[1]),np.mean(coord[0])]) | |
| 31 | |
| 32 #make data frame of detections | |
| 33 out_dataFrame = pd.DataFrame(center_mass) | |
| 34 | |
| 35 | |
| 36 #return | |
| 37 return(out_dataFrame) | |
| 38 | |
| 39 | |
| 40 | |
| 41 | |
| 42 if __name__ == "__main__": | |
| 43 parser = argparse.ArgumentParser() | |
| 44 parser.add_argument('input_file', help='input file') | |
| 45 parser.add_argument('out_file', help='out file (CSV)') | |
| 46 | |
| 47 args = parser.parse_args() | |
| 48 input_file = args.input_file | |
| 49 out_file = args.out_file | |
| 50 | |
| 51 #TOOL | |
| 52 out_dataFrame = binaryimage2points(input_file) | |
| 53 | |
| 54 #Print to csv file | |
| 55 out_dataFrame.to_csv(out_file,index=False,header=False) |
