annotate labelimage2points.py @ 0:732d95b2b030 draft default tip

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/labelimage2points/ commit a0ba841e8b3aee770a3243155bedfac0adf9a5a6
author thomaswollmann
date Wed, 12 Dec 2018 04:38:34 -0500
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732d95b2b030 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/labelimage2points/ commit a0ba841e8b3aee770a3243155bedfac0adf9a5a6
thomaswollmann
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1 import argparse
732d95b2b030 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/labelimage2points/ commit a0ba841e8b3aee770a3243155bedfac0adf9a5a6
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2 import sys
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3 import pandas as pd
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4 import skimage.io
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5 from skimage.measure import label
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6 from skimage.data import checkerboard
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7 import numpy as np
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11 def labelimage2points(input_file):
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12 img_in = skimage.io.imread(input_file)
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14 #amount of regions
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15 amount_label = np.max(img_in)
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17 # iterate over all regions in order to calc center of mass
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18 center_mass = []
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19 for i in range(1,amount_label+1):
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20 #get coordinates of region
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21 coord = np.where(img_in==i)
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22 # be carefull with x,y coordinates
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23 center_mass.append([np.mean(coord[1]),np.mean(coord[0])])
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25 #make data frame of detections
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26 out_dataFrame = pd.DataFrame(center_mass)
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29 #return
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30 return(out_dataFrame)
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35 if __name__ == "__main__":
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36 parser = argparse.ArgumentParser()
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37 parser.add_argument('input_file', help='input file')
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38 parser.add_argument('out_file', help='out file (CSV)')
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40 args = parser.parse_args()
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41 input_file = args.input_file
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42 out_file = args.out_file
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44 #TOOL
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45 out_dataFrame = labelimage2points(input_file)
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47 #Print to csv file
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48 out_dataFrame.to_csv(out_file,index=False,header=False)