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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_auto_threshold/ commit 01343602708de3cc7fa4986af9000adc36dd0651
author imgteam
date Sat, 07 Jun 2025 18:38:16 +0000
parents 5224cc463a97
children
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5224cc463a97 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_auto_threshold/ commit b1b3c63ab021aa77875c3b04127f6836024812f9"
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1 """
4
7d80eb2411fb planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_auto_threshold/ commit 01343602708de3cc7fa4986af9000adc36dd0651
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2 Copyright 2017-2024 Biomedical Computer Vision Group, Heidelberg University.
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4 Distributed under the MIT license.
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5 See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
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6 """
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8 import argparse
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9
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10 import numpy as np
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11 import skimage.filters
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12 import skimage.util
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13 from giatools.image import Image
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16 class DefaultThresholdingMethod:
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18 def __init__(self, thres, accept: list[str] | None = None, **kwargs):
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19 self.thres = thres
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20 self.accept = accept if accept else []
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21 self.kwargs = kwargs
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23 def __call__(self, image, *args, offset=0, **kwargs):
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24 accepted_kwargs = self.kwargs.copy()
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25 for key, val in kwargs.items():
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26 if key in self.accept:
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27 accepted_kwargs[key] = val
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28 thres = self.thres(image, *args, **accepted_kwargs)
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29 return image > thres + offset
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32 class ManualThresholding:
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34 def __call__(self, image, thres1: float, thres2: float | None, **kwargs):
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35 if thres2 is None:
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36 return image > thres1
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37 else:
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38 thres1, thres2 = sorted((thres1, thres2))
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39 return skimage.filters.apply_hysteresis_threshold(image, thres1, thres2)
7d80eb2411fb planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/2d_auto_threshold/ commit 01343602708de3cc7fa4986af9000adc36dd0651
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42 th_methods = {
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43 'manual': ManualThresholding(),
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45 'otsu': DefaultThresholdingMethod(skimage.filters.threshold_otsu),
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46 'li': DefaultThresholdingMethod(skimage.filters.threshold_li),
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47 'yen': DefaultThresholdingMethod(skimage.filters.threshold_yen),
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48 'isodata': DefaultThresholdingMethod(skimage.filters.threshold_isodata),
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49
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50 'loc_gaussian': DefaultThresholdingMethod(skimage.filters.threshold_local, accept=['block_size'], method='gaussian'),
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51 'loc_median': DefaultThresholdingMethod(skimage.filters.threshold_local, accept=['block_size'], method='median'),
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52 'loc_mean': DefaultThresholdingMethod(skimage.filters.threshold_local, accept=['block_size'], method='mean'),
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53 }
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54
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55
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56 def do_thresholding(
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57 input_filepath: str,
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58 output_filepath: str,
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59 th_method: str,
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60 block_size: int,
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61 offset: float,
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62 threshold1: float,
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63 threshold2: float | None,
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64 invert_output: bool,
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65 ):
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66 assert th_method in th_methods, f'Unknown method "{th_method}"'
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67
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68 # Load image
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69 img_in = Image.read(input_filepath)
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70
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71 # Perform thresholding
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72 result = th_methods[th_method](
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73 image=img_in.data,
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74 block_size=block_size,
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75 offset=offset,
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76 thres1=threshold1,
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77 thres2=threshold2,
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78 )
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79 if invert_output:
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80 result = np.logical_not(result)
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81
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82 # Convert to canonical representation for binary images
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83 result = (result * 255).astype(np.uint8)
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84
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85 # Write result
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86 Image(
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87 data=skimage.util.img_as_ubyte(result),
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88 axes=img_in.axes,
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89 ).normalize_axes_like(
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90 img_in.original_axes,
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91 ).write(
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92 output_filepath,
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93 )
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94
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95
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96 if __name__ == "__main__":
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97 parser = argparse.ArgumentParser(description='Automatic image thresholding')
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98 parser.add_argument('input', type=str, help='Path to the input image')
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99 parser.add_argument('output', type=str, help='Path to the output image (uint8)')
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100 parser.add_argument('th_method', choices=th_methods.keys(), help='Thresholding method')
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101 parser.add_argument('block_size', type=int, help='Odd size of pixel neighborhood for calculating the threshold')
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102 parser.add_argument('offset', type=float, help='Offset of automatically determined threshold value')
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103 parser.add_argument('threshold1', type=float, help='Manual threshold value')
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104 parser.add_argument('--threshold2', type=float, help='Second manual threshold value (for hysteresis thresholding)')
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105 parser.add_argument('--invert_output', default=False, action='store_true', help='Values below/above the threshold are labeled with 0/255 by default, and with 255/0 if this argument is used')
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106 args = parser.parse_args()
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107
4
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108 do_thresholding(
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109 args.input,
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110 args.output,
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111 args.th_method,
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112 args.block_size,
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113 args.offset,
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114 args.threshold1,
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115 args.threshold2,
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116 args.invert_output,
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117 )