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annotate filter_skimage.py @ 1:b8867c9e0526 draft default tip

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit ee4527761a958353ab636eb9e7ad7502a2f6cece
author imgteam
date Mon, 15 Dec 2025 22:25:39 +0000
parents 0cb07fefbe70
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0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
imgteam
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diff changeset
1 import argparse
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
imgteam
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2 import json
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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3 from typing import (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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4 Any,
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5 Callable,
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6 )
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7
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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8 import giatools
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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9 import numpy as np
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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10 import skimage.filters
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11
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12
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13 filters = {
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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14 'frangi': lambda img, **kwargs: (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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15 apply_nd_filter(skimage.filters.frangi, img, **kwargs)
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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16 ),
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17 'hessian': lambda img, **kwargs: (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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18 apply_nd_filter(skimage.filters.hessian, img, **kwargs)
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19 ),
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20 'laplace': lambda img, **kwargs: (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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21 apply_nd_filter(skimage.filters.laplace, img, **kwargs)
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22 ),
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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23 'meijering': lambda img, **kwargs: (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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24 apply_nd_filter(skimage.filters.meijering, img, **kwargs)
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25 ),
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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26 'sato': lambda img, **kwargs: (
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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27 apply_nd_filter(skimage.filters.sato, img, **kwargs)
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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28 ),
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29 }
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30
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31
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32 def apply_nd_filter(
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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33 filter_impl: Callable[[np.ndarray, Any, ...], np.ndarray],
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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34 img: giatools.Image,
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35 dtype: str,
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36 **kwargs: Any,
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37 ) -> giatools.Image:
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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38 """
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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39 Apply the filter to the 2-D/3-D, potentially multi-frame and multi-channel image.
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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40 """
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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41 result_data = np.empty(img.data.shape, dtype=dtype)
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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42 for qtc in np.ndindex(
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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43 img.data.shape[ 0], # Q axis
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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44 img.data.shape[ 1], # T axis
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45 img.data.shape[-1], # C axis
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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46 ):
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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47 sl = np.s_[*qtc[:2], ..., qtc[2]] # noqa: E999
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48 arr = img.data[sl]
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49 assert arr.ndim == 3 # sanity check, should always be True
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50
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51 # Perform 2-D or 3-D filtering
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52 if arr.shape[0] == 1:
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53 info = 'Performing 2-D filtering'
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54 result_data[sl][0] = filter_impl(arr[0], **kwargs).astype(dtype)
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55 else:
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56 info = 'Performing 3-D filtering'
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57 result_data[sl] = filter_impl(arr, **kwargs).astype(dtype)
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58
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59 # Print status info
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60 print(info)
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61
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62 # Return results as 16bit, 32bit, or 64bit floating point
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63 return giatools.Image(result_data.astype(dtype), img.axes)
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64
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65
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66 def apply_filter(
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67 input_filepath: str,
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68 output_filepath: str,
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69 filter_type: str,
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70 **kwargs: Any,
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71 ):
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72 # Validate and transform input parameters
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73 params = dict(kwargs)
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74 if (sigma_min := params.pop('sigma_min', None)) is not None and (sigma_max := params.pop('sigma_max', None)) is not None:
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75 num_sigma = params.pop('num_sigma')
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76 if sigma_min < sigma_max:
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77 params['sigmas'] = np.linspace(sigma_min, sigma_max, num_sigma)
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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78 elif sigma_min == sigma_max:
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79 params['sigmas'] = [sigma_min]
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80 else:
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81 raise ValueError(f'Minimum sigma ({sigma_min:g}) must not be greater than Maximum sigma ({sigma_max:g})')
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82
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83 # Read the input image
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84 img = giatools.Image.read(input_filepath)
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85
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86 # Perform filtering
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87 print(f'Applying filter: "{filter_type}"')
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88 filter_impl = filters[filter_type]
0cb07fefbe70 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/ridge_filter/ commit 85b0f6afacb8933db19e03682559cc4d71031cf1
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89 res = filter_impl(img, **params).normalize_axes_like(img.original_axes)
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90
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91 # Adopt metadata and write the result
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92 res.metadata = img.metadata
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93 res.write(output_filepath, backend='tifffile')
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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()
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98 parser.add_argument('input', type=str)
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99 parser.add_argument('output', type=str)
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100 parser.add_argument('params', type=str)
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101 args = parser.parse_args()
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102
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103 # Read the config file
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104 with open(args.params) as cfgf:
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105 cfg = json.load(cfgf)
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106
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107 apply_filter(
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108 args.input,
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109 args.output,
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110 **cfg,
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111 )