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annotate landmark_registration.py @ 4:aee73493bf53 draft

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit ba383a4f617791d0c84737a179e5b4b66cecc334
author imgteam
date Mon, 18 Jul 2022 18:41:19 +0000
parents 4e089a0983b1
children 12997d4c5b00
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1 """
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2 Copyright 2017-2022 Biomedical Computer Vision Group, Heidelberg University.
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3
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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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7 """
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8
0
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9 import argparse
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11 import numpy as np
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12 import pandas as pd
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13 from scipy import spatial
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14 from scipy.linalg import lstsq
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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15 from skimage.measure import ransac
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16 from skimage.transform import AffineTransform
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19 class pwlTransform(object):
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21 def __init__(self):
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22 self.triangulation = None
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23 self.affines = None
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25 def estimate(self, src, dst):
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26 self.triangulation = spatial.Delaunay(src)
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27 success = True
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28 self.affines = []
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29 for tri in self.triangulation.simplices:
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30 affine = AffineTransform()
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31 success &= affine.estimate(src[tri, :], dst[tri, :])
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32 self.affines.append(affine)
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33 return success
aee73493bf53 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit ba383a4f617791d0c84737a179e5b4b66cecc334
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35 def __call__(self, coords):
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36 simplex = self.triangulation.find_simplex(coords)
aee73493bf53 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit ba383a4f617791d0c84737a179e5b4b66cecc334
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37 simplex[simplex == -1] = 0 # todo: dealing with points outside the triangulation
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38 out = np.empty_like(coords, np.float64)
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39 for i in range(len(self.triangulation.simplices)):
aee73493bf53 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit ba383a4f617791d0c84737a179e5b4b66cecc334
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40 idx = simplex == i
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41 out[idx, :] = self.affines[i](coords[idx, :])
aee73493bf53 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit ba383a4f617791d0c84737a179e5b4b66cecc334
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42 return out
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45 def landmark_registration(pts_f1, pts_f2, out_f, pts_f=None, res_th=None, max_ite=None, delimiter="\t"):
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47 points1 = pd.read_csv(pts_f1, delimiter=delimiter)
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48 points2 = pd.read_csv(pts_f2, delimiter=delimiter)
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49
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50 src = np.concatenate([np.array(points1['x']).reshape([-1, 1]),
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51 np.array(points1['y']).reshape([-1, 1])],
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52 axis=-1)
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53 dst = np.concatenate([np.array(points2['x']).reshape([-1, 1]),
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54 np.array(points2['y']).reshape([-1, 1])],
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55 axis=-1)
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56
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57 if res_th is not None and max_ite is not None:
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58 model_robust, inliers = ransac((src, dst), AffineTransform, min_samples=3, residual_threshold=res_th, max_trials=max_ite)
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59 pd.DataFrame(model_robust.params).to_csv(out_f, header=None, index=False, sep="\t")
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61 elif pts_f is not None:
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62 pwlt = pwlTransform()
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63 pwlt.estimate(src, dst)
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64
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65 pts_df = pd.read_csv(pts_f, delimiter=delimiter)
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66 pts = np.concatenate([np.array(pts_df['x']).reshape([-1, 1]),
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67 np.array(pts_df['y']).reshape([-1, 1])],
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68 axis=-1)
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69 pts_pwlt = pwlt(pts)
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70
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71 df = pd.DataFrame()
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72 df['x'] = pts_pwlt[:, 0]
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73 df['y'] = pts_pwlt[:, 1]
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74 df.to_csv(out_f, index=False, sep="\t", float_format='%.1f')
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75
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76 else:
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77 A = np.zeros((src.size, 6))
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78 A[0:src.shape[0], [0, 1]] = src
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79 A[0:src.shape[0], 2] = 1
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80 A[src.shape[0]:, [3, 4]] = src
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81 A[src.shape[0]:, 5] = 1
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82 b = dst.T.flatten().astype('float64')
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83 x = lstsq(A, b)
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84
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85 tmat = np.eye(3)
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86 tmat[0, :] = x[0].take([0, 1, 2])
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87 tmat[1, :] = x[0].take([3, 4, 5])
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88 pd.DataFrame(tmat).to_csv(out_f, header=None, index=False, sep="\t")
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89
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91 if __name__ == "__main__":
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92 parser = argparse.ArgumentParser(description="estimates the affine transformation matrix or performs piecewiese affine transformation based on landmarks")
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93 parser.add_argument("fn_lmkmov", help="Coordinates of moving landmarks (tsv file)")
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94 parser.add_argument("fn_lmkfix", help="Coordinates of fixed landmarks (tsv file)")
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95 parser.add_argument("fn_out", help="Path to the output")
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96 parser.add_argument("--pwlt", dest="fn_ptsmov", help="Coordinates of points to be transformed (tsv file)")
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97 parser.add_argument("--res_th", dest="res_th", type=float, help="Maximum distance for a data point to be classified as an inlier")
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98 parser.add_argument("--max_ite", dest="max_ite", type=int, help="Maximum number of iterations for random sample selection")
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99 args = parser.parse_args()
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100
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101 fn_ptsmov = None
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102 if args.fn_ptsmov:
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103 fn_ptsmov = args.fn_ptsmov
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104 res_th = None
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105 if args.res_th:
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106 res_th = args.res_th
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107 max_ite = None
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108 if args.max_ite:
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109 max_ite = args.max_ite
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110
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111 landmark_registration(args.fn_lmkmov, args.fn_lmkfix, args.fn_out, pts_f=fn_ptsmov, res_th=res_th, max_ite=max_ite)