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annotate landmark_registration.py @ 2:4e089a0983b1 draft

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"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
author imgteam
date Sun, 20 Feb 2022 15:46:58 +0000
parents b0503eec7bd6
children aee73493bf53
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4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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1 """
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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2 Copyright 2017-2022 Biomedical Computer Vision Group, Heidelberg University.
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3
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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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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7 """
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8
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a71239f3543a planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit d5df0e2f37920d09b5d942a7b128041ee1f0b6f5
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9 import argparse
a71239f3543a planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit d5df0e2f37920d09b5d942a7b128041ee1f0b6f5
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11 import numpy as np
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12 import pandas as pd
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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13 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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14 from skimage.measure import ransac
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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15 from skimage.transform import AffineTransform
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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18 def landmark_registration(pts_f1, pts_f2, out_f, res_th=None, max_ite=None, delimiter="\t"):
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20 points1 = pd.read_csv(pts_f1, delimiter=delimiter)
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21 points2 = pd.read_csv(pts_f2, delimiter=delimiter)
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23 src = np.concatenate([np.array(points1['x']).reshape([-1, 1]),
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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24 np.array(points1['y']).reshape([-1, 1])],
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25 axis=-1)
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26 dst = np.concatenate([np.array(points2['x']).reshape([-1, 1]),
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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27 np.array(points2['y']).reshape([-1, 1])],
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28 axis=-1)
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30 if res_th is not None and max_ite is not None:
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31 model_robust, inliers = ransac((src, dst), AffineTransform, min_samples=3, residual_threshold=res_th, max_trials=max_ite)
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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32 pd.DataFrame(model_robust.params).to_csv(out_f, header=None, index=False, sep="\t")
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a71239f3543a planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit d5df0e2f37920d09b5d942a7b128041ee1f0b6f5
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34 else:
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35 A = np.zeros((src.size, 6))
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36 A[0:src.shape[0], [0, 1]] = src
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37 A[0:src.shape[0], 2] = 1
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38 A[src.shape[0]:, [3, 4]] = src
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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39 A[src.shape[0]:, 5] = 1
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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40 b = dst.T.flatten().astype('float64')
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41 x = lstsq(A, b)
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42
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43 tmat = np.eye(3)
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44 tmat[0, :] = x[0].take([0, 1, 2])
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45 tmat[1, :] = x[0].take([3, 4, 5])
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46 pd.DataFrame(tmat).to_csv(out_f, header=None, index=False, sep="\t")
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47
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49 if __name__ == "__main__":
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50 parser = argparse.ArgumentParser(description="Estimate affine transformation matrix based on landmark coordinates")
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51 parser.add_argument("fn_pts1", help="Coordinates of SRC landmarks (tsv file)")
4e089a0983b1 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
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52 parser.add_argument("fn_pts2", help="Coordinates of DST landmarks (tsv file)")
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53 parser.add_argument("fn_tmat", help="Path the output (transformation matrix)")
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54 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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55 parser.add_argument("--max_ite", dest="max_ite", type=int, help="Maximum number of iterations for random sample selection")
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56 args = parser.parse_args()
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58 res_th = None
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59 if args.res_th:
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60 res_th = args.res_th
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61 max_ite = None
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62 if args.max_ite:
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63 max_ite = args.max_ite
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64
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65 landmark_registration(args.fn_pts1, args.fn_pts2, args.fn_tmat, res_th=res_th, max_ite=max_ite)