Mercurial > repos > imgteam > landmark_registration_ls

comparison landmark_registration_ls.py @ 1:69db8c7d4244 draft default tip

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"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/landmark_registration_ls/ commit 927b78d47c31714776ccdf3d16f26c3779298abb"
author imgteam
date Sun, 20 Feb 2022 15:47:16 +0000
parents 2f36165c49fb
children
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0:2f36165c49fb 1:69db8c7d4244
1 from scipy.linalg import lstsq
2 import pandas as pd
3 import numpy as np
4 import argparse 1 import argparse
5 2
3 import numpy as np
4 import pandas as pd
5 from scipy.linalg import lstsq
6
7
6 def landmark_registration_ls(pts_f1, pts_f2, out_f, delimiter="\t"): 8 def landmark_registration_ls(pts_f1, pts_f2, out_f, delimiter="\t"):
7 9
8 points1 = pd.read_csv(pts_f1, delimiter=delimiter) 10 points1 = pd.read_csv(pts_f1, delimiter=delimiter)
9 points2 = pd.read_csv(pts_f2, delimiter=delimiter) 11 points2 = pd.read_csv(pts_f2, delimiter=delimiter)
10 12
11 src = np.concatenate([np.array(points1['x']).reshape([-1,1]), 13 src = np.concatenate([np.array(points1['x']).reshape([-1, 1]),
12 np.array(points1['y']).reshape([-1,1])], 14 np.array(points1['y']).reshape([-1, 1])],
13 axis=-1) 15 axis=-1)
14 dst = np.concatenate([np.array(points2['x']).reshape([-1,1]), 16 dst = np.concatenate([np.array(points2['x']).reshape([-1, 1]),
15 np.array(points2['y']).reshape([-1,1])], 17 np.array(points2['y']).reshape([-1, 1])],
16 axis=-1) 18 axis=-1)
17 19
18 A = np.zeros((src.size,6)) 20 A = np.zeros((src.size, 6))
19 A[0:src.shape[0],[0,1]] = src 21 A[0:src.shape[0], [0, 1]] = src
20 A[0:src.shape[0],2] = 1 22 A[0:src.shape[0], 2] = 1
21 A[src.shape[0]:,[3,4]] = src 23 A[src.shape[0]:, [3, 4]] = src
22 A[src.shape[0]:,5] = 1 24 A[src.shape[0]:, 5] = 1
23 b = dst.T.flatten().astype('float64') 25 b = dst.T.flatten().astype('float64')
24 x = lstsq(A,b) 26 x = lstsq(A, b)
25 27
26 tmat = np.eye(3) 28 tmat = np.eye(3)
27 tmat[0,:] = x[0].take([0,1,2]) 29 tmat[0, :] = x[0].take([0, 1, 2])
28 tmat[1,:] = x[0].take([3,4,5]) 30 tmat[1, :] = x[0].take([3, 4, 5])
29 pd.DataFrame(tmat).to_csv(out_f, header=None, index=False, sep="\t") 31 pd.DataFrame(tmat).to_csv(out_f, header=None, index=False, sep="\t")
30 32
31 33
32 if __name__ == "__main__": 34 if __name__ == "__main__":
33
34 parser = argparse.ArgumentParser(description="Estimate transformation from points using least squares") 35 parser = argparse.ArgumentParser(description="Estimate transformation from points using least squares")
35
36 parser.add_argument("fn_pts1", help="File name src points") 36 parser.add_argument("fn_pts1", help="File name src points")
37 parser.add_argument("fn_pts2", help="File name dst points") 37 parser.add_argument("fn_pts2", help="File name dst points")
38 parser.add_argument("fn_tmat", help="File name transformation matrix") 38 parser.add_argument("fn_tmat", help="File name transformation matrix")
39 args = parser.parse_args() 39 args = parser.parse_args()
40 40
41 landmark_registration_ls(args.fn_pts1, args.fn_pts2, args.fn_tmat) 41 landmark_registration_ls(args.fn_pts1, args.fn_pts2, args.fn_tmat)
42
43