Mercurial > repos > imgteam > projective_transformation_points
comparison projective_transformation_points.py @ 0:ed8a71e13f7b draft
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation_points/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
author | imgteam |
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date | Sat, 09 Feb 2019 14:45:19 -0500 |
parents | |
children | f1744c5654b9 |
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-1:000000000000 | 0:ed8a71e13f7b |
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1 from skimage.transform import ProjectiveTransform | |
2 import numpy as np | |
3 import pandas as pd | |
4 import argparse | |
5 | |
6 | |
7 def warp_coords_batch(coord_map, coords, dtype=np.float64, batch_size=1000000): | |
8 tf_coords = coords.astype(np.float32) | |
9 | |
10 for i in range(0, (tf_coords.shape[0]//batch_size+1)): | |
11 tf_coords[batch_size*i:batch_size*(i+1)] = coord_map(tf_coords[batch_size*i:batch_size*(i+1)]) | |
12 | |
13 return np.unique(np.round(tf_coords).astype(coords.dtype),axis=0) | |
14 | |
15 | |
16 def transform(coords, warp_matrix, out): | |
17 indices = np.array(pd.read_csv(coords, delimiter="\t")) | |
18 a_matrix = np.array(pd.read_csv(warp_matrix, delimiter="\t", header=None)) | |
19 | |
20 trans = ProjectiveTransform(matrix=a_matrix) | |
21 warped_coords = warp_coords_batch(trans, indices) | |
22 | |
23 df = pd.DataFrame() | |
24 df['x'] = warped_coords[:,0] | |
25 df['y'] = warped_coords[:,1] | |
26 df.to_csv(out, index = False, sep="\t") | |
27 | |
28 | |
29 if __name__ == "__main__": | |
30 parser = argparse.ArgumentParser(description="Transform coordinates") | |
31 parser.add_argument("coords", help="Paste path to .csv with coordinates to transform (tab separated)") | |
32 parser.add_argument("warp_matrix", help="Paste path to .csv that should be used for transformation (, separated)") | |
33 parser.add_argument("out", help="Paste path to file in which transformed coords should be saved (tab separated)") | |
34 args = parser.parse_args() | |
35 transform(args.coords, args.warp_matrix, args.out) |