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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
author thomaswollmann
date Mon, 07 Jan 2019 05:38:46 -0500
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e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
thomaswollmann
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1 import skimage.io
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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2 from skimage.transform import ProjectiveTransform
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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3 from scipy.ndimage import map_coordinates
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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4 import numpy as np
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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5 import pandas as pd
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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6 import argparse
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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7 import warnings
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8 import shutil
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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11 def _stackcopy(a, b):
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12 if a.ndim == 3:
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13 a[:] = b[:, :, np.newaxis]
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14 else:
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15 a[:] = b
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18 def warp_coords_batch(coord_map, shape, dtype=np.float64, batch_size=1000000):
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19 rows, cols = shape[0], shape[1]
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20 coords_shape = [len(shape), rows, cols]
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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21 if len(shape) == 3:
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22 coords_shape.append(shape[2])
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23 coords = np.empty(coords_shape, dtype=dtype)
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25 tf_coords = np.indices((cols, rows), dtype=dtype).reshape(2, -1).T
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27 for i in range(0, (tf_coords.shape[0]//batch_size+1)):
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28 tf_coords[batch_size*i:batch_size*(i+1)] = coord_map(tf_coords[batch_size*i:batch_size*(i+1)])
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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29 tf_coords = tf_coords.T.reshape((-1, cols, rows)).swapaxes(1, 2)
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31 _stackcopy(coords[1, ...], tf_coords[0, ...])
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32 _stackcopy(coords[0, ...], tf_coords[1, ...])
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33 if len(shape) == 3:
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34 coords[2, ...] = range(shape[2])
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36 return coords
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39 def transform(moving_image, fixed_image, warp_matrix, out):
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40 moving_image = skimage.io.imread(moving_image)
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41 fixed_image = skimage.io.imread(fixed_image)
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42 warp_matrix = pd.read_csv(warp_matrix, delimiter=",", header=None)
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43 warp_matrix = np.array(warp_matrix)
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45 trans = ProjectiveTransform(matrix=warp_matrix)
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46 warped_coords = warp_coords_batch(trans, fixed_image.shape)
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47 t = map_coordinates(moving_image, warped_coords, mode='reflect')
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48
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49 with warnings.catch_warnings():
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50 warnings.simplefilter("ignore")
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51 skimage.io.imsave(out, t)
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53
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54 if __name__ == "__main__":
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55 parser = argparse.ArgumentParser(description="Transform the image")
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56 parser.add_argument("fixed_image", help="Paste path to image.png that should be transformed")
e3e4b058db67 planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation/ commit 787ebcc8daa1834214bc92c201c921c704ef2d1f
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57 parser.add_argument("moving_image", help="Paste path to fixed image.png")
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58 parser.add_argument("warp_matrix", help="Paste path to warp_matrix.csv that should be used for transformation")
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59 parser.add_argument("out", help="Paste path to file in which transformed image should be saved")
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60 args = parser.parse_args()
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61 transform(args.moving_image, args.fixed_image, args.warp_matrix, args.out)