Mercurial > repos > imgteam > projective_transformation_points

comparison projective_transformation_points.py @ 1:ae600b1c6c48 draft

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planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation_points/ commit 201f4231192bc368b14e72bb1314b9a97b8db8d0
author imgteam
date Wed, 27 Mar 2019 14:54:13 -0400
parents dd792352f2a7
children 2749345d62fa
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0:dd792352f2a7 1:ae600b1c6c48
3 import pandas as pd 3 import pandas as pd
4 import argparse 4 import argparse
5 5
6 6
7 def warp_coords_batch(coord_map, coords, dtype=np.float64, batch_size=1000000): 7 def warp_coords_batch(coord_map, coords, dtype=np.float64, batch_size=1000000):
8 tf_coords = coords.astype(np.float32) 8 tf_coords = coords.astype(np.float32)[:, ::-1]
9 9
10 for i in range(0, (tf_coords.shape[0]//batch_size+1)): 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)]) 11 tf_coords[batch_size*i:batch_size*(i+1)] = coord_map(tf_coords[batch_size*i:batch_size*(i+1)])
12 12
13 return np.unique(np.round(tf_coords).astype(coords.dtype),axis=0) 13 return np.unique(np.round(tf_coords).astype(coords.dtype),axis=0)[:, ::-1]
14 14
15 15
16 def transform(coords, warp_matrix, out): 16 def transform(coords, warp_matrix, out):
17 indices = np.array(pd.read_csv(coords, delimiter="\t")) 17 indices = np.array(pd.read_csv(coords, delimiter="\t"))
18 a_matrix = np.array(pd.read_csv(warp_matrix, delimiter="\t", header=None)) 18 a_matrix = np.array(pd.read_csv(warp_matrix, delimiter="\t", header=None))