# HG changeset patch # User imgteam # Date 1645895667 0 # Node ID b4fc6e09e576fa05e2281d6057b45c4f28e30e92 # Parent bc324ec667198e12acf7304460788a05c9f5c499 "planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/overlay_moving_and_fixed_image/ commit 0500f513ee291ae0f6fad32a0b4fad05cd59cb71" diff -r bc324ec66719 -r b4fc6e09e576 overlay_moving_and_fixed_image.py --- a/overlay_moving_and_fixed_image.py Wed Dec 18 05:02:39 2019 -0500 +++ b/overlay_moving_and_fixed_image.py Sat Feb 26 17:14:27 2022 +0000 @@ -1,11 +1,12 @@ import argparse -from PIL import Image -import skimage.io -import skimage.color -from skimage.transform import ProjectiveTransform -from scipy.ndimage import map_coordinates + import numpy as np import pandas as pd +import skimage.color +import skimage.io +from PIL import Image +from scipy.ndimage import map_coordinates +from skimage.transform import ProjectiveTransform def _stackcopy(a, b): @@ -24,12 +25,12 @@ tf_coords = np.indices((cols, rows), dtype=dtype).reshape(2, -1).T - for i in range(0, (tf_coords.shape[0]//batch_size+1)): - tf_coords[batch_size*i:batch_size*(i+1)] = coord_map(tf_coords[batch_size*i:batch_size*(i+1)]) + for i in range(0, (tf_coords.shape[0] // batch_size + 1)): + tf_coords[batch_size * i:batch_size * (i + 1)] = coord_map(tf_coords[batch_size * i:batch_size * (i + 1)]) tf_coords = tf_coords.T.reshape((-1, cols, rows)).swapaxes(1, 2) _stackcopy(coords[1, ...], tf_coords[0, ...]) - _stackcopy(coords[0, ...], tf_coords[1, ...]) + _stackcopy(coords[0, ...], tf_coords[1, ...]) if len(shape) == 3: coords[2, ...] = range(shape[2]) @@ -47,16 +48,16 @@ fixed_image = Image.fromarray(fixed_image).convert("RGBA") overlay_out = Image.blend(moving_image, fixed_image, factor) overlay_out.save(overlay_out_path, "PNG") - + -if __name__=="__main__": - parser = argparse.ArgumentParser(description = "Overlay two images") - parser.add_argument("fixed_image", help = "Path to fixed image") - parser.add_argument("moving_image", help = "Path to moving image") +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Overlay two images") + parser.add_argument("fixed_image", help="Path to fixed image") + parser.add_argument("moving_image", help="Path to moving image") parser.add_argument("warp_matrix", help="Paste path to warp_matrix.csv that should be used for transformation") parser.add_argument("--inverse_transform", dest='inverse_transform', action='store_true', help="Set if inverse transform should be visualized") - parser.add_argument("--factor", dest = "factor", help = "Enter the factor by which images should be blended, 1.0 returns a copy of second image", type = float, default = 0.5) - parser.add_argument("overlay_out", help = "Overlay output path") + parser.add_argument("--factor", dest="factor", help="Enter the factor by which images should be blended, 1.0 returns a copy of second image", type=float, default=0.5) + parser.add_argument("overlay_out", help="Overlay output path") args = parser.parse_args() fixed_image = skimage.io.imread(args.fixed_image) diff -r bc324ec66719 -r b4fc6e09e576 overlay_moving_and_fixed_image.xml --- a/overlay_moving_and_fixed_image.xml Wed Dec 18 05:02:39 2019 -0500 +++ b/overlay_moving_and_fixed_image.xml Sat Feb 26 17:14:27 2022 +0000 @@ -1,4 +1,4 @@ - + moving and fixed image scikit-image @@ -42,6 +42,8 @@ **What it does** This tool performs an overlay of two images of which one was transformed to match the other. + + Note: This tool is deprecated and may not be supported in future. Please use the tools "Projective Transformation" and "Overlay Images" instead. 10.1016/j.jbiotec.2017.07.019