Mercurial > repos > imgteam > overlay_moving_and_fixed_image
changeset 0:165a9330fc90 draft
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/overlay_moving_and_fixed_image/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
| author | imgteam |
|---|---|
| date | Sat, 09 Feb 2019 14:39:40 -0500 |
| parents | |
| children | bc324ec66719 |
| files | overlay_moving_and_fixed_image.py overlay_moving_and_fixed_image.xml test-data/out.png test-data/sample1.png test-data/sample2.png test-data/warp_matrix.tsv |
| diffstat | 6 files changed, 124 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/overlay_moving_and_fixed_image.py Sat Feb 09 14:39:40 2019 -0500 @@ -0,0 +1,73 @@ +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 + + +def _stackcopy(a, b): + if a.ndim == 3: + a[:] = b[:, :, np.newaxis] + else: + a[:] = b + + +def warp_coords_batch(coord_map, shape, dtype=np.float64, batch_size=1000000): + rows, cols = shape[0], shape[1] + coords_shape = [len(shape), rows, cols] + if len(shape) == 3: + coords_shape.append(shape[2]) + coords = np.empty(coords_shape, dtype=dtype) + + 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)]) + tf_coords = tf_coords.T.reshape((-1, cols, rows)).swapaxes(1, 2) + + _stackcopy(coords[1, ...], tf_coords[0, ...]) + _stackcopy(coords[0, ...], tf_coords[1, ...]) + if len(shape) == 3: + coords[2, ...] = range(shape[2]) + + return coords + + +def transform(moving_image, fixed_image, warp_matrix): + trans = ProjectiveTransform(matrix=warp_matrix) + warped_coords = warp_coords_batch(trans, fixed_image.shape) + return map_coordinates(moving_image, warped_coords) + + +def overlay(moving_image, fixed_image, factor, overlay_out_path): + moving_image = Image.fromarray(moving_image).convert("RGBA") + 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") + 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") + args = parser.parse_args() + + fixed_image = skimage.io.imread(args.fixed_image) + moving_image = skimage.io.imread(args.moving_image) + + warp_matrix = pd.read_csv(args.warp_matrix, delimiter="\t", header=None) + warp_matrix = np.array(warp_matrix) + if args.inverse_transform: + fixed_image = transform(fixed_image, moving_image, warp_matrix) + else: + warp_matrix = np.linalg.inv(warp_matrix) + moving_image = transform(moving_image, fixed_image, warp_matrix) + + overlay(moving_image, fixed_image, args.factor, args.overlay_out)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/overlay_moving_and_fixed_image.xml Sat Feb 09 14:39:40 2019 -0500 @@ -0,0 +1,48 @@ +<tool id="ip_viz_overlay_moving_and_fixed_image" name="Overlay" version="0.0.1"> + <description>moving and fixed image</description> + <requirements> + <requirement type="package" version="0.14.2">scikit-image</requirement> + <requirement type="package" version="0.23.4">pandas</requirement> + <requirement type="package" version="1.15.4">numpy</requirement> + <requirement type="package" version="1.1.0">scipy</requirement> + <requirement type="package" version="5.3.0">pillow</requirement> + </requirements> + <command><![CDATA[ + python '$__tool_directory__/overlay_moving_and_fixed_image.py' + '$fixed_image' + '$moving_image' + '$warp_matrix' + '$overlay_out' + --factor $factor + $inverse_transform + ]]></command> + <inputs> + <param name="fixed_image" type= "data" format="png" label="Fixed image" /> + <param name="moving_image" type= "data" format="png" label="Moving image" /> + <param name="warp_matrix" type= "data" format="tabular" label="Warp Matrix" /> + <param name="factor" type="float" value="0.5" + label="Factor by which images are blended. 1.0 returns a copy of the fixed image, 0.0 returns a copy of the moving image."/> + <param name="inverse_transform" type="boolean" checked="false" truevalue="--inverse_transform" falsevalue="" + label="Set to Yes if inverse transformation should be displayed" /> + </inputs> + <outputs> + <data format="png" name="overlay_out" /> + </outputs> + <tests> + <test> + <param name="fixed_image" value="sample1.png" /> + <param name="moving_image" value="sample2.png" /> + <param name="warp_matrix" value="warp_matrix.tsv" /> + <param name="factor" value="0.75" /> + <output name="overlay_out" value="out.png" ftype="png" compare="sim_size" /> + </test> + </tests> + <help> + **What it does** + + This tool performs an overlay of two images of which one was transformed to match the other. + </help> + <citations> + <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation> + </citations> +</tool>