| Next changeset 1:bf590a9733ed (2022-07-19) |
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Commit message:
"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/overlay_images/ commit 736949b5fb325cc7880d0ff0bb13b78115b9f81c" |
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added:
overlay_images.py overlay_images.xml test-data/mask1.tif test-data/mask1r.tif test-data/sample1.tif test-data/test1.tif test-data/test2.tif test-data/test3.tif |
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| diff -r 000000000000 -r 589af0005df5 overlay_images.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/overlay_images.py Sat Feb 26 15:16:10 2022 +0000 |
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| @@ -0,0 +1,95 @@ +""" +Copyright 2022 Biomedical Computer Vision Group, Heidelberg University. + +Distributed under the MIT license. +See file LICENSE for detail or copy at https://opensource.org/licenses/MIT + +""" + +import argparse + +import matplotlib.pyplot as plt +import numpy as np +import skimage.color +import skimage.io +import skimage.measure +import tifffile + + +def read_im_gray(fn): + img = skimage.io.imread(fn) + nDims = len(img.shape) + assert nDims in [2, 3], 'this tool only supports single 2D images' + if nDims == 3 and img.shape[-1] in [3, 4]: + img = skimage.color.rgb2gray(img) + if len(img.shape) == 3: + return img[:, :, 0] + else: + return img + + +def coloc_vis(in_red_fn, in_green_fn, out_fn): + im1 = read_im_gray(in_red_fn) + im2 = read_im_gray(in_green_fn) + assert im1.shape == im2.shape, 'Two images should have the same dimension' + + vmin = np.min([np.min(im1), np.min(im2)]) + scal = 255.0 / (np.max([np.max(im1), np.max(im2)]) - vmin) + + out_im = np.zeros(im1.shape + (3,), dtype=np.ubyte) + out_im[:, :, 0] = (im1 - vmin) * scal + out_im[:, :, 1] = (im2 - vmin) * scal + skimage.io.imsave(out_fn, out_im) # output is RGB + + +def blending(im1_fn, im2_fn, out_fn, alpha=0.5): + im1 = skimage.io.imread(im1_fn) + im2 = skimage.io.imread(im2_fn) + assert im1.shape == im2.shape, 'Two images should have the same dimension' + out_im = (1 - alpha) * im1 + alpha * im2 + if len(im1.shape) > 3: + tifffile.imwrite(out_fn, out_im.astype(im1.dtype), imagej=True) + else: + skimage.io.imsave(out_fn, out_im.astype(im1.dtype)) # format of output is the same as input + + +def seg_contour(im1_fn, im2_fn, out_fn, linewidth=0.3, color='#ff0000', show_label=False): + img = skimage.io.imread(im1_fn) + label = skimage.io.imread(im2_fn) + + fig = plt.figure() + ax = fig.add_axes([0, 0, 1, 1]) + ax.axis('off') + if show_label: + for reg in skimage.measure.regionprops(label): + ax.text(reg.centroid[1], reg.centroid[0], str(reg.label), color=color) + + if len(img.shape) == 2: + plt.imshow(img, cmap=plt.cm.gray) + else: + plt.imshow(img) + plt.contour(label, linewidths=linewidth, colors=color) + fig.canvas.print_png(out_fn) # output is RGB + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Overlay two images") + parser.add_argument("im1", help="The first image") + parser.add_argument("im2", help="The second image") + parser.add_argument("out", help="Output image") + parser.add_argument('--method', dest='method', default='coloc_vis', help='How to overlay images') + parser.add_argument('--alpha', dest='alpha', default=0.5, type=float, help='Blending weight') + parser.add_argument('--thickness', dest='thickness', default=0.3, type=float, help='Contour thickness') + parser.add_argument('--color', dest='color', default='#FFFF00', help='Contour color') + parser.add_argument('--show_label', dest='show_label', action='store_true', help='Plot label') + args = parser.parse_args() + + if args.method == 'coloc_vis': + coloc_vis(args.im1, args.im2, args.out) + elif args.method == 'blending': + blending(args.im1, args.im2, args.out, alpha=args.alpha) + elif args.method == 'seg_contour': + seg_contour(args.im1, args.im2, args.out, + linewidth=args.thickness, + color=args.color, + show_label=args.show_label) |
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| diff -r 000000000000 -r 589af0005df5 overlay_images.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/overlay_images.xml Sat Feb 26 15:16:10 2022 +0000 |
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| @@ -0,0 +1,88 @@ +<tool id="ip_overlay_images" name="Overlay Images" version="0.0.1" profile="20.05"> + <description>for visualization</description> + <requirements> + <requirement type="package" version="0.18.1">scikit-image</requirement> + <requirement type="package" version="3.3.4">matplotlib</requirement> + <requirement type="package" version="2020.10.1">tifffile</requirement> + <requirement type="package" version="1.20.2">numpy</requirement> + </requirements> + <command detect_errors="aggressive"> + <![CDATA[ + python '$__tool_directory__/overlay_images.py' + '$im1' '$im2' ./output.tif + --method '$method_option.method' + #if '$method_option.method' == 'blending': + --alpha '$alpha' + #elif '$method_option.method' == 'seg_contour': + --thickness '$thickness' + --color '$color' + $show_label + #end if + ]]> + </command> + <inputs> + <conditional name="method_option"> + <param name="method" type="select" label="How to visualize the overlay?"> + <option value="coloc_vis" selected="True">Colocalization</option> + <option value="blending">Blending</option> + <option value="seg_contour">Segmentation mask over image</option> + </param> + <when value="coloc_vis"> + <param name="im1" type="data" format="tiff,png" label="Image #1 (red channel)" /> + <param name="im2" type="data" format="tiff,png" label="Image #2 (green channel)" /> + </when> + <when value="blending"> + <param name="im1" type="data" format="tiff,png" label="Image #1" /> + <param name="im2" type="data" format="tiff,png" label="Image #2" /> + <param name="alpha" type="float" value="0.5" min="0.0" max="1.0" label="The weight for blending: I_out = (1 - w) * I_1 + w * I_2."/> + </when> + <when value="seg_contour"> + <param name="im1" type="data" format="tiff,png" label="Image" /> + <param name="im2" type="data" format="tiff,png" label="Label image" /> + <param name="thickness" type="float" value="0.3" label="Contour thickness" /> + <param name="color" type="color" value="#ff0000" label="Contour color"/> + <param argument="--show_label" type="boolean" checked='false' truevalue="--show_label" falsevalue="" label="Show labels" /> + </when> + </conditional> + </inputs> + <outputs> + <data format="tiff" name="out" from_work_dir="output.tif" /> + </outputs> + <tests> + <test> + <param name="im1" value="mask1.tif"/> + <param name="im2" value="mask1r.tif"/> + <conditional name="method_option"> + <param name="method" value="coloc_vis"/> + </conditional> + <output name="out" value="test1.tif" ftype="tiff" compare="sim_size" delta_frac="0.1"/> + </test> + <test> + <param name="im1" value="mask1.tif"/> + <param name="im2" value="mask1r.tif"/> + <conditional name="method_option"> + <param name="method" value="blending"/> + </conditional> + <param name="alpha" value="0.3"/> + <output name="out" value="test2.tif" ftype="tiff" compare="sim_size" delta_frac="0.1"/> + </test> + <test> + <param name="im1" value="sample1.tif"/> + <param name="im2" value="mask1.tif"/> + <conditional name="method_option"> + <param name="method" value="seg_contour"/> + </conditional> + <param name="thickness" value="0.4"/> + <param name="color" value="#ffaa00"/> + <param name="show_label" value="true"/> + <output name="out" value="test3.tif" ftype="tiff" compare="sim_size" delta="20000" delta_frac="0.2"/> + </test> + </tests> + <help> + **What it does** + + This tool overlays two image to visualize 1) image blending, 2) colocalization, or 3) a segmentation mask over an image. + </help> + <citations> + </citations> +</tool> |
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