comparison overlay_images.py @ 2:b74693340624 draft

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/overlay_images/ commit 71dae1df58f579b84d4f9d92fb0dd509c02dd48f

1:bf590a9733ed

"""
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)

        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)

        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)

2:b74693340624

"""
Copyright 2022-2023 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.colors
import matplotlib.pyplot as plt
import numpy as np
import skimage.color
import skimage.io
import skimage.measure
import tifffile
from contours import ContourPaint


def read_im_gray(fn):
    img = skimage.io.imread(fn)
    nDims = len(img.shape)

        img = skimage.color.rgb2gray(img)
    if len(img.shape) == 3:
        return img[:, :, 0]
    else:
        return img


def get_rgb8_copy(img):
    img = np.squeeze(img)
    assert img.ndim == 2 or (img.ndim == 3 and img.shape[-1] in (3, 4))
    if str(img.dtype).startswith('float'):
        img = np.round(img * 255).astype('uint8')
    elif img.dtype == 'uint16':
        img = img // 256
    elif img.dtype != 'uint8':
        raise ValueError(f'unknown dtype: {img.dtype}')
    if img.ndim == 2:
        return np.dstack([img] * 3).copy()
    else:
        return img[:, :, :3].copy()


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)

        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, color='#ff0000', show_label=False, label_color='#ffff00'):
    img = skimage.io.imread(im1_fn)
    labels = skimage.io.imread(im2_fn)

    result = get_rgb8_copy(img)
    cp = ContourPaint(labels, linewidth, where='center')
    color_rgb = np.multiply(255, matplotlib.colors.to_rgb(color))

    for label in np.unique(labels):
        if label > 0:
            cc = (labels == label)
            bd = cp.get_contour_mask(cc)
            for i in range(3):
                result[:, :, i][bd] = color_rgb[i]

    if show_label:
        fig = plt.figure(figsize=np.divide(img.shape[:2][::-1], 100), dpi=100)
        ax = fig.add_axes([0, 0, 1, 1])
        ax.axis('off')
        ax.imshow(result)
        for reg in skimage.measure.regionprops(labels):
            ax.text(reg.centroid[1], reg.centroid[0], str(reg.label), color=label_color)
        fig.canvas.print_png(out_fn)

    else:
        skimage.io.imsave(out_fn, result)  # format of output is RGB8


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=2, type=int, help='Contour thickness')
    parser.add_argument('--color', dest='color', default='#FF0000', help='Contour color')
    parser.add_argument('--show_label', dest='show_label', action='store_true', help='Show labels')
    parser.add_argument('--label_color', dest='label_color', default='#FFFF00', help='Label color')
    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,
                    label_color=args.label_color)