[scikit-image] Viewing 3D images/stacks of images

[Kesavan Subburam]

from matplotlib.widgets import Slider
import matplotlib.pyplot as plt
import numpy as np

def ddd(images):
    def _update_image(num):
        num = int(num)
        image = np.squeeze(images[num:num+1])
        img_ax.set_data(image)
        fig.canvas.draw_idle()

    if images.ndim is not 3:
        raise ValueError("Not a 3D image.")

    Z, _, _ = images.shape

    fig, ax = plt.subplots()
    img_ax = ax.imshow(np.squeeze(images[0]), cmap="gray")
    ax.axis("off")

    sliderax = plt.axes([0.19, 0.05, 0.65, 0.03],
                        facecolor="lightgoldenrodyellow")
    img_slider = Slider(sliderax, "Z", 0, Z-1,
                        valfmt='%d', valinit=0)
    img_slider.on_changed(_update_image)
    plt.show()

I'd forgotten to include the import statements. Just in case you'd like to
test the code. Input image of shape (Z, N, M).

On 19 May 2017 at 22:10, Kesavan Subburam <pskeshu at gmail.com> wrote:

> Hi all,
>
> I'd used CollectionViewer from skimage.viewer before for viewing
> microscopy Z stacks. However, I personally felt it was a bit of a pain to
> use. For instance, before passing in an array of images, the image has to
> be stretched, otherwise, most of the time, one would end up with a "black"
> series of images.
>
> So, I wrote a simple function using matplotlib to view image collections,
> which works quite well, and I think it can be extended to display nD images
> with multiple sliders.
>
> def ddd(images):
>     def _update_image(num):
>         num = int(num)
>         image = np.squeeze(images[num:num+1])
>         img_ax.set_data(image)
>         fig.canvas.draw_idle()
>
>     if images.ndim is not 3:
>         raise ValueError("Not a 3D image.")
>
>     Z, _, _ = images.shape
>
>     fig, ax = plt.subplots()
>     img_ax = ax.imshow(np.squeeze(images[0]), cmap="gray")
>     ax.axis("off")
>
>     sliderax = plt.axes([0.19, 0.05, 0.65, 0.03],
>                         facecolor="lightgoldenrodyellow")
>     img_slider = Slider(sliderax, "Z", 0, Z-1,
>                         valfmt='%d', valinit=0)
>     img_slider.on_changed(_update_image)
>     plt.show()
>
>
> This might be a bit redundant, but I would like your thoughts on whether
> this might be useful for scikit-image. Some of the plugins of
> CollectionViewer can be rewritten for this matplotlib based approach in a
> much more readable fashion -- for instance, the line profile plugin.
>
> Best,
>
> --
> Kesavan Subburam
>



-- 
Kesavan
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