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islic.py

%matplotlib inline
from skimage import img_as_float
import numpy as np
from matplotlib import pyplot as plt

def imshow_all(*images, **kwargs):
    """ Plot a series of images side-by-side.

    Convert all images to float so that images have a common intensity range.

    Parameters
    ----------
    limits : str
        Control the intensity limits. By default, 'image' is used set the
        min/max intensities to the min/max of all images. Setting `limits` to
        'dtype' can also be used if you want to preserve the image exposure.
    titles : list of str
        Titles for subplots. If the length of titles is less than the number
        of images, empty strings are appended.
    kwargs : dict
        Additional keyword-arguments passed to `imshow`.
    """
    images = [img_as_float(img) for img in images]

    titles = kwargs.pop('titles', [])
    if len(titles) != len(images):
        titles = list(titles) + [''] * (len(images) - len(titles))

    limits = kwargs.pop('limits', 'image')
    if limits == 'image':
        kwargs.setdefault('vmin', min(img.min() for img in images))
        kwargs.setdefault('vmax', max(img.max() for img in images))
    elif limits == 'dtype':
        vmin, vmax = dtype_limits(images[0])
        kwargs.setdefault('vmin', vmin)
        kwargs.setdefault('vmax', vmax)

    nrows, ncols = kwargs.get('shape', (1, len(images)))

    size = nrows * kwargs.pop('size', 5)
    width = size * len(images)
    if nrows > 1:
        width /= nrows * 1.33
    fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(width, size))
    for ax, img, label in zip(axes.ravel(), images, titles):
        ax.imshow(img, **kwargs)
        ax.set_title(label)

def mean_color(image, labels):
    out = np.zeros_like(image)
    for label in np.unique(labels):
        indices = np.nonzero(labels == label)
        out[indices] = np.mean(image[indices], axis=0)
    return out

from skimage import data, segmentation as seg
image = data.lena()

def islic(*args, **kwargs):
    labels = seg.slic(image, *args, **kwargs)
    label_image = mean_color(image, labels)
    imshow_all(image, label_image) # plot two items side by side
    plt.show()

from IPython.html import widgets
widgets.interact(islic, n_segments=(20, 100, 5), enforce_connectivity=True,
                 compactness=(20., 100., 10.), sigma=(0., 5., 0.1),
                 slic_zero=False)