Image-colored wordcloud with boundary map

A slightly more elaborate version of an image-colored wordcloud that also takes edges in the image into account. Recreating an image similar to the parrot example.

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import os
from PIL import Image

import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_gradient_magnitude

from wordcloud import WordCloud, ImageColorGenerator

# get data directory (using getcwd() is needed to support running example in generated IPython notebook)
d = os.path.dirname(__file__) if "__file__" in locals() else os.getcwd()

# load wikipedia text on rainbow
text = open(os.path.join(d, 'wiki_rainbow.txt'), encoding="utf-8").read()

# load image. This has been modified in gimp to be brighter and have more saturation.
parrot_color = np.array(Image.open(os.path.join(d, "parrot-by-jose-mari-gimenez2.jpg")))
# subsample by factor of 3. Very lossy but for a wordcloud we don't really care.
parrot_color = parrot_color[::3, ::3]

# create mask  white is "masked out"
parrot_mask = parrot_color.copy()
parrot_mask[parrot_mask.sum(axis=2) == 0] = 255

# some finesse: we enforce boundaries between colors so they get less washed out.
# For that we do some edge detection in the image
edges = np.mean([gaussian_gradient_magnitude(parrot_color[:, :, i] / 255., 2) for i in range(3)], axis=0)
parrot_mask[edges > .08] = 255

# create wordcloud. A bit sluggish, you can subsample more strongly for quicker rendering
# relative_scaling=0 means the frequencies in the data are reflected less
# acurately but it makes a better picture
wc = WordCloud(max_words=2000, mask=parrot_mask, max_font_size=40, random_state=42, relative_scaling=0)

# generate word cloud
wc.generate(text)
plt.imshow(wc)

# create coloring from image
image_colors = ImageColorGenerator(parrot_color)
wc.recolor(color_func=image_colors)
plt.figure(figsize=(10, 10))
plt.imshow(wc, interpolation="bilinear")
wc.to_file("parrot_new.png")

plt.figure(figsize=(10, 10))
plt.title("Original Image")
plt.imshow(parrot_color)

plt.figure(figsize=(10, 10))
plt.title("Edge map")
plt.imshow(edges)
plt.show()