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colors: Use kmeans to generate a palette.

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Dylan Araps 2017-12-28 17:07:33 +11:00
parent 514f81a2c5
commit 4f7dc74b13
1 changed files with 19 additions and 16 deletions
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33
pywal/colors.py
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@ -17,14 +17,11 @@ from . import util
def sort_colors(img, colors): def sort_colors(img, colors):
"""Sort the generated colors and store them in a dict that """Sort the generated colors and store them in a dict that
we will later save in json format.""" we will later save in json format."""
# raw_colors = [colors[0], *colors[15:23], *colors[15:23]]
raw_colors = [colors[0], *colors[8:], *colors[8:]] raw_colors = [colors[0], *colors[8:], *colors[8:]]
# Darken the background color if it's too light. # Darken the background color if it's too light.
# The value can be a letter or an int so we treat the # The value can be a letter or an int so we treat the
# entire test as strings. # entire test as strings.
print(raw_colors[0][1])
if raw_colors[0][1] not in ["0", "1", "2"]:
raw_colors[0] = util.darken_color(raw_colors[0], 0.25) raw_colors[0] = util.darken_color(raw_colors[0], 0.25)
# Create a comment color from the background. # Create a comment color from the background.
@ -47,31 +44,37 @@ def sort_colors(img, colors):
def kmeans(img, color_count): def kmeans(img, color_count):
"""Get colors using kmeans.""" """Get colors using kmeans."""
numpy.warnings.filterwarnings('ignore')
numpy.random.seed(12345)
# Process the image.
image = Image.open(img) image = Image.open(img)
image.thumbnail((100, 100), Image.ANTIALIAS) image.thumbnail((100, 100), Image.ANTIALIAS)
enhancer = ImageEnhance.Brightness(image) enhancer = ImageEnhance.Brightness(image)
image = enhancer.enhance(1.0) image = enhancer.enhance(1.2)
# Turn the image into an array.
arr = numpy.asarray(image) arr = numpy.asarray(image)
shape = arr.shape arr = arr.reshape(scipy.product(arr.shape[:2]), arr.shape[2]).astype(float)
arr = arr.reshape(scipy.product(shape[:2]), shape[2]).astype(float)
colors = scipy.cluster.vq.kmeans2(arr, color_count*2)[0] centroids, labels = scipy.cluster.vq.kmeans2(arr, color_count,
check_finite=False,
minit="points")
if len(colors) < 16: counts = numpy.unique(labels, return_counts=True)[1]
print("error: Failed to find enough colors.") best_centroid = numpy.argsort(counts)[::-1]
exit(1) colors = centroids[best_centroid].astype(int)
colors = colors.tolist()
colors = [list(map(int, color)) for color in colors.tolist()]
# Calculate brightness
for color in colors: for color in colors:
red, gre, blu = color red, gre, blu = color[:3]
color.append((red+red+blu+gre+gre+gre) / 6) color.append((red+red+blu+gre+gre+gre) / 6)
# Sort the colors by brightness.
colors = sorted(colors, key=lambda e: e[3]) colors = sorted(colors, key=lambda e: e[3])
del colors[1::2]
return ["#%02x%02x%02x" % tuple(color[:-1]) for color in colors] return ["#%02x%02x%02x" % tuple(color[:3]) for color in colors]
def get(img, cache_dir=CACHE_DIR, def get(img, cache_dir=CACHE_DIR,