Created
November 1, 2010 15:22
-
-
Save nathforge/658336 to your computer and use it in GitHub Desktop.
Find the dominant colour in an image
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import colorsys | |
def get_dominant_color(image): | |
""" | |
Find a PIL image's dominant color, returning an (r, g, b) tuple. | |
""" | |
image = image.convert('RGBA') | |
# Shrink the image, so we don't spend too long analysing color | |
# frequencies. We're not interpolating so should be quick. | |
image.thumbnail((200, 200)) | |
max_score = None | |
dominant_color = None | |
for count, (r, g, b, a) in image.getcolors(image.size[0] * image.size[1]): | |
# Skip 100% transparent pixels | |
if a == 0: | |
continue | |
# Get color saturation, 0-1 | |
saturation = colorsys.rgb_to_hsv(r / 255.0, g / 255.0, b / 255.0)[1] | |
# Calculate luminance - integer YUV conversion from | |
# http://en.wikipedia.org/wiki/YUV | |
y = min(abs(r * 2104 + g * 4130 + b * 802 + 4096 + 131072) >> 13, 235) | |
# Rescale luminance from 16-235 to 0-1 | |
y = (y - 16.0) / (235 - 16) | |
# Ignore the brightest colors | |
if y > 0.9: | |
continue | |
# Calculate the score, preferring highly saturated colors. | |
# Add 0.1 to the saturation so we don't completely ignore grayscale | |
# colors by multiplying the count by zero, but still give them a low | |
# weight. | |
score = (saturation + 0.1) * count | |
if score > max_score: | |
max_score = score | |
dominant_color = (r, g, b) | |
return dominant_color |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment