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python判断、获取一张图片主色调的2个实例

2019年03月31日  | 移动技术网IT编程  | 我要评论

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python判断图片主色调，单个颜色：

复制代码 代码如下:

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import colorsys
from pil import image
import optparse

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

def main():
img = image.open("meitu.jpg")
print '#%02x%02x%02x' % get_dominant_color(img)

if __name__ == '__main__':
main()

python判断一张图片的主色调，多个颜色：

复制代码 代码如下:

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import colorsys
from pil import image
import optparse

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 = 1
dominant_color = []

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.append((r, g, b))

return dominant_color

def main():
img = image.open("meitu.jpg")
colors = get_dominant_color(img)
for item in colors:
print '#%02x%02x%02x' % item

if __name__ == '__main__':
main()

 

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