Python judge, get a picture of 2 instances of the main hue _python

Python determines the primary hue of a picture, a single color:

Copy Code code as follows:

#!/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 a (R, G, b) tuple.
"""

Image = Image.convert (' RGBA ')

# Shrink The image, so we don ' t spend too long analysing color
# frequencies. We don't interpolating so should to 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 * + 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 determines the primary hue of a picture, multiple colors:

Copy Code code as follows:

#!/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 a (R, G, b) tuple.
"""

Image = Image.convert (' RGBA ')

# Shrink The image, so we don ' t spend too long analysing color
# frequencies. We don't interpolating so should to 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 * + 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 ()