# -*- coding: utf-8 -*-
"""
Sub-module providing color functions.
References,
-
https://en.wikipedia.org/wiki/Color_difference
-
http://www.easyrgb.com/en/math.php
- Measuring Colour by R.W.G. Hunt
and M.R. Pointer
"""
# std imports
from math
import cos, exp, sin, sqrt, atan2
# isort: off
try:
from functools
import lru_cache
except ImportError:
# lru_cache was added in Python 3.2
from backports.functools_lru_cache
import lru_cache
def rgb_to_xyz(red, green, blue):
"""
Convert standard RGB color to XYZ color.
:arg int red: RGB value of Red.
:arg int green: RGB value of Green.
:arg int blue: RGB value of Blue.
:returns: Tuple (X, Y, Z) representing XYZ color
:rtype: tuple
D65/
2° standard illuminant
"""
rgb = []
for val
in red, green, blue:
val /=
255.
0
if val >
0.
04045:
val = pow((val +
0.
055) /
1.
055,
2.
4)
else:
val /=
12.
92
val *=
100
rgb.append(val)
red, green, blue = rgb
# pylint: disable=unbalanced-tuple-unpacking
x_val = red *
0.
4124 + green *
0.
3576 + blue *
0.
1805
y_val = red *
0.
2126 + green *
0.
7152 + blue *
0.
0722
z_val = red *
0.
0193 + green *
0.
1192 + blue *
0.
9505
return x_val, y_val, z_val
def xyz_to_lab(x_val, y_val, z_val):
"""
Convert XYZ color to CIE-Lab color.
:arg float x_val: XYZ value of X.
:arg float y_val: XYZ value of Y.
:arg float z_val: XYZ value of Z.
:returns: Tuple (L, a, b) representing CIE-Lab color
:rtype: tuple
D65/
2° standard illuminant
"""
xyz = []
for val, ref
in (x_val,
95.
047), (y_val,
100.
0), (z_val,
108.
883):
val /= ref
val = pow(val,
1 /
3.
0)
if val >
0.
008856 else 7.
787 * val +
16 /
116.
0
xyz.append(val)
x_val, y_val, z_val = xyz
# pylint: disable=unbalanced-tuple-unpacking
cie_l =
116 * y_val -
16
cie_a =
500 * (x_val - y_val)
cie_b =
200 * (y_val - z_val)
return cie_l, cie_a, cie_b
@lru_cache(maxsize=
256)
def rgb_to_lab(red, green, blue):
"""
Convert RGB color to CIE-Lab color.
:arg int red: RGB value of Red.
:arg int green: RGB value of Green.
:arg int blue: RGB value of Blue.
:returns: Tuple (L, a, b) representing CIE-Lab color
:rtype: tuple
D65/
2° standard illuminant
"""
return xyz_to_lab(*rgb_to_xyz(red, green, blue))
def dist_rgb(rgb1, rgb2):
"""
Determine distance between two rgb colors.
:arg tuple rgb1: RGB color definition
:arg tuple rgb2: RGB color definition
:returns: Square of the distance between provided colors
:rtype: float
This works by treating RGB colors
as coordinates
in three dimensional
space
and finding the closest point within the configured color range
using the formula::
d^
2 = (r2 - r1)^
2 + (g2 - g1)^
2 + (b2 - b1)^
2
For efficiency, the square of the distance
is returned
which
is sufficient
for comparisons
"""
return sum(pow(rgb1[idx] - rgb2[idx],
2)
for idx
in (
0,
1,
2))
def dist_rgb_weighted(rgb1, rgb2):
"""
Determine the weighted distance between two rgb colors.
:arg tuple rgb1: RGB color definition
:arg tuple rgb2: RGB color definition
:returns: Square of the distance between provided colors
:rtype: float
Similar to a standard distance formula, the values are weighted
to approximate human perception of color differences
For efficiency, the square of the distance
is returned
which
is sufficient
for comparisons
"""
red_mean = (rgb1[
0] + rgb2[
0]) /
2.
0
return ((
2 + red_mean /
256) * pow(rgb1[
0] - rgb2[
0],
2) +
4 * pow(rgb1[
1] - rgb2[
1],
2) +
(
2 + (
255 - red_mean) /
256) * pow(rgb1[
2] - rgb2[
2],
2))
def dist_cie76(rgb1, rgb2):
"""
Determine distance between two rgb colors using the CIE94 algorithm.
:arg tuple rgb1: RGB color definition
:arg tuple rgb2: RGB color definition
:returns: Square of the distance between provided colors
:rtype: float
For efficiency, the square of the distance
is returned
which
is sufficient
for comparisons
"""
l_1, a_1, b_1 = rgb_to_lab(*rgb1)
l_2, a_2, b_2 = rgb_to_lab(*rgb2)
return pow(l_1 - l_2,
2) + pow(a_1 - a_2,
2) + pow(b_1 - b_2,
2)
def dist_cie94(rgb1, rgb2):
# pylint: disable=too-many-locals
"""
Determine distance between two rgb colors using the CIE94 algorithm.
:arg tuple rgb1: RGB color definition
:arg tuple rgb2: RGB color definition
:returns: Square of the distance between provided colors
:rtype: float
For efficiency, the square of the distance
is returned
which
is sufficient
for comparisons
"""
l_1, a_1, b_1 = rgb_to_lab(*rgb1)
l_2, a_2, b_2 = rgb_to_lab(*rgb2)
s_l = k_l = k_c = k_h =
1
k_1 =
0.
045
k_2 =
0.
015
delta_l = l_1 - l_2
delta_a = a_1 - a_2
delta_b = b_1 - b_2
c_1 = sqrt(a_1 **
2 + b_1 **
2)
c_2 = sqrt(a_2 **
2 + b_2 **
2)
delta_c = c_1 - c_2
delta_h = sqrt(delta_a **
2 + delta_b **
2 + delta_c **
2)
s_c =
1 + k_1 * c_1
s_h =
1 + k_2 * c_1
return ((delta_l / (k_l * s_l)) **
2 +
# pylint: disable=superfluous-parens
(delta_c / (k_c * s_c)) **
2 +
(delta_h / (k_h * s_h)) **
2)
def dist_cie2000(rgb1, rgb2):
# pylint: disable=too-many-locals
"""
Determine distance between two rgb colors using the CIE2000 algorithm.
:arg tuple rgb1: RGB color definition
:arg tuple rgb2: RGB color definition
:returns: Square of the distance between provided colors
:rtype: float
For efficiency, the square of the distance
is returned
which
is sufficient
for comparisons
"""
s_l = k_l = k_c = k_h =
1
l_1, a_1, b_1 = rgb_to_lab(*rgb1)
l_2, a_2, b_2 = rgb_to_lab(*rgb2)
delta_l = l_2 - l_1
l_mean = (l_1 + l_2) /
2
c_1 = sqrt(a_1 **
2 + b_1 **
2)
c_2 = sqrt(a_2 **
2 + b_2 **
2)
c_mean = (c_1 + c_2) /
2
delta_c = c_1 - c_2
g_x = sqrt(c_mean **
7 / (c_mean **
7 +
25 **
7))
h_1 = atan2(b_1, a_1 + (a_1 /
2) * (
1 - g_x)) %
360
h_2 = atan2(b_2, a_2 + (a_2 /
2) * (
1 - g_x)) %
360
if 0 in (c_1, c_2):
delta_h_prime =
0
h_mean = h_1 + h_2
else:
delta_h_prime = h_2 - h_1
if abs(delta_h_prime) <=
180:
h_mean = (h_1 + h_2) /
2
else:
if h_2 <= h_1:
delta_h_prime +=
360
else:
delta_h_prime -=
360
h_mean = (h_1 + h_2 +
360) /
2 if h_1 + h_2 <
360 else (h_1 + h_2 -
360) /
2
delta_h =
2 * sqrt(c_1 * c_2) * sin(delta_h_prime /
2)
t_x = (
1 -
0.
17 * cos(h_mean -
30) +
0.
24 * cos(
2 * h_mean) +
0.
32 * cos(
3 * h_mean +
6) -
0.
20 * cos(
4 * h_mean -
63))
s_l =
1 + (
0.
015 * (l_mean -
50) **
2) / sqrt(
20 + (l_mean -
50) **
2)
s_c =
1 +
0.
045 * c_mean
s_h =
1 +
0.
015 * c_mean * t_x
r_t = -
2 * g_x * sin(abs(
60 * exp(-
1 * abs((delta_h -
275) /
25) **
2)))
delta_l = delta_l / (k_l * s_l)
delta_c = delta_c / (k_c * s_c)
delta_h = delta_h / (k_h * s_h)
return delta_l **
2 + delta_c **
2 + delta_h **
2 + r_t * delta_c * delta_h
COLOR_DISTANCE_ALGORITHMS = {
'rgb': dist_rgb,
'rgb-weighted': dist_rgb_weighted,
'cie76': dist_cie76,
'cie94': dist_cie94,
'cie2000': dist_cie2000}
