Convert RGB color to English color name, like 'green' with Python
Question:
I want to convert a color tuple to a color name, like ‘yellow’ or ‘blue’
>>> im = Image.open("test.jpg")
>>> n, color = max(im.getcolors(im.size[0]*im.size[1]))
>>> print color
(119, 172, 152)
Is there a simple way in python to do this?
Answers:
It looks like webcolors will allow you to do this:
rgb_to_name(rgb_triplet, spec=’css3′)
Convert a 3-tuple of integers, suitable for use in an rgb() color triplet, to its corresponding normalized color name, if any such name exists; valid values are html4, css2, css21 and css3, and the default is css3.
Example:
>>> rgb_to_name((0, 0, 0))
'black'
it is vice-versa-able:
>>> name_to_rgb('navy')
(0, 0, 128)
#To find the closest colour name:
However webcolors raises an exception if it can’t find a match for the requested colour. I’ve written a little fix that delivers the closest matching name for the requested RGB colour. It matches by Euclidian distance in the RGB space.
import webcolors
def closest_colour(requested_colour):
min_colours = {}
for key, name in webcolors.CSS3_HEX_TO_NAMES.items():
r_c, g_c, b_c = webcolors.hex_to_rgb(key)
rd = (r_c - requested_colour[0]) ** 2
gd = (g_c - requested_colour[1]) ** 2
bd = (b_c - requested_colour[2]) ** 2
min_colours[(rd + gd + bd)] = name
return min_colours[min(min_colours.keys())]
def get_colour_name(requested_colour):
try:
closest_name = actual_name = webcolors.rgb_to_name(requested_colour)
except ValueError:
closest_name = closest_colour(requested_colour)
actual_name = None
return actual_name, closest_name
requested_colour = (119, 172, 152)
actual_name, closest_name = get_colour_name(requested_colour)
print("Actual colour name:", actual_name, ", closest colour name:", closest_name)
Output:
Actual colour name: None , closest colour name: cadetblue
There is a program called pynche which can change RGB to colour name in English for Python.
You can try to use the method ColorDB.nearest() in ColorDB.py which can do what you want.
You can find more information about this method here : ColorDB Pynche
A solution to your problem consists in mapping the RGB values to the HSL color space.
Once you have the color in the HSL color space you can use the H (hue) component to map it the color. Note that color is a somewhat subjective concept, so you would have to define which ranges of H corresponds to a given color.
For those who, like me, want a more familiar colour name, you can use the CSS 2.1 colour names, also provided by webcolors:
- aqua:
#00ffff
- black:
#000000
- blue:
#0000ff
- fuchsia:
#ff00ff
- green:
#008000
- grey:
#808080
- lime:
#00ff00
- maroon:
#800000
- navy:
#000080
- olive:
#808000
- purple:
#800080
- red:
#ff0000
- silver:
#c0c0c0
- teal:
#008080
- white:
#ffffff
- yellow:
#ffff00
- orange:
#ffa500
Just use fraxel’s excellent answer and code for getting the closest colour, adapted to CSS 2.1:
def get_colour_name(rgb_triplet):
min_colours = {}
for key, name in webcolors.css21_hex_to_names.items():
r_c, g_c, b_c = webcolors.hex_to_rgb(key)
rd = (r_c - rgb_triplet[0]) ** 2
gd = (g_c - rgb_triplet[1]) ** 2
bd = (b_c - rgb_triplet[2]) ** 2
min_colours[(rd + gd + bd)] = name
return min_colours[min(min_colours.keys())]
The best solution I’ve found to solve this problem is the one provided by tux21b on this post:
find the colour name from a hexadecimal colour code
With the fix I’ve made (to avoid the division by zero error).
It is (from my understanding) an approximation calculation, that doesn’t require to load a large set of data table to get an approaching value, and that allow to set your own set of needed colors.
I would just use a dictionary to figure out the base colors, and then find the closest one.:
def get_color_name(rgb):
colors = {
"red": (255, 0, 0),
"green": (0, 255, 0),
"blue": (0, 0, 255),
"yellow": (255, 255, 0),
"magenta": (255, 0, 255),
"cyan": (0, 255, 255),
"black": (0, 0, 0),
"white": (255, 255, 255)
}
min_distance = float("inf")
closest_color = None
for color, value in colors.items():
distance = sum([(i - j) ** 2 for i, j in zip(rgb, value)])
if distance < min_distance:
min_distance = distance
closest_color = color
return closest_color
# Testing
print(get_color_name((255, 0, 0))) # red
print(get_color_name((0, 255, 0))) # green
print(get_color_name((0, 0, 255))) # blue
I want to convert a color tuple to a color name, like ‘yellow’ or ‘blue’
>>> im = Image.open("test.jpg")
>>> n, color = max(im.getcolors(im.size[0]*im.size[1]))
>>> print color
(119, 172, 152)
Is there a simple way in python to do this?
It looks like webcolors will allow you to do this:
rgb_to_name(rgb_triplet, spec=’css3′)
Convert a 3-tuple of integers, suitable for use in an rgb() color triplet, to its corresponding normalized color name, if any such name exists; valid values are html4, css2, css21 and css3, and the default is css3.
Example:
>>> rgb_to_name((0, 0, 0))
'black'
it is vice-versa-able:
>>> name_to_rgb('navy')
(0, 0, 128)
#To find the closest colour name:
However webcolors raises an exception if it can’t find a match for the requested colour. I’ve written a little fix that delivers the closest matching name for the requested RGB colour. It matches by Euclidian distance in the RGB space.
import webcolors
def closest_colour(requested_colour):
min_colours = {}
for key, name in webcolors.CSS3_HEX_TO_NAMES.items():
r_c, g_c, b_c = webcolors.hex_to_rgb(key)
rd = (r_c - requested_colour[0]) ** 2
gd = (g_c - requested_colour[1]) ** 2
bd = (b_c - requested_colour[2]) ** 2
min_colours[(rd + gd + bd)] = name
return min_colours[min(min_colours.keys())]
def get_colour_name(requested_colour):
try:
closest_name = actual_name = webcolors.rgb_to_name(requested_colour)
except ValueError:
closest_name = closest_colour(requested_colour)
actual_name = None
return actual_name, closest_name
requested_colour = (119, 172, 152)
actual_name, closest_name = get_colour_name(requested_colour)
print("Actual colour name:", actual_name, ", closest colour name:", closest_name)
Output:
Actual colour name: None , closest colour name: cadetblue
There is a program called pynche which can change RGB to colour name in English for Python.
You can try to use the method ColorDB.nearest() in ColorDB.py which can do what you want.
You can find more information about this method here : ColorDB Pynche
A solution to your problem consists in mapping the RGB values to the HSL color space.
Once you have the color in the HSL color space you can use the H (hue) component to map it the color. Note that color is a somewhat subjective concept, so you would have to define which ranges of H corresponds to a given color.
For those who, like me, want a more familiar colour name, you can use the CSS 2.1 colour names, also provided by webcolors:
- aqua:
#00ffff - black:
#000000 - blue:
#0000ff - fuchsia:
#ff00ff - green:
#008000 - grey:
#808080 - lime:
#00ff00 - maroon:
#800000 - navy:
#000080 - olive:
#808000 - purple:
#800080 - red:
#ff0000 - silver:
#c0c0c0 - teal:
#008080 - white:
#ffffff - yellow:
#ffff00 - orange:
#ffa500
Just use fraxel’s excellent answer and code for getting the closest colour, adapted to CSS 2.1:
def get_colour_name(rgb_triplet):
min_colours = {}
for key, name in webcolors.css21_hex_to_names.items():
r_c, g_c, b_c = webcolors.hex_to_rgb(key)
rd = (r_c - rgb_triplet[0]) ** 2
gd = (g_c - rgb_triplet[1]) ** 2
bd = (b_c - rgb_triplet[2]) ** 2
min_colours[(rd + gd + bd)] = name
return min_colours[min(min_colours.keys())]
The best solution I’ve found to solve this problem is the one provided by tux21b on this post:
find the colour name from a hexadecimal colour code
With the fix I’ve made (to avoid the division by zero error).
It is (from my understanding) an approximation calculation, that doesn’t require to load a large set of data table to get an approaching value, and that allow to set your own set of needed colors.
I would just use a dictionary to figure out the base colors, and then find the closest one.:
def get_color_name(rgb):
colors = {
"red": (255, 0, 0),
"green": (0, 255, 0),
"blue": (0, 0, 255),
"yellow": (255, 255, 0),
"magenta": (255, 0, 255),
"cyan": (0, 255, 255),
"black": (0, 0, 0),
"white": (255, 255, 255)
}
min_distance = float("inf")
closest_color = None
for color, value in colors.items():
distance = sum([(i - j) ** 2 for i, j in zip(rgb, value)])
if distance < min_distance:
min_distance = distance
closest_color = color
return closest_color
# Testing
print(get_color_name((255, 0, 0))) # red
print(get_color_name((0, 255, 0))) # green
print(get_color_name((0, 0, 255))) # blue