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#This file finds X dominant colors of a given image, using k-means and different channels of the image,
#like RGB, and luminance.
import colorsys
import math
import numpy as np
from PIL import Image
from sklearn.cluster import MiniBatchKMeans
PALETTE_WIDTH = 800
PALETTE_HEIGHT = 200
MAX_SIZE = 500,500
def make_palette(file, n_clusters):
im = Image.open(file)
im.thumbnail(MAX_SIZE)
pixels = np.array([im.getpixel((x,y)) for x in range(0, im.size[0]) for y in range(0, im.size[1])])
clt = MiniBatchKMeans(n_clusters = n_clusters, n_init = 1)
clt.fit(pixels)
return [[int(round(i)) for i in color] for color in clt.cluster_centers_]
def perceived_brightness (r, g, b):
"""
Calculates perceived brightness for the given RGB values.
code from Darel Rex Finley (http://alienryderflex.com/hsp.html)
"""
return math.sqrt((.299 * r * r) + (.587 * g * g) + (.114 * b * b))
def hsp_rank (r, g, b, mult=8):
"""
Combines hue, saturation, and perceived brightness info for a
smoother sort.
"""
lum = perceived_brightness(r, g, b)
h, s, v = colorsys.rgb_to_hsv(r, g, b)
return (h * lum * mult, s * lum * mult, s * mult)
def findDominantColors(imageFile, numberOfColors, showImage = True):
src = imageFile
n_clusters = numberOfColors
cluster_centers = make_palette(src, n_clusters)
cluster_centers.sort(key=lambda rgb: hsp_rank(*rgb))
pixels = []
dominantColors = []
for i in range(n_clusters):
color = tuple(cluster_centers[i])
dominantColors.append(color)
# print("Color #{}: {}".format(i+1, color))
for j in range(PALETTE_WIDTH//n_clusters * PALETTE_HEIGHT):
pixels.append(color)
if showImage:
img = Image.new('RGB',(PALETTE_HEIGHT,PALETTE_WIDTH))
img.putdata(pixels)
img.show()
return dominantColors
def rgb_to_hex(rgb):
return '#{:02x}{:02x}{:02x}'.format(rgb[0], rgb[1], rgb[2])
def hex_to_rgb(hex):
hex = hex.lstrip('#')
return tuple(int(hex[i:i+2], 16) for i in (0, 2, 4))
def create_color_palette(colors, palette_width=800, palette_height=200):
"""
Receives a list of colors in hex format and creates a palette image
"""
pixels = []
n_colors = len(colors)
for i in range(n_colors):
color = hex_to_rgb(colors[i])
for j in range(palette_width//n_colors * palette_height):
pixels.append(color)
img = Image.new('RGB', (palette_height, palette_width))
img.putdata(pixels)
img.show()
##############pipeline for testing
# print("Dominant colors:")
# dominantColors=findDominantColors('./estampa-test.png', 10, False)
# dominantColorHex=[rgb_to_hex(color) for color in dominantColors]
# print(dominantColorHex)
# # ['#d54b18', '#555015', '#98680e', '#1f3919', '#da8007', '#a50637', '#b50406', '#d52350', '#e2090f', '#f8545c'] |