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import os
import sys
sys.path.append(os.getcwd())
sys.path.append(os.path.join(os.getcwd(), 'rayleigh'))
import numpy as np
from skimage.color import rgb2lab
from .rayleigh import Palette
from .rayleigh.util import histogram_colors_strict, smooth_histogram, color_hist_to_palette_image
class CIELabDetector:
MAX_DIMENSION = 240 + 1
def __init__(self, sigma=10, num_hues=11, num_light=5, num_sat=5):
self.sigma = sigma
self.palette = Palette(num_hues=num_hues, light_range=num_light, sat_range=num_sat)
def __call__(self, img):
# Handle grayscale and RGBA images.
# TODO: Should be smarter here in the future, but for now simply remove
# the alpha channel if present.
if img.ndim == 2:
img = np.tile(img[:, :, np.newaxis], (1, 1, 3))
elif img.ndim == 4:
img = img[:, :, :3]
img = img[:,:,:3]
h, w, d = tuple(img.shape)
h_stride = int(h / self.MAX_DIMENSION + 1)
w_stride = int(w / self.MAX_DIMENSION + 1)
img = img[::h_stride, ::w_stride, :]
# Convert to L*a*b colors.
h, w, d = img.shape
lab_array = rgb2lab(img).reshape((h * w, d))
# compute hist
hist = histogram_colors_strict(lab_array, self.palette)
hist = smooth_histogram(hist, self.palette, self.sigma)
return hist
def hist_to_palette(self, hist):
# hist to image
plt = color_hist_to_palette_image(hist, self.palette)
return (plt * 255).astype(np.uint8)
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