src/LBP.py

from skimage import feature
import numpy as np
from PIL import Image

class LBPImageEncoder:
	def __init__(self, numPoints, radius):
		# store the number of points and radius
		self.numPoints = numPoints
		self.radius = radius
        
	def describe(self, image, eps=1e-7):
		# compute the Local Binary Pattern representation
		# of the image, and then use the LBP representation
		# to build the histogram of patterns
        gray_img = imgage.convert('L')
		lbp = feature.local_binary_pattern(image, self.numPoints,
			self.radius, method="uniform")
		(hist, _) = np.histogram(lbp.ravel(),
			bins=np.arange(0, self.numPoints + 3),
			range=(0, self.numPoints + 2))
		# normalize the histogram
		hist = hist.astype("float")
		hist /= (hist.sum() + eps)
		# return the histogram of Local Binary Patterns
		return hist