localbinarypatterns.py

# import the necessary packages
from skimage import feature
import numpy as np

class LocalBinaryPatterns:
    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
        
        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