gistfile1.py

import numpy as np
def integral(mask):
	"""
	calculate integral image for quick histogram
	"""
	assert(mask.dtype == bool)
	M, N = mask.shape

	integral = np.zeros((M + 1, N + 1)).astype(int)

	for i in range(1,M + 1):
		for j in range(1,N + 1):
			integral[i][j] = 	integral[i-1][j] + integral[i][j-1] - \
						integral[i-1][j-1] + mask[i - 1][j - 1]
	return integral

def padimage(integral, patch):
	"""
	pad for integral image only
	"""
	M, N = integral.shape

	out = np.zeros((M + 2*patch, N + 2*patch))
	out[patch: M + patch, patch: N + patch] = integral

	out[(M+patch):,:] = np.tile(out[M+patch-1,:], (patch, 1))
	out[:, (N+patch):] = np.tile(out[:, N+patch-1], (patch, 1)).transpose()
	return out

def histogram(textonmap, Nclusters):
	"""
	calculate the histogram of textons in the image inside a sliding window
	"""
	patch = 1
	M, N = textonmap.shape

	histogram = np.zeros((M, N, Nclusters))

	for lev in range(Nclusters):
		mask = textonmap == lev
		integral = integral(mask)

		integral = padimage(integral, patch)

		for i in range(M):
			for j in range(N):
				histogram[i][j][lev] = integral[i+2*patch+1][j+2*patch+1] + integral[i][j] - \
									integral[i][j+2*patch+1] - integral[i+2*patch+1][j]
	# histogram normalization
	sums = histogram.sum(axis = 2)
	histogram = histogram/sums[:,:,np.newaxis]

	return histogram

textonmap =  np.array([[1, 0, 0],[1, 0, 0],[1, 0, 0]])
print histogram(textonmap, 10)