Construct a matrix in openCV based on a given matrix - c++

Question

I am writing some code using the OpenCV library in Python. In the process, I need to construct a matrix based on another matrix given. Now my code looks like the following:
for x in range(0, width):
for y in range(0, height):
if I_mat[x][y]>=0 and I_mat[x][y]<=c_low:
w_mat[x][y] = float(I_mat[x][y])/c_low
elif I_mat[x][y]>c_low and I_mat[x][y]<c_high:
w_mat[x][y] = 1
else:
w_mat[x][y] = float((255-I_mat[x][y]))/float((255-c_high))
where, I_mat is the input matrix and w_mat is the matrix I am going to construct. Since the input matrix is quite large, this algorithm is quite slow. I wonder if there are any other methods to construct w_mat more efficiently. Thank a lot!
(It is not necessary to show the solution in Python.)

Answer 1

edit:you might want to use numba
import numpy as np
import timeit
from numba import void,jit
c_low = .3
c_high = .6
def func(val):
if val>=0 and val<=c_low:
return float(val)/c_low
elif val>c_low and val<c_high:
return 1.
else:
return (255.-val)/(255.-c_high)
def npvectorize():
global w_mat
vfunc = np.vectorize(func)
w_mat = vfunc(I_mat)
def orig():
for x in range(I_mat.shape[0]):
for y in range(I_mat.shape[1]):
if I_mat[x][y]>=0 and I_mat[x][y]<=c_low:
w_mat[x][y] = float(I_mat[x][y])/c_low
elif I_mat[x][y]>c_low and I_mat[x][y]<c_high:
w_mat[x][y] = 1
else:
w_mat[x][y] = float((255-I_mat[x][y]))/float((255-c_high))
I_mat = np.array(np.random.random((1000,1000)), dtype = np.float)
w_mat = np.empty_like(I_mat)
fast = jit(void(),nopython=True)(orig)
print timeit.Timer(fast).timeit(1)
print timeit.Timer(npvectorize).timeit(1)
print timeit.Timer(orig).timeit(1)
output:
0.0352660446331
0.472590475098
4.78634474265