I have two images with the following dimensions, x, y, z:
img_a: 50, 50, 100
img_b: 50, 50
I'd like to reduce the z-dim of img_a from 100 to 1, grabbing just the value coincide with the indices stored in img_b, pixel by pixel, as indices vary throughout the image.
This should result in a third image with the dimension:
img_c: 50, 50
Is there already a function dealing with this issue?
thanks, peter
Ok updated with a vectorized method.
Here is a duplicate question but the solution currently doesn't work when the row and column dimensions are not the same size.
The code below has the method I added that explicitly creates the indices for look up purposes with numpy.indices() and then does the loop logic but in a vectorized way. It's slightly slower (2x) than the numpy.meshgrid() method but I think it's easier to understand and it also works with unequal row and column sizes.
The timing is approximate but on my system I get:
Meshgrid time: 0.319000005722
Indices time: 0.704999923706
Loops time: 13.3789999485
-
import numpy as np
import time
x_dim = 5000
y_dim = 5000
channels = 3
# base data
a = np.random.randint(1, 1000, (x_dim, y_dim, channels))
b = np.random.randint(0, channels, (x_dim, y_dim))
# meshgrid method (from here https://stackoverflow.com/a/27281566/377366 )
start_time = time.time()
i1, i0 = np.meshgrid(xrange(x_dim), xrange(y_dim), sparse=True)
c_by_meshgrid = a[i0, i1, b]
print('Meshgrid time: {}'.format(time.time() - start_time))
# indices method (this is the vectorized method that does what you want)
start_time = time.time()
b_indices = np.indices(b.shape)
c_by_indices = a[b_indices[0], b_indices[1], b[b_indices[0], b_indices[1]]]
print('Indices time: {}'.format(time.time() - start_time))
# loops method
start_time = time.time()
c_by_loops = np.zeros((x_dim, y_dim), np.intp)
for i in xrange(x_dim):
for j in xrange(y_dim):
c_by_loops[i, j] = a[i, j, b[i, j]]
print('Loops time: {}'.format(time.time() - start_time))
# confirm correctness
print('Meshgrid method matches loops: {}'.format(np.all(c_by_meshgrid == c_by_loops)))
print('Loop method matches loops: {}'.format(np.all(c_by_indices == c_by_loops)))