If I have a numpy array like so:
[[[137 153 135]
[138 154 136]
[138 153 138]
...,
[134 159 153]
[136 159 153]
[135 158 152]]
...,
[ 57 44 34]
[ 55 47 37]
[ 55 47 37]]]
How can I apply a function to each [000 000 000] entry, modifying it?
# a = numpy array
for x in a:
for y in x:
y = modify(y)
What I'd like to achieve is modifying each (r,g,b) pixel in a PIL image that was converted to a numpy array.
A simple answer to your question is
for row in a:
for item in row:
item[:] = modify(item)
This won't be very efficient, though. An efficient solution should avoid Python loops over all pixels. (That's somehow what NumPy is all about -- vectorise your code!) A vectorised version for the case at hand would be
r, g, b = a[..., 0], a[..., 1], a[..., 2]
new_a = numpy.empty_like(a)
new_a.fill(255)
new_a[(r != a.max(axis=2)) | (r <= 125) | (g >= 70) | (b >= 110), 1:] = 0
y there is your rgb array, isn't it?
for row in a:
for px in row:
px[0] = 255 - px[0]
px[1] = 255 - px[1]
px[2] = 255 - px[2]
or more generally:
for row in a:
for px in row:
n = modify(px)
px[0] = n[0]
px[1] = n[1]
px[2] = n[2]
modify()exactly do? It is easy to give an answer to this question, but we can only give an efficient answer if we know whatmodify()does.