Mart. wrote:
On Oct 5, 5:14 pm, Martin <mar...@hvidberg.net> wrote:
On Oct 4, 10:16 pm, "Mart." <mdeka...@gmail.com> wrote:





On Oct 4, 9:47 am, Martin <mar...@hvidberg.net> wrote:
On Oct 3, 11:56 pm, Peter Otten <__pete...@web.de> wrote:
Martin wrote:
Dear group
I'm trying to use PIL to write an array (a NumPy array to be exact) to
an image.
Peace of cake, but it comes out looking strange.
I use the below mini code, that I wrote for the purpose. The print of
a looks like expected:
[[ 200.  200.  200. ...,    0.    0.    0.]
 [ 200.  200.  200. ...,    0.    0.    0.]
 [ 200.  200.  200. ...,    0.    0.    0.]
 ...,
 [   0.    0.    0. ...,  200.  200.  200.]
 [   0.    0.    0. ...,  200.  200.  200.]
 [   0.    0.    0. ...,  200.  200.  200.]]
But the image looks nothing like that.
Please see the images on:
http://hvidberg.net/Martin/temp/quat_col.png
http://hvidberg.net/Martin/temp/quat_bw.png
or run the code to see them locally.
Please – what do I do wrong in the PIL part ???
:-? Martin
import numpy as np
from PIL import Image
from PIL import ImageOps
maxcol = 100
maxrow = 100
a = np.zeros((maxcol,maxrow),float)
for i in range(maxcol):
    for j in range(maxrow):
        if (i<(maxcol/2) and j<(maxrow/2)) or (i>=(maxcol/2) and j>=
(maxrow/2)):
            a[i,j] = 200
        else:
            a[i,j] = 0
print a
pilImage = Image.fromarray(a,'RGB')
pilImage.save('quat_col.png')
pilImage = ImageOps.grayscale(pilImage)
pilImage.save('quat_bw.png')
The PIL seems to copy the array contents directly from memory without any
conversions or sanity check. In your example The float values determine the
gray value of 8 consecutive pixels.
If you want a[i,j] to become the color of the pixel (i, j) you have to use
an array with a memory layout that is compatible to the Image.
Here are a few examples:
import numpy
from PIL import Image
a = numpy.zeros((100, 100), numpy.uint8)
a[:50, :50] = a[50:, 50:] = 255
Image.fromarray(a).save("tmp1.png")
b = numpy.zeros((100, 100, 3), numpy.uint8)
b[:50, :50, :] = b[50:, 50:, :] = [255, 0, 0]
Image.fromarray(b).save("tmp2.png")
c = numpy.zeros((100, 100), numpy.uint32)
c[:50, :50] = c[50:, 50:] = 0xff808000
Image.fromarray(c, "RGBA").save("tmp3.png")
Peter
Thanks All - That helped a lot...
The working code ended with:
        imga = np.zeros((imgL.shape[1],imgL.shape[0]),np.uint8)
        for ro in range(imgL.shape[1]):
            for co in range(imgL.shape[0]):
                imga[ro,co] = imgL[ro,co]
        Image.fromarray(imga).save('_a'+str(lev)+'.png')
Without knowing how big your image is (can't remember if you said!).
Perhaps rather than looping in the way you might in C for example, the
numpy where might be quicker if you have a big image. Just a
thought...
And a good thought too...

I think what Martin is telling you is:

Look to numpy to continue working on the array first.

    byte_store = imgL.astype(np.uint8)
    Image.fromarray(byte_store).save('_a%s.png' % lev)

--Scott David Daniels
scott.dani...@acm.org
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