PIL : How to write array to image ???

[Mart.]

On Oct 5, 5:14 pm, Martin <Mar... at Hvidberg.net> wrote:
> On Oct 4, 10:16 pm, "Mart." <mdeka... at gmail.com> wrote:
>
>
>
>
>
> > On Oct 4, 9:47 am, Martin <Mar... at Hvidberg.net> wrote:
>
> > > On Oct 3, 11:56 pm, Peter Otten <__pete... at 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 use to teach ansi C at Univ. many ears
> ago, and it's still one of my favorits. But I prefere Python for this
> type of work. Python have a much faster develop time, is much easier
> to write (fewer linees, simpler syntax) and is much more 'hot' in
> these days. Finally my favorit GIS and RS applications support Python
> out-of-the-box.
>
> :-) Martin

I wasn't advocating doing it in c just that you could speed up your
program considerably by not looping and using some of the numpy array
options.