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 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. -- http://mail.python.org/mailman/listinfo/python-list
