2011/8/31 Claudio <claudyu...@gmail.com>: > 2011/8/31 Guilherme Polo <ggp...@gmail.com>: >> 2011/8/31 Claudio <claudyu...@gmail.com>: >>> Hi all, >>> I'm tring to implement a sobel filter using PIL library with few success. >>> >>> Now I never used this library before so any help is appreciate. >>> I wrote the following code that essential is a standard implementation >>> of the sobel filter: >>> >>> input img, output dimg: >>> dx = [-1, 0, 1, -2, 0, 2, -1, 0, 1] >>> dy = [-1, -2, -1, 0, 0, 0, 1, 2, 1] >>> >>> ximg = img.filter(ImageFilter.Kernel((3,3), dx, None, 0)) #apply the >>> kernel in x e y >>> yimg = img.filter(ImageFilter.Kernel((3,3), dy, None, 0)) >>> >>> dimg = img.copy() >>> dest = dimg.load() >>> xdata = ximg.load() #retrieve the x e y data >>> ydata = yimg.load() >>> >>> for y in range ( img.size[1]): # calcolo il gradiente per >>> ogni punto >>> for x in range( img.size[0]): >>> # dest[x, y] = sqrt( xdata[x, y] * xdata[x, y] + ydata[x, y] * >>> ydata[x, y]) >>> dest[x, y] = abs( xdata[x, y] ) + abs (ydata[x, y]) >>> >>> The result is not what I expected, so I misunderstood some function usage? >> >> "not what I expected" is too vague. Maybe you have a 8 bits image and > > Ok that's true, I was too vague. > So using the same photo of the stream engine that is on wikipedia [1] > I obtain this image: > https://www.mignanti.eu/articoli/tmp > >> the convolution only uses 8 bits to store the results and then you get >> weird results ? > > Well, I'm working on grayscale image but the results should be in the > same domain. >
Do you want something like http://i.imgur.com/Ij6s6.png (res1) or http://imgur.com/kTBLK (res2) ? # orig is your RGB image, I don't know how you wish to handle the bands img = ImageOps.grayscale(orig) dxn = scipy.signal.convolve2d(numpy.array(img), [[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]) dyn = scipy.signal.convolve2d(numpy.array(img), [[-1, -2, -1], [0, 0, 0], [1, 2, 1]]) resn = dxn + dyn a = 255. / (resn.max() - resn.min()) b = -a * resn.min() # cap is a function that returns 0 if a point is below 0 and # returns 255 if a point is above 255 res1 = Image.fromarray(numpy.uint8((resn * a + b).round())) res2 = Image.fromarray(numpy.uint8((cap(resn)).round())) Now I see that I'm very naive with PIL, I don't know how to achieve exactly the same result using only PIL. -- -- Guilherme H. Polo Goncalves _______________________________________________ Image-SIG maillist - Image-SIG@python.org http://mail.python.org/mailman/listinfo/image-sig
