On Wed, Feb 2, 2011 at 8:22 AM, Asmi Shah <[email protected]> wrote: > Hi all, > It seems that using 64 bit python is the solution. But the thing is i would > compile my code and wanna distribute it to the clients.. and that is the > only reason why i want to work on 32 bit system. Sturla, how I can make it > sure that some part of the data is kept on the disk and only the necessary > one in the memory; as this seems to be a solution to my problem. As i said i > want a 3d visualization out of the numpy array. it works fine for the > downsampled dataset. And to visualize, i have to convert the 16bit data into > 8bit as PIL doesnt support 16 bit data.. the only thing i do to create my > array is this: > stack = numpy.empty((120, 1024, 1024)) > i = 0 > os.chdir(dirr) > for f in os.listdir(dirr): > im = Image.open(f) > im = im.convert("L") > a = numpy.asarray(im) > print a.dtype > stack[i] = a > i += 1 > one more thing, it really doesnt work for tiff files at all, i have to > convert them into jpgs as a prior step to this. and it at max lets me create > an array for around 60 slices only, where as my requirement would be around > 100 to 200 images.. > any ideas? can diagnose the problem?? > thanks a lot.. asmi
Give a try to pylibtiff [1], the cool thing is it give support to get metainformations from tiff files. There is support to read tiff files in VTK [2]. [1] - http://code.google.com/p/pylibtiff/ [2] - http://www.vtk.org/doc/nightly/html/classvtkTIFFReader.html _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
