2011/1/28 Christopher Barker <chris.bar...@noaa.gov>: > On 1/28/11 7:01 AM, Asmi Shah wrote: >> I am using python for a while now and I have a requirement of creating a >> numpy array of microscopic tiff images ( this data is 3d, meaning there are >> 100 z slices of 512 X 512 pixels.) How can I create an array of images? > > It's quite straightforward to create a 3-d array to hold this kind of data: > > image_block = np.empty((100, 512, 512), dtype=??) > > now you can load it up by using some lib (PIL, or ???) to load the tif > images, and then: > > for i in images: > image_block[i,:,:] = i
Notice that since PIL 1.1.6, PIL Image objects support the numpy interface: http://effbot.org/zone/pil-changes-116.htm >>> import PIL.Image >>> im = PIL.Image.open('P1010102.JPG') >>> im <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=3264x2448 at 0x4CA0A8> >>> a = numpy.asarray(im) >>> a.shape (2448, 3264, 3) >>> a.dtype dtype('uint8') You can use the image just as any other ndarray: >>> stack = numpy.empty((5, 2488, 3264, 3)) >>> stack[0] = im and so on for 5 images in a stack, notice that the dtype of the initially empty ndarray is float! It works also vice-versa: >>> im_copy = PIL.Image.fromarray(a) but this seems to require integer-valued ndarrays as input, except when the ndarray is monochrome. This might be even simpler than the dtype proposed by Christopher. For more info on PIL: http://www.pythonware.com/library/pil/handbook/ Friedrich _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
