Alright, I'm toying around with converting a PIL image object back and forth to a numpy array so I can do some faster pixel by pixel transformations than PIL's
PixelAccess object would allow. I've figured out how to place the pixel information in a useful 3D numpy array by way of:
pic = Image.open("foo.jpg") pix = numpy.array(pic.getdata()).reshape(pic.size, pic.size, 3)
But I can't seem to figure out how to load it back into the PIL object after I've done all my awesome transforms. I'm aware of the
putdata() method, but can't quite seem to get it to behave.
You're not saying how exactly
putdata() is not behaving. I'm assuming you're doing
>>> pic.putdata(a) Traceback (most recent call last): File "...blablabla.../PIL/Image.py", line 1185, in putdata self.im.putdata(data, scale, offset) SystemError: new style getargs format but argument is not a tuple
This is because
putdata expects a sequence of tuples and you're giving it a numpy array. This
>>> data = list(tuple(pixel) for pixel in pix) >>> pic.putdata(data)
will work but it is very slow.
As of PIL 1.1.6, the "proper" way to convert between images and numpy arrays is simply
>>> pix = numpy.array(pic)
although the resulting array is in a different format than yours (3-d array or rows/columns/rgb in this case).
Then, after you make your changes to the array, you should be able to do either
pic.putdata(pix) or create a new image with
I as an array:
>>> I = numpy.asarray(PIL.Image.open('test.jpg'))
Do some stuff to
I, then, convert it back to an image:
>>> im = PIL.Image.fromarray(numpy.uint8(I))
If you want to do it explicitly for some reason, there are pil2array() and array2pil() functions using getdata() on this page in correlation.zip.