How to convert a PIL Image into a numpy array? How to convert a PIL Image into a numpy array? python python

How to convert a PIL Image into a numpy array?

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/", line 1185, in putdata, 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 Image.fromarray(pix).

Open I as an array:

>>> I = numpy.asarray('test.jpg'))

Do some stuff to I, then, convert it back to an image:

>>> im = PIL.Image.fromarray(numpy.uint8(I))

Source: Filter numpy images with FFT, Python

If you want to do it explicitly for some reason, there are pil2array() and array2pil() functions using getdata() on this page in

I am using Pillow 4.1.1 (the successor of PIL) in Python 3.5. The conversion between Pillow and numpy is straightforward.

from PIL import Imageimport numpy as npim ='1.jpg')im2arr = np.array(im) # im2arr.shape: height x width x channelarr2im = Image.fromarray(im2arr)

One thing that needs noticing is that Pillow-style im is column-major while numpy-style im2arr is row-major. However, the function Image.fromarray already takes this into consideration. That is, arr2im.size == im.size and arr2im.mode == im.mode in the above example.

We should take care of the HxWxC data format when processing the transformed numpy arrays, e.g. do the transform im2arr = np.rollaxis(im2arr, 2, 0) or im2arr = np.transpose(im2arr, (2, 0, 1)) into CxHxW format.