[python] PIL image to array (numpy array to array) - Python

I have a .jpg image that I would like to convert to Python array, because I implemented treatment routines handling plain Python arrays.

It seems that PIL images support conversion to numpy array, and according to the documentation I have written this:

from PIL import Image
im = Image.open("D:\Prototype\Bikesgray.jpg")
im.show()

print(list(np.asarray(im)))

This is returning a list of numpy arrays. Also, I tried with

list([list(x) for x in np.asarray(im)])

which is returning nothing at all since it is failing.

How can I convert from PIL to array, or simply from numpy array to Python array?

I use numpy.fromiter to invert a 8-greyscale bitmap, yet no signs of side-effects

import Image
import numpy as np

im = Image.load('foo.jpg')
im = im.convert('L')

arr = np.fromiter(iter(im.getdata()), np.uint8)
arr.resize(im.height, im.width)

arr ^= 0xFF  # invert
inverted_im = Image.fromarray(arr, mode='L')
inverted_im.show()

I highly recommend you use the tobytes function of the Image object. After some timing checks this is much more efficient.

def jpg_image_to_array(image_path):
  """
  Loads JPEG image into 3D Numpy array of shape 
  (width, height, channels)
  """
  with Image.open(image_path) as image:         
    im_arr = np.fromstring(image.tobytes(), dtype=np.uint8)
    im_arr = im_arr.reshape((image.size[1], image.size[0], 3))                                   
  return im_arr

The timings I ran on my laptop show

In [76]: %timeit np.fromstring(im.tobytes(), dtype=np.uint8)
1000 loops, best of 3: 230 µs per loop

In [77]: %timeit np.array(im.getdata(), dtype=np.uint8)
10 loops, best of 3: 114 ms per loop

```

Based on zenpoy's answer:

import Image
import numpy

def image2pixelarray(filepath):
    """
    Parameters
    ----------
    filepath : str
        Path to an image file

    Returns
    -------
    list
        A list of lists which make it simple to access the greyscale value by
        im[y][x]
    """
    im = Image.open(filepath).convert('L')
    (width, height) = im.size
    greyscale_map = list(im.getdata())
    greyscale_map = numpy.array(greyscale_map)
    greyscale_map = greyscale_map.reshape((height, width))
    return greyscale_map