Getting list of pixel values from PIL

Question

I'm trying to convert a black & white .jpg image into a list which I can then modulate into an audio signal.

I have imported the PIL module and am trying to call the built-in function: list(im.getdata()). When I call it, python crashes. Is there some way of breaking down the image (always 320x240) into 240 lines to make the computations easier? Or am I just calling the wrong function?

Answer 1

Python shouldn't crash when you call getdata(). The image might be corrupted or there is something wrong with your PIL installation. Try it with another image or post the image you are using.

This should break down the image the way you want:

from PIL import Image
im = Image.open('um_000000.png')

pixels = list(im.getdata())
width, height = im.size
pixels = [pixels[i * width:(i + 1) * width] for i in xrange(height)]

Answer 2

If you have numpy installed you can try:

data = numpy.asarray(im)

(I say "try" here, because it's unclear why getdata() isn't working for you, and I don't know whether asarray uses getdata, but it's worth a test.)

Answer 3

I assume you are getting an error like.. TypeError: 'PixelAccess' object is not iterable...?

See the Image.load documentation for how to access pixels..

Basically, to get the list of pixels in an image, using PIL:

from PIL import Image
i = Image.open("myfile.png")

pixels = i.load() # this is not a list, nor is it list()'able
width, height = i.size

all_pixels = []
for x in range(width):
    for y in range(height):
        cpixel = pixels[x, y]
        all_pixels.append(cpixel)

That appends every pixel to the all_pixels - if the file is an RGB image (even if it only contains a black-and-white image) these will be a tuple, for example:

(255, 255, 255)

To convert the image to monochrome, you just average the three values - so, the last three lines of code would become..

cpixel = pixels[x, y]
bw_value = int(round(sum(cpixel) / float(len(cpixel))))
# the above could probably be bw_value = sum(cpixel)/len(cpixel)
all_pixels.append(bw_value)

Or to get the luminance (weighted average):

cpixel = pixels[x, y]
luma = (0.3 * cpixel[0]) + (0.59 * cpixel[1]) + (0.11 * cpixel[2])
all_pixels.append(luma)

Or pure 1-bit looking black and white:

cpixel = pixels[x, y]
if round(sum(cpixel)) / float(len(cpixel)) > 127:
    all_pixels.append(255)
else:
    all_pixels.append(0)

There is probably methods within PIL to do such RGB -> BW conversions quicker, but this works, and isn't particularly slow.

If you only want to perform calculations on each row, you could skip adding all the pixels to an intermediate list.. For example, to calculate the average value of each row:

from PIL import Image
i = Image.open("myfile.png")

pixels = i.load() # this is not a list
width, height = i.size
row_averages = []
for y in range(height):
    cur_row_ttl = 0
    for x in range(width):
        cur_pixel = pixels[x, y]
        cur_pixel_mono = sum(cur_pixel) / len(cur_pixel)
        cur_row_ttl += cur_pixel_mono
    
    cur_row_avg = cur_row_ttl / width
    row_averages.append(cur_row_avg)

print "Brighest row:",
print max(row_averages)

Answer 4

Or if you want to count white or black pixels

This is also a solution:

from PIL import Image
import operator

img = Image.open("your_file.png").convert('1')
black, white = img.getcolors()

print black[0]
print white[0]

Answer 5

Not PIL, but scipy.misc.imread might still be interesting:

import scipy.misc
im = scipy.misc.imread('um_000000.png', flatten=False, mode='RGB')
print(im.shape)

gives

(480, 640, 3)

so it is (height, width, channels). So you can iterate over it by

for y in range(im.shape[0]):
    for x in range(im.shape[1]):
        color = tuple(im[y][x])
        r, g, b = color

Answer 6

pixVals = list(pilImg.getdata())

output is a list of all RGB values from the picture:

[(248, 246, 247), (246, 248, 247), (244, 248, 247), (244, 248, 247), (246, 248, 247), (248, 246, 247), (250, 246, 247), (251, 245, 247), (253, 244, 247), (254, 243, 247)]

Answer 7

data = numpy.asarray(im)

Notice：In PIL, img is RGBA. In cv2, img is BGRA.

My robust solution:

def cv_from_pil_img(pil_img):
    assert pil_img.mode=="RGBA"
    return cv2.cvtColor(np.array(pil_img), cv2.COLOR_RGBA2BGRA)

Answer 8

As I commented above, problem seems to be the conversion from PIL internal list format to a standard python list type. I've found that Image.tostring() is much faster, and depending on your needs it might be enough. In my case, I needed to calculate the CRC32 digest of image data, and it suited fine.

If you need to perform more complex calculations, tom10 response involving numpy might be what you need.

Answer 9

Looks like PILlow may have changed tostring() to tobytes(). When trying to extract RGBA pixels to get them into an OpenGL texture, the following worked for me (within the glTexImage2D call which I omit for brevity).

from PIL import Image
img = Image.open("mandrill.png").rotate(180).transpose(Image.FLIP_LEFT_RIGHT)

# use img.convert("RGBA").tobytes() as texels