Errow displaying image from array of pixels in python

Question

I have a (numpy) array of pixels acquired as:

''' import numpy and matplotlib '''
image = Image.open('trollface.png', 'r')
width, height = image.size
pixel_values = list(image.getdata())


pixel_values = np.array(pixel_values).reshape((width, height, 3)) # 3 channels RGB
#height, width = len(pixel_values), len(pixel_values[0])

I need to compute digital negative of this image -

for y in range(0,height):
   for x in range(0,width):
       R,G,B = pixel_values[x,y]
       pixel_values[x,y] =(255 - R, 255 - G, 255 - B)

tried displaying image from above pixels with the help of this thread

plt.imshow(np.array(pixel_values).reshape(width,height,3))
plt.show()

But it just displays a blank (white) window, with this error in CLI:

The error message seems pretty self explanatory. The size of your reshaped array must be the same size as the original. What are the values of width and height? — DavidG
– DavidG, Commented Jan 8, 2018 at 9:17
I am really sorry for the typo, I actually tried to map the image into same width and height, but couldn't. — Jeevan Acharya
– Jeevan Acharya, Commented Jan 8, 2018 at 9:27
You are probably going to have to provide a Minimal, Complete, and Verifiable Example. — DavidG
– DavidG, Commented Jan 8, 2018 at 9:31

Oluwafemi Sule · Accepted Answer · 2018-01-13 16:23:27Z

1

The aim here is to achieve a negative transformation of an image.

Pixel translations can be directly applied to the R, G, B band using Image.point method.

image = Image.open('trollface.png')

source = image.split()
r, g, b, a = 0, 1, 2, 3

negate = lambda i: 255 - i

transform = [source[band].point(negate) for band in (r, g, b)]
if len(source) == 4:  # should have 4 bands for images with alpha channel
    transform.append(source[a])  # add alpha channel

out = Image.merge(im.mode, transform)
out.save('negativetrollface.png')

EDIT using OP's procedure, you have:

im = Image.open('trollface.png')

w, h = im.size

arr = np.array(im)
original_shape = arr.shape


arr_to_dim = arr.reshape((w, h, 4))

# Note that this is expensive.
# Always take advantage of array manipulation implemented in the C bindings
for x in range(0, w):
    for y in range(0, h):
        r, g, b, a = arr_to_dim[x, y]
        arr_to_dim[x, y] = np.array([255 - r, 255 - g, 255 - b, a])


dim_to_arr = arr_to_dim.reshape(original_shape)

im = Image.fromarray(dim_to_arr)
out.save('negativetrollface.png')

edited Jan 13, 2018 at 16:23

answered Jan 8, 2018 at 9:51

Oluwafemi Sule

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6 Comments

Jeevan Acharya Over a year ago

Thanks for the suggestion, but I would appreciate it if you could help identify my mistake.

Oluwafemi Sule Over a year ago

You need to reshape an ndim 2 array to ndim 3. What you're looking for is .reshape((width, height, 4))

Jeevan Acharya Over a year ago

tried setting 4 instead of 3 shows new error : plt.imshow(np.array(pixel_values).reshape((width,height,4))) ValueError: total size of new array must be unchanged

Oluwafemi Sule Over a year ago

Please see edit. I was able to run this successfully.

Jeevan Acharya Over a year ago

this works [when I reshaped to w,h,3 instead of 4(no alpha)]! what do you mean implementing c bindings in this context?

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