Discord.py Image Editing with Python Imaging Library only works for some pictures? - python-imaging-library

Question

I've tried an image-editing-effect which should recolor a picture with little black dots, however it only works for certain images and I honestly don't know why. Any ideas?
#url = member.avatar_url
#print(url)
#response = requests.get(url=url, stream=True).raw
#imag = Image.open(response)
imag = Image.open("unknown.png")
#out = Image.new('I', imag.size)
i = 0
width, height = imag.size
for x in range(width):
i+=1
for y in range(height):
if i ==5:
# changes every 5th pixel to a certain brightness value
r,g,b,a = imag.getpixel((x,y))
print(imag.getpixel((x,y)))
brightness = int(sum([r,g,b])/3)
print(brightness)
imag.putpixel((x, y), (brightness,brightness,brightness,255))
i= 0
else:
i += 1
imag.putpixel((x,y),(255,255,255,255))
imag.save("test.png")
The comments are what I would've used if my tests had worked. Using local pngs also don't work all the time.

Answer 1

Your image that doesn't work doesn't have an alpha channel but your code assumes it does. Try forcing in an alpha channel on opening like this:
imag = Image.open("unknown.png").convert('RGBA')
See also What's the difference between a "P" and "L" mode image in PIL?
A couple of other ideas too:
looping over images with Python for loops is slow and inefficient - in general, try to find a vectorised Numpy alternative
you have an alpha channel but set it to 255 (i.e. opaque) everywhere, so in reality, you may as well not have it and save roughly 1/4 of the file size
your output image is RGB with all 3 components set identically - that is really a greyscale image, so you could create it as such and your output file will be 1/3 the size
So, here is an alternative rendition:
#!/usr/bin/env python3
from PIL import Image
import numpy as np
# Load image and ensure neither palette nor alpha
im = Image.open('paddington.png').convert('RGB')
# Make into Numpy array
na = np.array(im)
# Calculate greyscale image as mean of R, G and B channels
grey = np.mean(na, axis=-1).astype(np.uint8)
# Make white output image
out = np.full(grey.shape, 255, dtype=np.uint8)
# Copy across selected pixels
out[1::6, 1::4] = grey[1::6, 1::4]
out[3::6, 0::4] = grey[3::6, 0::4]
out[5::6, 2::4] = grey[5::6, 2::4]
# Revert to PIL Image
Image.fromarray(out).save('result.png')
That transforms this:
into this:
If you accept calculating the greyscale with the normal method, rather than averaging R, G and B, you could change to this:
im = Image.open('paddington.png').convert('L')
and remove the line that does the averaging:
grey = np.mean(na, axis=-1).astype(np.uint8)