[SOLVED] Converting an Image to numpy array, then converting it immediately back to an image gives two different results

Converting an Image to numpy array, then converting it immediately back to an image gives two different results

As the title states I'm converting my image to a numpy array then converting it right back. Here's my code:

import os
import numpy as np
from PIL import Image
img = Image.open(os.path.join(no_black_border, png_files[0]))
img.show()

np_arr = np.asarray(img)
img1 = Image.fromarray(np_arr)
img1.show()

Here's my before converting it Here's my after converting it back

Solution

Your image is not RGB, it is a palette image. That means it does not have a Red, a Green and a Blue value at every pixel location, instead it has a single 8-bit palette index at each location that PIL uses to know the colour. You lose the palette when you convert to Numpy array.

You have 2 choices.

Either convert your image to RGB when you open it and all 3 values will be carried across to Numpy:

# Load image and make RGB
im = Image.open(...).convert('RGB')

# Convert to Numpy array and process
numpyarray = np.array(im)

Or, do as you currently do, but re-appply the palette from the original image after converting back to PIL Image:

# Load image
im = Image.open()

# Convert to Numpy array
numpyarray = np.array(im)

... do Numpy stuff ...

# Convert back to PIL Image and re-apply original palette
r = Image.fromarray(numpyarray,mode='P') 
r.putpalette(im.getpalette())

# Optionally save
r.save('result.png')

See answer here and accompanying comments.