CODEWITHSUNDEEP
pythonimagenumpypython-imaging-library
mydude1234
mydude1234

Reputation: 55

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

Upvotes: 2

Views: 1696

Answers (1)

Mark Setchell
Mark Setchell

Reputation: 207445

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.

Upvotes: 3

Related Questions