How could I implement image channel drop with the python lib of pillow

Question

I need to randomly zero out 0, 1 or 2 channel of a pillow image. That means I need to randomly set 0, 1 or 2 channels of an image to 0.

How could I do that with pil?

Answer 1

Have you tried using Numpy? It's quite simple.

import numpy as np
import PIL.Image as Image
img = np.array(Image.open("image1.jpg")) # My Image
c = np.random.randint(3, size=1)[0] # Selecting a random channel c
img[:,:,c] = img[:,:,c] * 0 # channel c times 0.

Answer 2

Here's an easy, native PIL way of doing it by multiplying by a transform. I set the default transform so the maths looks like this:

newRed   = 1*oldRed  +  0*oldGreen  +  0*oldBlue  + constant
newGreen = 0*oldRed  +  1*OldGreen  +  0*OldBlue  + constant
newBlue  = 0*oldRed  +  0*OldGreen  +  1*OldBlue  + constant

Then I just change the 1 to 0 where I want a channel zeroed out.

#!/usr/bin/env python3

from PIL import Image

# Open image
im = Image.open('input.png').convert("RGB")

# Pre-set R, G and B multipliers to 1
Rmult, Gmult, Bmult = 1, 1, 1

# Select one (or more) channels to zero out, I choose B channel here
Bmult=0

# Make transform matrix
Matrix = ( Rmult, 0, 0, 0,
           0, Gmult, 0, 0,
           0, 0, Bmult, 0)

# Apply transform and save
im = im.convert("RGB", Matrix)
im.save('result.png')

So, if you start with this:

and you set the Blue multiplier ( Bmult ) to zero, you'll get:

If you zero Red and Blue with:

Rmult = Bmult = 0 

you'll get:

Answer 3

TRY:-

from PIL import Image
import random

# Provide path to your image
img = Image.open(r"Image_Path")

# Converting the Image's mode to RGB, coz you wanted a random channel out of 3 channels
img.convert("RGB")

# Getting individual channels off the image
r, g, b = img.split()

# choice will store a random number b/w 0-2 we will use this value to extract a random channel
choice = random.randrange(0, 3)
null_channel = (r, g, b)[choice]

# printing the index of our randomly selected channel, ( 0 = Red; 1 = Green; 2 = Blue)
print(choice)

# changing each individual pixel value to 0, of our randomly selected channel
null_channel = null_channel.point(lambda p: 0)

# These conditions will provide the null channel to it's original channel's variable
if choice is 1:
    g = null_channel

elif choice is 2:
    b = null_channel

else:
    r = null_channel

# creating a new image with the original two channels' and our null'd channel
new_img = Image.merge("RGB", (r, g, b))

new_img.save("new_img.jpg")

The above code will first convert an image's color mode to RGB, so that we can deal with 3 channels. Then it will extract the individual image channels. Then it will select a random channel of the 3 channel, and convert each pixel value of that channel to (0, 0, 0). Then it will figure out which channel was originally used (R or G or B) and then overwrite the modified values to the channel. In the end, it will create a Image Object by merging all the new channels and saves it.

Sample Image:-

Image after modification:-

After analysing the modified Image, we can clearly deduce that the red channel of the image was converted into null channel.