Remove background colour from image using Python/PIL
Use np.all() compare along the third axis.
import numpy as np
from PIL import Image
im = Image.open('my_file.tif')
im = im.convert('RGBA')
data = np.array(im)
# just use the rgb values for comparison
rgb = data[:,:,:3]
color = [246, 213, 139] # Original value
black = [0,0,0, 255]
white = [255,255,255,255]
mask = np.all(rgb == color, axis = -1)
# change all pixels that match color to white
data[mask] = white
# change all pixels that don't match color to black
##data[np.logical_not(mask)] = black
new_im = Image.fromarray(data)
new_im.save('new_file.tif')
hansolo
Updated on February 20, 2020Comments
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hansolo about 4 years
I've been trying to get this to work and am really having trouble, so would be very grateful for some help.
Using the code below, I want to change the features with the specified RGB values to white, and all the other features in the image black (i.e. basically extracting the features from the image. Unfortunately, although I can make the features I want to 'extract' fine, when I try to remove the background colours (I'd been trying to use
mask2 = ((red != r1) & (green != g1) & (blue != b1)) data[:,:,:4][mask2] = [rb, gb, bb, ab]
but that seems to select any pixels except those with red == r1 OR green == g1 etc, leaving me with a background image that is quite 'noisy'.) Does anyone know a way to literally extract those pixels with the specified RGB values, or a better way to recolour the background pixels?
Thanks
import numpy as np from PIL import Image im = Image.open('/home/me/nh09sw.tif') im = im.convert('RGBA') data = np.array(im) r1, g1, b1 = 246, 213, 139 # Original value rw, gw, bw, aw = 255, 255, 255, 255 # Value that we want to replace features with rb, gb, bb, ab = 0, 0, 0, 255 #value we want to use as background colour red, green, blue, alpha = data[:,:,0], data[:,:,1], data[:,:,2], data[:,:,3] mask = ((red == r1) & (green == g1) & (blue == b1)) data[:,:,:4][mask] = [rw, gw, bw, aw] im = Image.fromarray(data) im.save('/home/me/nh09sw_recol.tif')