Can anyone tell me how can I change mask the foreground if I know the color range of background in RGB?

Question

all of you,

Here is the image;

The exact background color is in RGB; (246, 46, 100)

I have tried several methods but those are too slow, one of the methods is below;

new_image = Image.open("image-from-rawpixel-id-6649116-original.png")
img_up = np.asarray(new_image)

for ind1, i in enumerate(tqdm(img_up)):
    for ind2, i2 in enumerate(i):
        if list(i2[:3]) != a:
            img_up2 = img_up.copy()
            img_up2.setflags(write=1)
            img_up2[ind1][ind2][:3] = [0,0,0]

cv2.imshow('', img_up2)

cv2.waitKey()

I want to make the background white and the foreground person black (masked), but unable to find a quick method.

Modified

I have tied another method to mask the foreground but I think, I am doing some mistakes while converting between RGBs. Below is the code;

path = 'image-from-rawpixel-id-2923073-png.png'

im = Image.open(path).convert('RGBA')

img = cv2.imread(path, cv2.IMREAD_UNCHANGED)


#--------------------------- To change the background color that is not present in the foreground ---------------------------------------------
lst_ch_a = []
for pixel in tqdm(im.getdata()):
    lst_ch_a.append(pixel[:3])

break_out = True
while break_out:
    a = random.sample(range(0, 255), 3)
    if a not in lst_ch_a:
        new_image = Image.new("RGBA", im.size, tuple(a))
        print(tuple(a))
        break_out = False

new_image.paste(im, mask=im)
new_image.convert("RGB").save("check6.jpg")

#--------------------------- Numpy ----------------------------------------------------------------
img_up = np.asarray(new_image)

img = img_up.copy()
img.setflags(write=1)
img[:,:,:3][img[:,:,:3] != tuple(a)] = 0
img[img!=0]=255

img = cv2.cvtColor(img, cv2.COLOR_BGRA2RGBA)
img = cv2.resize(img,(500,500), cv2.INTER_LINEAR)

cv2.imwrite('results1.jpg', img)

cv2.imshow('', img)
cv2.waitKey(0)

Below is the result, but I am getting pixels of Blue, green, red, and some other colors in the image. do you know why I am getting this?

You can see in the above first image, where I have changed the background. The image was transparent image, but then I changed the background color. There was no green, blue, or red colors but while masking the foreground the red, blue, and green color emerges.

Do you know why it is happening?

Answer 1

First you could read image using cv2.imread() and you get directly numpy.array.

You can use numpy image[ mask ] = [0,0,0] to assign value to many pixels in milliseconds.

For exact color you can create mask using img == (100, 46, 247).

cv2 keeps image as BGR instead of RGB so it needs (100,46,247) instead of (247,46,100).

It needs also .all(axis=-1) because it compares every value B,G,R separatelly and gets tuples (True, True, False) but it needs to reduce it to single True when all values are True.

import cv2

img = cv2.imread("image.png")

#print('color:', img[0, 0])  # [100  46 247]

mask = (img == (100, 46, 247)).all(axis=-1)

img1 = img.copy()
img2 = img.copy()

img1[  mask ] = [0,0,0]
img2[ ~mask ] = [0,0,0]

cv2.imshow('image1', img1)
cv2.imshow('image2', img2)
cv2.waitKey()
cv2.destroyAllWindows()

cv2.imwrite('image2-1.png', img1)
cv2.imwrite('image2-2.png', img2)

Result:

image1:

image2:

---

BTW:

cv2 has function inRange() to select colors in some ranges and it may give better result.

Example code but I didn't find good range for this image.

Besides it starts removing similar pixels in lips.

import cv2
import numpy as np

img = cv2.imread("image.jpg")

hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
#print('hsv:', hsv[0, 0])

lower = np.array([92, 120, 147])
upper = np.array([172, 208, 247])  # for BGR (100, 46, 247) - value from hsv[0,0]
upper = np.array([202, 218, 247])

mask = cv2.inRange(hsv, lower, upper)

print('masking')
# `mask==255` `mask==0`
#img = cv2.bitwise_and(img, img, mask=~mask)  # OK
#img[np.where(mask==255)] = [0,0,0]           # OK 
img[ mask==255 ] = [0,0,0]                    # OK
#img[ mask.astype(bool) ] = [0,0,0]           # OK
#img[ mask ] = [0,0,0]                        # WRONG (hangs)

print('display')
#h, w = img.shape[:2]
#img = cv2.resize(img, (h//5, w//5))
cv2.imshow('image', img)
cv2.waitKey()
cv2.destroyAllWindows()

cv2.imwrite('image2b.jpg', img)

See also: Finding red color in image using Python & OpenCV - Stack Overflow

Answer 2

You should be able to do this more effectively with PIL.ImageDraw.floodfill() which is described here.

If you use a global replacement, you will catch reddish tones (such as the model's lips) anywhere and everywhere they occur in the image. If you use a floodfill from the top-left corner with a suitable tolerance, the flooding should get stopped by her dark hair before it can contaminate her lips.

The result should be like this:

---

I actually did that with ImageMagick equivalent operator in Terminal as I don't currently have Python to hand:

magick IXVJl.jpg -fuzz 30% -fill white -draw "color 0,0 floodfill" result.jpg