How set white color background when concatenating images via python?

Question

import numpy as np
from imageio import imread, imwrite

im1 = imread('https://api.sofascore.app/api/v1/team/2697/image')[...,:3]
im2 = imread('https://api.sofascore.app/api/v1/team/2692/image')[...,:3]

result = np.hstack((im1,im2))

imwrite('result.jpg', result)

Original images opening directly from the url's (I'm trying to concatenate the two images into one and keep the background white):

As can be seen both have no background, but when joining the two via Python, the defined background becomes this moss green:

I tried modifying the color reception:

im1 = imread('https://api.sofascore.app/api/v1/team/2697/image')[...,:1]
im2 = imread('https://api.sofascore.app/api/v1/team/2692/image')[...,:1]

But the result is a Black & White with the background still looking like it was converted from the previous green, even though the PNG's don't have such a background color.

How should I proceed to solve my need?

score 1 · Answer 1 · 2022-02-05T20:43:51.643

1

If you want to change the background of a Image, pixellib is the best solution because it seemed the most reasonable and easy library to use.

import pixellib
from pixellib.tune_bg import alter_bg

change_bg = alter_bg()
change_bg.load_pascalvoc_model("deeplabv3_xception_tf_dim_ordering_tf_kernels.h5")
change_bg.color_bg("sample.png", colors=(255,255,255), output_image_name="colored_bg.png")

This code requires pixellib to be higher or the same as 0.6.1

edited Feb 05 '22 at 20:43

answered Feb 05 '22 at 20:23

Hi mate, Taking advantage of your help, do you by any chance know a way to concatenate images so that their quality is better than the one I'm using? I noticed that the original png's that I pasted in the question are of a much higher quality than the concatenated I created. – Digital Farmer Feb 05 '22 at 20:28
In my attempts this error is occurring, even though I have successfully installed pixellib, could you tell me what might be happening? ```ModuleNotFoundError: No module named 'tensorflow'``` – Digital Farmer Feb 05 '22 at 20:33
1

Its probably because you don't have installed tensorflow. Pixellib needs tensorflow to work @Brondby – Feb 05 '22 at 20:37
Ahhh ok mate, my fault, thanks! – Digital Farmer Feb 05 '22 at 20:42

CJR · Accepted Answer · 2022-02-05T20:44:00.560

There is a 4th channel in your images - transparency. You are discarding that channel with [...,:1]. This is a mistake.

If you retain the alpha channel this will work fine:

import numpy as np
from imageio import imread, imwrite

im1 = imread('https://api.sofascore.app/api/v1/team/2697/image')
im2 = imread('https://api.sofascore.app/api/v1/team/2692/image')

result = np.hstack((im1,im2))

imwrite('result.png', result)

However, if you try to make a jpg, you will have a problem:

>>> imwrite('test.jpg', result)

OSError: JPEG does not support alpha channel.

This is correct, as JPGs do not do transparency. If you would like to use transparency and also have your output be a JPG, I suggest a priest.

You can replace the transparent pixels by using np.where and looking for places that the alpha channel is 0:

result = np.hstack((im1,im2))
result[np.where(result[...,3] == 0)] = [255, 255, 255, 255]

imwrite('result.png', result)

Hi @CJR I didn't know that this conversion generated such a problem, now the quality of the images has increased a lot and we have the transparent background, now it will make it easier for me to find out how to put the white background, thank you very much. And if you can help me to add the white background, I would greatly appreciate it! — Digital Farmer, Feb 05 '22 at 20:36
`result[np.where(result[...,3] == 0)] = [255, 255, 255, 255]` this will replace all the pixels where the alpha channel is 0 (the transparent background) with white pixels. — CJR, Feb 05 '22 at 20:42

score 1 · Answer 3 · answered Feb 05 '22 at 20:39

If you want to improve image quality, here is a solution. @Brondy

# External libraries used for
# Image IO
from PIL import Image

# Morphological filtering
from skimage.morphology import opening
from skimage.morphology import disk

# Data handling
import numpy as np

# Connected component filtering
import cv2

black = 0
white = 255
threshold = 160

# Open input image in grayscale mode and get its pixels.
img = Image.open("image.jpg").convert("LA")
pixels = np.array(img)[:,:,0]

# Remove pixels above threshold
pixels[pixels > threshold] = white
pixels[pixels < threshold] = black


# Morphological opening
blobSize = 1 # Select the maximum radius of the blobs you would like to remove
structureElement = disk(blobSize)  # you can define different shapes, here we take a disk shape
# We need to invert the image such that black is background and white foreground to perform the opening
pixels = np.invert(opening(np.invert(pixels), structureElement))


# Create and save new image.
newImg = Image.fromarray(pixels).convert('RGB')
newImg.save("newImage1.PNG")

# Find the connected components (black objects in your image)
# Because the function searches for white connected components on a black background, we need to invert the image
nb_components, output, stats, centroids = cv2.connectedComponentsWithStats(np.invert(pixels), connectivity=8)

# For every connected component in your image, you can obtain the number of pixels from the stats variable in the last
# column. We remove the first entry from sizes, because this is the entry of the background connected component
sizes = stats[1:,-1]
nb_components -= 1

# Define the minimum size (number of pixels) a component should consist of
minimum_size = 100

# Create a new image
newPixels = np.ones(pixels.shape)*255

# Iterate over all components in the image, only keep the components larger than minimum size
for i in range(1, nb_components):
    if sizes[i] > minimum_size:
        newPixels[output == i+1] = 0

# Create and save new image.
newImg = Image.fromarray(newPixels).convert('RGB')
newImg.save("new_img.PNG")

How set white color background when concatenating images via python?

3 Answers3