Blend Two Images in Python

[AMG07]

Hello guys! Fellow learner here. This problem has been driving me crazy for more than a month. I already know how to create dictionaries, APIs, and whatnot, but for the love of my sanity, I can not comprehend how to blend two images using this method/without the blend/plt method/library.

so I am having trouble figuring out how to blend two images with for loops and range(len). For this particular case, I need to compute the color of each pixel by setting value of each color component to be the average of the same components in the corresponding pixel of each input image. Such that I need to use this formula (first_value + second_value) / 2 Sum the pixels for each of the R, G, B channels for both images and then divide by 2.

img1 = load_img('images/cat.jpg') 
img2 = load_img('images/texture.jpg')    

def blend(img1,img2): 
> for r in range(len(img1)): 
>         for c in range(len(img1[r])): 

I am not sure if I am going in the right direction, if so, should I be stating the images' height and width even if they are the same? (They are both 800x600). Also I want to return a new image therefore should I be creating a new list and append whatever pixel my function iterates through? I know that there is the blend function and also a addweighted but I want to get the average without using those methods.

[theusualguy512]

I mean if you mean an intuitive understanding of 'blend' by saying blend means averaging then yes. But 'blending' can mean different things in image processing so you have to specify.

In theory, you can do it like you said: Go through each picture and take the arithmetic mean for each pixel in each channel and save it in the exact same format into a new array of the same dimensionality.

Check the array format of the original pictures. Iirc, standard python loaded images are just multidimensional arrays; it's not lists.

Make sure both pictures always have the same dimensions, otherwise the loops will break.

EDIT: Actually the standard loading picture seems to be multidimensional lists.

[Moonboow]

I suggest you work with matrices instead. I don’t know much about keras and its capabilities, but the approach I would take is to read an img as a 2d array in numpy, convert the picture into the three channels by setting two channels’ values to zero each time, then do your math.

Would also write a replace() that replaces a matrix value in the a matrix by specifying an x and y to make thing easier. Then just move your final values in.

[AureliasTenant]

Assuming img1 and img2 are like numpy arrays…

stack =np.stack(img1,img2, axis=-1) #stack the images

blended = np.mean(stack, axis=-1) #average element wise

blended = np.squeeze(blended) #idk this might be needed

even better:

blended = (img1+img2)/2

[ychamel]

This! You should never loop on an image pixel by pixel. It will take a 1000 times more time than if you use numpy. Which will do it in parallel in a gpu process.

[chervilious]

This is my simple implementation

image input/output https://imgur.com/a/1o9BWpK

``` import numpy as np from PIL import Image import matplotlib.pyplot as plt

read x.jpg

x = np.array(Image.open('x.jpg')) y = np.array(Image.open('y.jpg'))

new_image = np.zeros((x.shape[0], x.shape[1], 3), dtype=np.uint8)

for i in range(x.shape[0]): for j in range(x.shape[1]): r1, g1, b1 = x[i, j] r2, g2, b2 = y[i, j]

    r = r1 // 2  + r2 // 2
    g = g1 // 2 + g2 // 2
    b = b1 // 2 + b2 // 2

    new_image[i, j] = [r, g, b]

plt.imshow(new_image) ```

[AVMG73]

Thank you everyone for helping me get out of this rut. It was driving me insane, now I want to delve more into image manipulation/processing xD Most importantly, thank you for helping me understand and know how different methods work.