How to combine splitted images with overlap

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I have a code that split large images into 1024X1024 small images with 10% overlap. After this process I am processing each 1024X1024 small image. Finally, I want to combine these small images I have processed in the original image size. How can I do the combine process? Can you share some sample code? Thanks...

import cv2
path_to_img = "demo.png"
img = cv2.imread(path_to_img)
img_h, img_w, _ = img.shape
split_width = 1024
split_height = 1024


def start_points(size, split_size, overlap=0):
    points = [0]
    stride = int(split_size * (1-overlap))
    counter = 1
    while True:
        pt = stride * counter
        if pt + split_size >= size:
            points.append(size - split_size)
            break
        else:
            points.append(pt)
        counter += 1
    return points


X_points = start_points(img_w, split_width, 0.1)
Y_points = start_points(img_h, split_height, 0.1)

splitted_images = []

for i in Y_points:
    for j in X_points:
        split = img[i:i+split_height, j:j+split_width]
        splitted_images.append(split)
opencv image-processing python-imaging-library python
1 Answers

To reconstruct the original image is almost the same principle. Simply use the horizontal and vertical coordinates you created and reverse the operation. You will of course need to use an external counter that will help you iterate through your list of patches. The only other intricacy you need is to declare a container that will house the final image. You can do that by declaring an array of the same type as the input image and setting it to all zeroes:

import numpy as np
final_image = np.zeros_like(img)

index = 0
for i in Y_points:
    for j in X_points:
        final_image[i:i+split_height, j:j+split_width] = splitted_images[index]
        index += 1

final_image will now contain the reconstructed image using the patches. Take note that I have simply overwritten any values that are overlapping with the most recent patch that overlaps any area of interest that would have overlapping values last.

user_32508290
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