I am using OpenCV and a kernel to count neighbors of each pixel, the pixel’s value then becomes the number of neighbors that it has, and then I apply Conway’s rules, but the output is not as expected, everything just expands. Here is my code if you want to test it yourself:
import cv2
import numpy as np
world = cv2.imread("start.png", cv2.IMREAD_GRAYSCALE)
for x in range(100):
world = np.uint8(world / 255)
kernel = np.array([
[1, 1, 1],
[1, 0, 1],
[1, 1, 1]
])
world = cv2.filter2D(src=world, ddepth=-1, kernel=kernel)
world[(world < 2) | (world > 3)] = 0
world[(world == 3) | (world == 2)] = 1
world *= 255
cv2.imwrite(f".OUTPUTstage {str(x).zfill(5)}.png", world)
print(f"Frame {x}")
4
The following statement does not correctly implement a Game of Life rule:
world[(world == 3) | (world == 2)] = 1
In case the number of live neighbors is two, you need to keep the current cell unchanged: when it was alive it should stay alive, when it was dead it should stay dead.
As your kernel ignores the current cell’s value, you will not be able to produce a correct next generation after you have applied the filter.
In order to fix the situation, you could apply a different kernel, one that has a non-zero value at the center. As you need to specifically be able to detect the state of the center cell, you could use 2 instead of 1 for the boundary, so the neighbors always add up to an even number, and use 1 at the center. That way you know when the cell was alive or not by looking at the parity after the filter has been applied.
Specifically, a cell should be alive when the application of the kernel results in 5, 6 or 7. In all other cases it should be dead.
The definition of kernel can be moved out of the loop. That leads to this code:
import cv2
import numpy as np
kernel = np.array([
[2, 2, 2],
[2, 1, 2],
[2, 2, 2]
])
world = cv2.imread("start.png", cv2.IMREAD_GRAYSCALE)
for x in range(10):
world = np.uint8(world / 255)
world = cv2.filter2D(src=world, ddepth=-1, kernel=kernel)
world[(world < 5) | (world > 7)] = 0
world[world > 0] = 255
cv2.imwrite(f"stage {str(x).zfill(5)}.png", world)
print(f"Frame {x}")
See it run on replit.com, where I limited it to just 10 generations.
It starts with an image having a glider:
…and the images created by the program are as expected.
6