"Mozart, Beethoven, and Chopin never died. They simply became music."
康威生命游戏规则十分简单，简化后如下：
一个“细胞”（或者说单元）分为生或死两种状态，
如果活相邻细胞有2或3个活细胞 该细胞活，否则死
如果死细胞周围有3个活细胞，该细胞转为活。
再OpenCV中，将二值化图像数值变为0和1之后，使用该内核进行卷积核操作（个位储存相邻活细胞个数，十位储存中间细胞生或死状态）
threshed_value = (convolved/255).astype(np.uint8)
kernel = np.asarray([[1,1,1],[1,10,1],[1,1,1]],dtype='uint8')
需要注意的是进行卷积操作的时候需要设置边界类型，这里将图像边界作为0处理
接下来对图片进行几次掩膜操作，完成一个循环
convolved = cv.filter2D(src=threshed_value, ddepth=cv.CV_8U, kernel=kernel,borderType=cv.BORDER_CONSTANT)#populated:convolved[convolved==10] = 0 #单独死亡convolved[convolved==11] = 0 convolved[convolved>=14] = 0#unpopulated:convolved[convolved==3] = 255 #复活细胞#binarize againconvolved[convolved>10] = 255 #转化为常值convolved[convolved<10] = 0#重新将图像数据转化成0和1ret,threshed_value = cv.threshold(convolved,10,1,cv.THRESH_BINARY) 整个代码见下
import cv2 as cv
import numpy as npimage = cv.imread('John_H_Conway_2005_(cropped).jpg',0)
convolved = cv.adaptiveThreshold(image,255,cv.ADAPTIVE_THRESH_GAUSSIAN_C,\cv.THRESH_BINARY,11,5)threshed_value = (convolved/255).astype(np.uint8)kernel = np.asarray([[1,1,1],[1,10,1],[1,1,1]],dtype='uint8')for name in ['convolved']:cv.namedWindow(name,cv.WINDOW_NORMAL)cv.imshow(name,eval(name))key = cv.waitKey(0)mode = Truewhile True:cv.imshow('convolved',convolved)key = cv.waitKey(10)if key == 27:breakconvolved = cv.filter2D(src=threshed_value, ddepth=cv.CV_8U, kernel=kernel,borderType=cv.BORDER_CONSTANT)#populated:convolved[convolved==10] = 0 #solitudeconvolved[convolved==11] = 0 convolved[convolved>=14] = 0#unpopulated:convolved[convolved==3] = 255 #revived#binarize againconvolved[convolved>10] = 255convolved[convolved<10] = 0ret,threshed_value = cv.threshold(convolved,10,1,cv.THRESH_BINARY)
