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from PIL import Image
import numpy as np
class dfs_simple_digital_chacpt(object):
def __init__(self, path):
self.white = [238, 238, 238]
self.row_num = 10
self.col_num = 40
self.walked_set = set()
self.roming_set = set()
self.dfs_num = 0
im = Image.open(path)
self.image_array = np.array(im).tolist()
def dfs(self, x, y, rgb):
'''
desc:用递归实现搜索范围内相同rgb值的像素
:param x:
:param y:
:param char:
:return:
'''
self.roming_set.add(tuple([x, y]))
if 0 > x or 0 > y or x >= self.row_num or y >= self.col_num: # 越界检查
return
if tuple([x,y]) in self.walked_set: # 重复遍历检查
return
if rgb != self.image_array[x][y]: # 目标rgb值检查
return
self.walked_set.add(tuple([x, y]))
self.dfs(x + 1, y, rgb) # x
self.dfs(x, y + 1, rgb) # y
self.dfs(x - 1, y, rgb) # -x
self.dfs(x, y - 1, rgb) # -y
self.dfs(x + 1, y + 1, rgb) # Ⅰ
self.dfs(x + 1, y - 1, rgb) # Ⅱ
self.dfs(x - 1, y - 1, rgb) # Ⅲ
self.dfs(x - 1, y + 1, rgb) # Ⅳ
return
def walk(self):
'''
desc:
:return:
'''
for y in range(self.col_num):
for x in range(self.row_num):
rgb = self.image_array[x][y]
if tuple([x, y]) in self.roming_set:
continue
if rgb != self.white:
self.dfs(x, y, rgb)
num = len(self.walked_set)
print(num)
self.walked_set.clear()
self.roming_set.clear()
if __name__ == '__main__':
path = ''
c = dfs_simple_digital_chacpt(path)
dfs_num = c.walk()
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