最短路线
时间: 2023-10-30 13:08:10 浏览: 39
好的,现在我明确了你的需求,那么我将为你提供一个基于opencv的最短路径搜索算法的代码示例。整个算法可以分为以下几个步骤:
1. 读入迷宫图像并将其转换为二值图像。
2. 使用二值图像构建迷宫的数据结构,比如一个二维数组,其中1表示墙壁,0表示通路。
3. 使用Dijkstra或A*等最短路径搜索算法,搜索起点到终点的最短路径。
4. 在原始图像上标记最短路径。
下面是一个简单的代码示例,其中使用A*算法实现最短路径搜索:
```python
import cv2
import numpy as np
from queue import PriorityQueue
def heuristic(a, b):
# 曼哈顿距离
return np.abs(a[0]-b[0]) + np.abs(a[1]-b[1])
def astar(array, start, goal):
neighbors = [(0,1),(0,-1),(1,0),(-1,0),(1,1),(1,-1),(-1,1),(-1,-1)]
close_set = set()
came_from = {}
gscore = {start:0}
fscore = {start:heuristic(start, goal)}
oheap = []
heapq.heappush(oheap, (fscore[start], start))
while oheap:
current = heapq.heappop(oheap)[1]
if current == goal:
data = []
while current in came_from:
data.append(current)
current = came_from[current]
return data
close_set.add(current)
for i, j in neighbors:
neighbor = current[0] + i, current[1] + j
tentative_g_score = gscore[current] + heuristic(current, neighbor)
if 0 <= neighbor[0] < array.shape[0]:
if 0 <= neighbor[1] < array.shape[1]:
if array[neighbor[0]][neighbor[1]] == 1:
continue
else:
continue
else:
continue
if neighbor in close_set and tentative_g_score >= gscore.get(neighbor, 0):
continue
if tentative_g_score < gscore.get(neighbor, 0) or neighbor not in [i[1]for i in oheap]:
came_from[neighbor] = current
gscore[neighbor] = tentative_g_score
fscore[neighbor] = tentative_g_score + heuristic(neighbor, goal)
heapq.heappush(oheap, (fscore[neighbor], neighbor))
return False
img = cv2.imread('maze.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,thresh1 = cv2.threshold(gray,127,255,cv2.THRESH_BINARY_INV)
kernel = np.ones((3,3),np.uint8)
erosion = cv2.erode(thresh1,kernel,iterations = 1)
dilation = cv2.dilate(erosion,kernel,iterations = 1)
maze = dilation / 255
start = (5,5)
end = (img.shape[0]-5,img.shape[1]-5)
path = astar(maze, start, end)
for i in range(len(path)):
img[path[i][0]][path[i][1]] = [0, 0, 255]
cv2.imshow("Maze", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
以上代码示例中,我们使用A*算法搜索起点到终点的最短路径,并在迷宫图像上标记出了路径。你可以根据自己的需求对代码进行调整和优化。
相关推荐
![rar](https://img-home.csdnimg.cn/images/20210720083606.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![-](https://csdnimg.cn/download_wenku/file_type_lunwen.png)
![-](https://csdnimg.cn/download_wenku/file_type_column_c1.png)
![-](https://csdnimg.cn/download_wenku/file_type_column_c1.png)
![-](https://csdnimg.cn/download_wenku/file_type_column_c1.png)
![-](https://csdnimg.cn/download_wenku/file_type_column_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)