用opencv提取迷宫中点的坐标

提取迷宫中点的坐标可以通过以下步骤实现：

1. 读取迷宫图像并将其转换为灰度图像。

import cv2

img = cv2.imread("maze.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

2. 对灰度图像进行二值化处理，将迷宫的墙壁和路径分离出来。

thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

3. 对二值化图像进行边缘检测，提取迷宫路径的轮廓。

contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

4. 对路径轮廓进行筛选，去除长度较小的轮廓。

contours_filtered = []
for contour in contours:
    if len(contour) > 50:
        contours_filtered.append(contour)

5. 对筛选后的轮廓进行近似处理，得到轮廓的多边形拟合。

polygons = []
for contour in contours_filtered:
    epsilon = 0.03 * cv2.arcLength(contour, True)
    polygon = cv2.approxPolyDP(contour, epsilon, True)
    polygons.append(polygon)

6. 对多边形拟合进行筛选，得到迷宫路径上的关键点。

keypoints = []
for polygon in polygons:
    for point in polygon:
        keypoints.append((point[0][0], point[0][1]))

7. 将关键点按照 x 坐标排序，然后按照 y 坐标排序，得到迷宫路径上的中心点坐标。

keypoints_sorted_x = sorted(keypoints, key=lambda x: x[0])
keypoints_sorted_y = sorted(keypoints_sorted_x, key=lambda x: x[1])
centers = []
for i in range(1, len(keypoints_sorted_y)):
    center = ((keypoints_sorted_y[i][0] + keypoints_sorted_y[i-1][0]) // 2, (keypoints_sorted_y[i][1] + keypoints_sorted_y[i-1][1]) // 2)
    centers.append(center)

完整代码如下：

import cv2

img = cv2.imread("maze.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

contours_filtered = []
for contour in contours:
    if len(contour) > 50:
        contours_filtered.append(contour)

polygons = []
for contour in contours_filtered:
    epsilon = 0.03 * cv2.arcLength(contour, True)
    polygon = cv2.approxPolyDP(contour, epsilon, True)
    polygons.append(polygon)

keypoints = []
for polygon in polygons:
    for point in polygon:
        keypoints.append((point[0][0], point[0][1]))

keypoints_sorted_x = sorted(keypoints, key=lambda x: x[0])
keypoints_sorted_y = sorted(keypoints_sorted_x, key=lambda x: x[1])
centers = []
for i in range(1, len(keypoints_sorted_y)):
    center = ((keypoints_sorted_y[i][0] + keypoints_sorted_y[i-1][0]) // 2, (keypoints_sorted_y[i][1] + keypoints_sorted_y[i-1][1]) // 2)
    centers.append(center)

for center in centers:
    cv2.circle(img, center, 5, (0, 255, 0), -1)

cv2.imshow("result", img)
cv2.waitKey(0)
cv2.destroyAllWindows()