使用 OpenCV 从图像中查找房间的坐标

Question

我正在尝试获取地图/导航应用程序的每个房间的坐标。 下面的代码找到了每个角落，再往下的代码找到了房间的中心。 我不知道如何将两者结合起来，以便分别获得每个房间的角坐标数组。

平面图图片：

#finds every corner
img = cv2.imread('out.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = np.float32(gray)
dst = cv2.cornerHarris(gray,5,3,0.04)
ret, dst = cv2.threshold(dst,0.1*dst.max(),255,0)
dst = np.uint8(dst)
ret, labels, stats, centroids = cv2.connectedComponentsWithStats(dst)
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.001)
corners = cv2.cornerSubPix(gray,np.float32(centroids),(50,50),(-1,-1),criteria)

img[dst>0.1*dst.max()]=[0,0,255]

#find centre of each room 
IMAGE_NAME = 'out.png'
#Remove Small Items
im_gray = cv2.imread(IMAGE_NAME, cv2.IMREAD_GRAYSCALE)
(thresh, im_bw) = cv2.threshold(im_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
thresh = 127
im_bw = cv2.threshold(im_gray, thresh, 255, cv2.THRESH_BINARY)[1]
#find all your connected components 
nb_components, output, stats, centroids = cv2.connectedComponentsWithStats(im_bw, connectivity=8)
#connectedComponentswithStats yields every seperated component with information on each of them, such as size
#the following part is just taking out the background which is also considered a component, but most of the time we don't want that.
sizes = stats[1:, -1]; nb_components = nb_components - 1

Answer 1

这是一个基于findContours使用opencv_contrib_python-4.5.5的示例：

import cv2 as cv

img = cv.imread("UYret.png")
img_gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
ret, thresh = cv.threshold(img_gray, 127, 255, 0)
contours, hierarchy = cv.findContours(thresh, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)

print(contours)
cv.drawContours(img, contours, -1, (0, 255, 0), 3)
cv.imwrite("out.png", img)

所选的近似方法会将轮廓点减少到房间角落。 所以contours返回一个数组列表，每个数组都包含其中一个房间角落的坐标：

(
...
array([[[9271, 7560]],
       [[9271, 7795]],
       [[9782, 7795]],
       [[9782, 7560]]], dtype=int32),
...
)

在out.png ，您可以看到已找到的房间以绿色显示。 外面的“房间”的形状也被检测出来。 您可以使用在hierarchy结构中返回的结构（可能您只对叶子感兴趣）或假设真实房间的大小有限，可以轻松过滤掉这些周围的房间。