如何在图像上找到特定点的坐标？-解网

问：

我正在尝试在图像中获取特定坐标。我在图像（图 2）的几个位置手动标记了点和矩形，以显示我想要获取的坐标（白点表示墙壁，粉红色圆点表示窗口，矩形表示列）。我正在使用 python 和 opencv 来做到这一点，但我不确定我是否走在正确的轨道上。这是我正在处理的图像示例（图 1）。图 1 图 2 这是我的第一次尝试：

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = np.float32(gray)
    cv2_imshow(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),(5,5),(-1,-1),criteria)
    for i in range(1, len(corners)):
        print(corners[i])
    img[dst>0.1*dst.max()]=[255,255,255]

首次尝试

编辑： -我想恢复除门窗区域外的墙壁中心线。这是一张图片 - 对于窗户/门，我想考虑以下几点：门/窗

python 图像 opencv 颜色坐标

import cv2
import numpy as np

# Load the image
img = cv2.imread('jCIUR.jpg')

# Convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Calculate the Harris corner response function
gray = np.float32(gray)
dst = cv2.cornerHarris(gray, 2, 3, 0.04)  # You can adjust the parameters

# Threshold the Harris response to find corner points
ret, dst = cv2.threshold(dst, 0.1 * dst.max(), 255, 0)
dst = np.uint8(dst)

# Find connected components and refine corner points
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), (5, 5), (-1, -1), criteria)

# Print and draw the corner points on the original image
for corner in corners:
    x, y = corner[0], corner[1]
    print(f"Corner at ({x},{y})")
    cv2.circle(img, (int(x), int(y)), 5, (0, 255, 0), -1)  # Draw a green circle

# Display the image with marked corners
cv2.imshow('Corners', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

如何在图像上找到特定点的坐标？

How to find coords of a specific point on an image?

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