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问矩形区域的中心线和中心点的求取
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Stack Overflow用户

提问于 2019-07-24 19:42:41

回答 2查看 4.3K关注 0票数 2

我运行了以下代码来创建一个矩形轮廓：

#import the necessary packages
import argparse
import imutils
import cv2
import numpy as np

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
                help="path to the input image")
args = vars(ap.parse_args())

# load the image, convert it to grayscale, blur it slightly, and threshold it
image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)

# threshold the image, then perform a series of erosions + dilations to remove any small regions of noise
thresh = cv2.threshold(gray, 45, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.erode(thresh, None, iterations=2)
thresh = cv2.dilate(thresh, None, iterations=2)

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

# Find the index of the largest contour
areas = [cv2.contourArea(c) for c in contours]
max_index = np.argmax(areas)
cnt=contours[max_index]

x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)

# show the output image
cv2.imshow("Image", image)
cv2.waitKey(0)

我想找到矩形轮廓的中心线和中点。请给我建议。

computer-vision

scikit-image

python

opencv

image-processing

回答 2

Stack Overflow用户

回答已采纳

发布于 2019-07-24 20:42:24

由于您已经在上面的代码中使用(x, y, w, h)获得了所需轮廓的x,y,w,h = cv2.boundingRect(cnt)，所以垂直中线的中心可以由(x+w//2, y+h//2)给出，而垂直线可以使用下面的代码绘制：

x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)
# center line
cv2.line(image, (x+w//2, y), (x+w//2, y+h), (0, 0, 255), 2)
# below circle to denote mid point of center line
center = (x+w//2, y+h//2)
radius = 2
cv2.circle(image, center, radius, (255, 255, 0), 2)

产出：

票数 7

Stack Overflow用户

发布于 2019-07-24 20:23:49

因为您已经有了边界框，所以可以使用cv2.moments()查找中心坐标。这给出了质心(即对象的中心(x，y)-coordinates )。

M = cv2.moments(cnt)
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])

中心点是(cX, cY)，您可以用cv2.circle()绘制这个

cv2.circle(image, (cX, cY), 5, (36, 255, 12), -1)

同样，我们可以使用cv2.line()或Numpy切片绘制中心线。

cv2.line(image, (x + int(w/2), y), (x + int(w/2), y+h), (0, 0, 255), 3)
image[int(cY - h/2):int(cY+h/2), cX] = (0, 0, 255)

import imutils
import cv2
import numpy as np

# load the image, convert it to grayscale, blur it slightly, and threshold it
image = cv2.imread('1.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)

# threshold the image, then perform a series of erosions + dilations to remove any small regions of noise
thresh = cv2.threshold(gray, 45, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.erode(thresh, None, iterations=2)
thresh = cv2.dilate(thresh, None, iterations=2)

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

# Find the index of the largest contour
areas = [cv2.contourArea(c) for c in contours]
max_index = np.argmax(areas)
cnt=contours[max_index]

x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)

M = cv2.moments(cnt)

cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])

cv2.circle(image, (cX, cY), 5, (36, 255, 12), -1)

# To draw line you can use cv2.line or numpy slicing
cv2.line(image, (x + int(w/2), y), (x + int(w/2), y+h), (0, 0, 255), 3)
# image[int(cY - h/2):int(cY+h/2), cX] = (36, 255, 12)

# show the output image
cv2.imshow("Image", image)
cv2.imwrite("Image.png", image)
cv2.waitKey(0)

票数 3

页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持

原文链接：

https://stackoverflow.com/questions/57190197

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