在尝试将Hough Circles合并到我要编写的跟踪程序的主要代码中之前,我试图弄清楚Hough Circles,但是除了None之外,我似乎一无所获。我使用孟加拉国旗作为图像,因为它很简单并且很容易检测。这是我的代码:

import numpy as np
import cv2


img = cv2.imread('Capture.PNG')

grayput = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

circles = cv2.HoughCircles(grayput, cv2.cv.CV_HOUGH_GRADIENT, 1, 20, param1 =50, param2 =10, minRadius=10, maxRadius=40)
print (circles)

    # need circles
if circles is not None:
    # convert the coord. to integers
    circles = np.round(circles[0, :]).astype("int")

    # loop over the (x, y) coordinates and radius of the circles
    for (x, y, r) in circles:
        # draw the circle in the output image
        cv2.circle(img, (x, y), r, (0, 0, 0), 4)


cv2.imwrite("image.PNG",img)

最佳答案

以下代码将为您提供“无”圈子:

import numpy as np
import cv2

img = cv2.imread("../images/opencv_logo.png", 0)
img = cv2.medianBlur(img,5)
cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
cv2.imshow("grayscale", cimg)
cv2.waitKey(0)

circles = cv2.HoughCircles(img,cv2.HOUGH_GRADIENT,1,20,
                                    param1=50,param2=30,minRadius=0,maxRadius=0)
print (circles)

实际上,输出为:
[[[  45.5         133.5          16.50757408]
  [  97.5          45.5          16.80773544]
  [ 147.5         133.5          16.32482719]]]

注意:此代码段使用以下内容作为其输入图像:

关于python - Python OpenCV Hough Circles返回无,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/31140386/

10-12 22:44