霍夫变换不起作用

Question

我正在尝试使用霍夫变换从代码中检测图像中的圆圈：

import numpy as np
import cv2

image = cv2.imread("C:/Users/Anmol/Desktop/your_file.bmp")
output = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)


circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2,10)        

cv2.waitKey(0)

print (circles)

# ensure at least some circles were found
if circles is not None:
# convert the (x, y) coordinates and radius of the circles 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, then draw a rectangle
    # corresponding to the center of the circle
    cv2.circle(output, (x, y), r, (0, 255, 0), 4)
    cv2.rectangle(output, (x -5, y - 5), (x + 5, y + 5), (0, 128, 255), -1)

# show the output image
cv2.imshow("output", np.hstack([image, output]))
cv2.waitKey(0)

停在这条线

 circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.2,10)

我将代码运行了大约5个小时，但仍未超出此行。 它没有给出任何错误。

请指导我该怎么做。

Answer 1

如果输入图像很大，我建议将其缩小，并运行模糊滤镜。 这两个都将大大加快Hough的速度。