OpenFV HoughCircles在使用FloodFill后不起作用

Question

我正在使用HoughCircles，并且可以很好地处理灰度图像，尝试使用二进制文件仍然可以按预期工作。在我使用FloodFill仅检测图像的内圆之后，HoughCircles返回一个空数组。我的代码在这里工作：

import cv2 
import numpy as np 

# Read image. 
img = cv2.imread('terminales.webp', cv2.IMREAD_COLOR) 

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

# Blur using 3 * 3 kernel. 
gray_blurred = cv2.blur(gray, (3, 3))
ret,binary_img = cv2.threshold(gray_blurred,220,255,cv2.THRESH_BINARY_INV)

# Copy the thresholded image.
im_floodfill = binary_img.copy()

# Mask used to flood filling.
# Notice the size needs to be 2 pixels than the image.
h, w = binary_img.shape[:2]
mask = np.zeros((h+2, w+2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(im_floodfill, mask, (0,0), 255);

# Invert floodfilled image
im_floodfill_inv = cv2.bitwise_not(im_floodfill)

# Combine the two images to get the foreground.
im_out = binary_img | im_floodfill_inv


# Apply Hough transform on the blurred image. 
detected_circles = cv2.HoughCircles(binary_img,  
                   cv2.HOUGH_GRADIENT, 1, 1, param1 = 50, 
               param2 = 30, minRadius = 10, maxRadius = 150) 

# Draw circles that are detected. 
if detected_circles is not None: 

    # Convert the circle parameters a, b and r to integers. 
    detected_circles = np.uint16(np.around(detected_circles))

    for pt in detected_circles[0, :]: 
        a, b, r = pt[0], pt[1], pt[2] 

        # Draw the circumference of the circle. 
        cv2.circle(img, (a, b), r, (0, 255, 0), 2) 

        # Draw a small circle (of radius 1) to show the center. 
        cv2.circle(img, (a, b), 1, (0, 0, 255), 3)
else:
    print("Nothing detected")

cv2.imshow("Detected Circle", img)

cv2.waitKey(0)

如果我在HoughCircle中使用“ im_floodfill”，“ im_out”或“ im_floodfill_inv”而不是“ binary_img”，则不会得到任何结果。我不知道我是否缺少无法完成的事情。

Answer 1

我能够检测到一些减少参数2并增加minDist的东西。

detected_circles_inner = cv2.HoughCircles(im_floodfill,  
                   cv2.HOUGH_GRADIENT, 1, 30, param1 = 50, 
               param2 = 15, minRadius = 10, maxRadius = 150)