如何从这张图片中检测和计算圆锥角？

Question

我目前正在尝试检测锥形材料的边缘并找到该形状的角度。

我有一张这样的原图：

我写了一个检测酒红色背景和灰色材质之间边缘的Python程序（下面给出代码），它检测边缘是这样的：

但我不知道如何从检测到的边缘找到角度。有什么想法吗？

import glob
import cv2
import numpy as np
import ctypes
import math

def get_screen_resolution():
    user32 = ctypes.windll.user32
    return user32.GetSystemMetrics(0), user32.GetSystemMetrics(1)

def process_photos():
    # Get the list of image files in the directory
    image_files = glob.glob("LEF_*.jpg")

    # Process each image file
    for image_file in image_files:
        process_image(image_file)

def process_image(image_file):
    # Load the image
    image = cv2.imread(image_file)

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

    # Perform color-based segmentation to extract the burgundy regions
    lower_burgundy = np.array([0, 0, 100])  # Adjust the lower threshold for burgundy color
    upper_burgundy = np.array([100, 100, 255])  # Adjust the upper threshold for burgundy color
    mask = cv2.inRange(image, lower_burgundy, upper_burgundy)

    # Apply a Gaussian blur to the mask to reduce noise
    blurred_mask = cv2.GaussianBlur(mask, (5, 5), 0)

    # Perform Canny edge detection on the grayscale image
    edges_gray = cv2.Canny(gray, 50, 150)

    # Combine the edges with the burgundy regions using bitwise AND
    combined_edges = cv2.bitwise_and(edges_gray, blurred_mask)

    # Dilate the edges to enhance connectivity
    dilated = cv2.dilate(combined_edges, None, iterations=2)

    # Find contours of the edges
    contours, _ = cv2.findContours(dilated.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # Approximate the contours to straight lines
    lines = cv2.HoughLinesP(dilated, rho=1, theta=np.pi/180, threshold=100, minLineLength=100, maxLineGap=10)

    # Draw the lines on the original image
    if lines is not None:
        # Compute the mean line from the detected line segments
        mean_x1, mean_y1, mean_x2, mean_y2 = np.mean(lines[:, 0, :], axis=0, dtype=np.int32)

        # Draw the mean line
        cv2.line(image, (mean_x1, mean_y1), (mean_x2, mean_y2), (0, 255, 0), 2)

        # Compute the angle of the mean line
        angle = math.atan2(mean_y2 - mean_y1, mean_x2 - mean_x1) * 180 / np.pi
        print("Angle:", angle)

    # Draw the contours on the original image
    cv2.drawContours(image, contours, -1, (0, 255, 0), 2)

    # Resize the image to fit the screen resolution
    screen_width, screen_height = get_screen_resolution()
    image = cv2.resize(image, (screen_width, screen_height))

    # Display the processed image
    cv2.imshow("Processed Image", image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

process_photos()