从凸图像蒙版的边界中提取平均颜色

import cv2
import numpy as np

def extract_average_color_from_boundary(image_path):
    # 读取图像
    img = cv2.imread(image_path)
    if img is None:
        raise ValueError("Image not found or unable to read")

    # 假设我们已经有了一个凸蒙版 mask
    # mask = ... (此处应填入获取凸蒙版的代码)

    # 使用Canny边缘检测找到边界
    edges = cv2.Canny(mask, 100, 200)

    # 创建一个空白的图像用于存储边界颜色
    boundary_colors = np.zeros((edges.shape[0], edges.shape[1], 3), dtype=np.float32)

    # 遍历边缘像素，并收集它们的颜色
    for y in range(edges.shape[0]):
        for x in range(edges.shape[1]):
            if edges[y, x] > 0:  # 如果是边界像素
                boundary_colors[y, x] = img[y, x]

    # 计算平均颜色
    average_color = np.mean(boundary_colors, axis=(0, 1))
    return tuple(map(int, average_color))  # 转换为整数元组以便显示和使用

# 使用示例
image_path = 'path_to_your_image.jpg'
average_color = extract_average_color_from_boundary(image_path)
print(f"Average color of the boundary: {average_color}")