针对给定的二值图像，采用8链码对图像轮廓进行描述，给出链码描述结果，并计算循环首差链码。写出能运行的代码

好的，以下是一个Python实现的8链码描述和循环首差链码计算的代码：

import cv2
import numpy as np

# 8链码
CHAIN_CODE = [0, 1, 2, 3, 4, 5, 6, 7]


def get_start_point(img):
    """
    找到图像的起始点
    """
    height, width = img.shape
    for i in range(height):
        for j in range(width):
            if img[i][j] > 0:
                return i, j


def get_chain_code(img):
    """
    计算图像的8链码
    """
    height, width = img.shape
    current_point = get_start_point(img)
    chain_code = []
    last_code = 0
    while True:
        x, y = current_point
        for code in CHAIN_CODE:
            i, j = current_point[0] + int(np.round(np.sin(np.pi * code / 4))), current_point[1] + int(
                np.round(np.cos(np.pi * code / 4)))
            if i >= 0 and i < height and j >= 0 and j < width and img[i][j] > 0:
                chain_code.append(code)
                current_point = (i, j)
                last_code = code
                break
        if current_point == get_start_point(img) and last_code == chain_code[0]:
            break
    return chain_code


def get_circular_shifted_chain_code(chain_code):
    """
    计算循环首差链码
    """
    circular_shifted_chain_code = []
    for i in range(len(chain_code)):
        circular_shifted_chain_code.append((chain_code[i] - chain_code[0]) % 8)
    return circular_shifted_chain_code


# 读取二值图像
img = cv2.imread("binary_image.png", cv2.IMREAD_GRAYSCALE)
_, img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
# 计算8链码
chain_code = get_chain_code(img)
print("8链码：", chain_code)
# 计算循环首差链码
circular_shifted_chain_code = get_circular_shifted_chain_code(chain_code)
print("循环首差链码：", circular_shifted_chain_code)

在运行代码之前，请先将名为“binary_image.png”的二值图像文件放在代码所在的目录中。运行后，程序将输出8链码和循环首差链码的结果。