帮我用Python写一个鱼眼图像双经度校正算法，要求要先取鱼眼图像进行标记来获得镜头参数以及自动获取有效区域后再进行鱼眼图像的校正

好的，鱼眼图像双经度校正算法可以基于OpenCV库来实现。下面是一个基本的实现步骤：

1. 读取鱼眼图像并显示

import cv2

# 读取鱼眼图像
img = cv2.imread('fish_eye_image.jpg')

# 显示鱼眼图像
cv2.imshow('Fish Eye Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

2. 标记鱼眼图像并获取镜头参数

import cv2
import numpy as np

# 读取鱼眼图像
img = cv2.imread('fish_eye_image.jpg')

# 初始化标记点坐标
points = []

# 鼠标事件回调函数
def mouse_callback(event, x, y, flags, param):
    # 左键单击添加标记点
    if event == cv2.EVENT_LBUTTONDOWN:
        points.append([x, y])
        # 显示标记点
        cv2.circle(img, (x, y), 3, (255, 0, 0), -1)
        cv2.imshow('Fish Eye Image', img)
        
# 显示鱼眼图像并等待标记点
cv2.imshow('Fish Eye Image', img)
cv2.setMouseCallback('Fish Eye Image', mouse_callback)
cv2.waitKey(0)
cv2.destroyAllWindows()

# 计算镜头参数
if len(points) == 4:
    # 标记点顺序为左上、右上、右下、左下
    src_pts = np.float32([points[0], points[1], points[2], points[3]])
    dst_pts = np.float32([[0, 0], [img.shape[1], 0], [img.shape[1], img.shape[0]], [0, img.shape[0]]])
    # 计算透视变换矩阵
    M = cv2.getPerspectiveTransform(src_pts, dst_pts)
    # 计算畸变矩阵和反畸变矩阵
    dist_coeffs = np.zeros((4, 1))
    K = np.eye(3)
    K[0][0] = K[1][1] = 1000
    K[0][2] = img.shape[1] / 2
    K[1][2] = img.shape[0] / 2
    undistort_map, _ = cv2.fisheye.initUndistortRectifyMap(K, dist_coeffs, np.eye(3), K, (img.shape[1], img.shape[0]), cv2.CV_16SC2)
    # 保存镜头参数
    np.savez('lens.npz', M=M, undistort_map=undistort_map)

3. 自动获取有效区域并进行鱼眼图像校正

import cv2
import numpy as np

# 读取鱼眼图像
img = cv2.imread('fish_eye_image.jpg')

# 加载镜头参数
params = np.load('lens.npz')
M, undistort_map = params['M'], params['undistort_map']

# 自动获取有效区域
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
mask = cv2.threshold(img_gray, 10, 255, cv2.THRESH_BINARY)[1]
mask = cv2.erode(mask, np.ones((5, 5), np.uint8), iterations=2)
mask = cv2.dilate(mask, np.ones((5, 5), np.uint8), iterations=4)
_, cnts, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
if len(cnts) > 0:
    cnt = max(cnts, key=cv2.contourArea)
    rect = cv2.minAreaRect(cnt)
    box = cv2.boxPoints(rect)
    box = np.int0(box)
    cv2.drawContours(img, [box], 0, (0, 255, 0), 2)

# 进行鱼眼图像校正
img_undistort = cv2.remap(img, undistort_map[0], undistort_map[1], interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)

# 显示鱼眼图像和校正后的图像
cv2.imshow('Fish Eye Image', img)
cv2.imshow('Undistorted Image', img_undistort)
cv2.waitKey(0)
cv2.destroyAllWindows()

完成了以上步骤后，你就可以在Python中实现鱼眼图像双经度校正算法了。