写出满足如下要求的python代码：将给定12张的不同曝光程度的图像合成一张高动态范围图像

以下是一个基于OpenCV库的Python代码示例，用于将给定的12张不同曝光程度的图像合成一张高动态范围图像：

import cv2
import numpy as np

# 读取12张不同曝光程度的图像
img1 = cv2.imread('img1.jpg')
img2 = cv2.imread('img2.jpg')
img3 = cv2.imread('img3.jpg')
img4 = cv2.imread('img4.jpg')
img5 = cv2.imread('img5.jpg')
img6 = cv2.imread('img6.jpg')
img7 = cv2.imread('img7.jpg')
img8 = cv2.imread('img8.jpg')
img9 = cv2.imread('img9.jpg')
img10 = cv2.imread('img10.jpg')
img11 = cv2.imread('img11.jpg')
img12 = cv2.imread('img12.jpg')

# 将图像转换为32位浮点数
img1 = np.float32(img1)
img2 = np.float32(img2)
img3 = np.float32(img3)
img4 = np.float32(img4)
img5 = np.float32(img5)
img6 = np.float32(img6)
img7 = np.float32(img7)
img8 = np.float32(img8)
img9 = np.float32(img9)
img10 = np.float32(img10)
img11 = np.float32(img11)
img12 = np.float32(img12)

# 将图像缩小为1/4大小以加快计算速度
img1 = cv2.resize(img1, (0,0), fx=0.25, fy=0.25)
img2 = cv2.resize(img2, (0,0), fx=0.25, fy=0.25)
img3 = cv2.resize(img3, (0,0), fx=0.25, fy=0.25)
img4 = cv2.resize(img4, (0,0), fx=0.25, fy=0.25)
img5 = cv2.resize(img5, (0,0), fx=0.25, fy=0.25)
img6 = cv2.resize(img6, (0,0), fx=0.25, fy=0.25)
img7 = cv2.resize(img7, (0,0), fx=0.25, fy=0.25)
img8 = cv2.resize(img8, (0,0), fx=0.25, fy=0.25)
img9 = cv2.resize(img9, (0,0), fx=0.25, fy=0.25)
img10 = cv2.resize(img10, (0,0), fx=0.25, fy=0.25)
img11 = cv2.resize(img11, (0,0), fx=0.25, fy=0.25)
img12 = cv2.resize(img12, (0,0), fx=0.25, fy=0.25)

# 将图像转换为灰度图像
img1_gray = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
img3_gray = cv2.cvtColor(img3, cv2.COLOR_BGR2GRAY)
img4_gray = cv2.cvtColor(img4, cv2.COLOR_BGR2GRAY)
img5_gray = cv2.cvtColor(img5, cv2.COLOR_BGR2GRAY)
img6_gray = cv2.cvtColor(img6, cv2.COLOR_BGR2GRAY)
img7_gray = cv2.cvtColor(img7, cv2.COLOR_BGR2GRAY)
img8_gray = cv2.cvtColor(img8, cv2.COLOR_BGR2GRAY)
img9_gray = cv2.cvtColor(img9, cv2.COLOR_BGR2GRAY)
img10_gray = cv2.cvtColor(img10, cv2.COLOR_BGR2GRAY)
img11_gray = cv2.cvtColor(img11, cv2.COLOR_BGR2GRAY)
img12_gray = cv2.cvtColor(img12, cv2.COLOR_BGR2GRAY)

# 计算每个图像的权重
w1 = 0.125
w2 = 0.125
w3 = 0.125
w4 = 0.125
w5 = 0.125
w6 = 0.125
w7 = 0.125
w8 = 0.125
w9 = 0.125
w10 = 0.125
w11 = 0.125
w12 = 0.125

# 计算每个像素的权重
weights = np.array([w1, w2, w3, w4, w5, w6, w7, w8, w9, w10, w11, w12])

# 将图像合并成一张高动态范围图像
hdr_img = cv2.merge([img1_gray, img2_gray, img3_gray, img4_gray, img5_gray, img6_gray, img7_gray, img8_gray, img9_gray, img10_gray, img11_gray, img12_gray])
hdr_img = cv2.normalize(hdr_img, None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX)

# 显示合成的高动态范围图像
cv2.imshow('HDR Image', hdr_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

注意，该代码仅提供了一个示例，具体的实现可能因情况而异。此外，该代码还使用了一些硬编码的变量和常量，您可能需要根据自己的需求进行修改。