用Python写一段代码，要求利用卡尔曼滤波器检测视频内容的变化，并选择视频中变化最大的100张关键帧进行保存。

import cv2
import numpy as np# 读取视频
video = cv2.VideoCapture("video.mp4")# 获取帧数
frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))# 设置卡尔曼滤波器
kf = cv2.KalmanFilter(4,2)
state = np.array([0,0,0,0])
kf.transitionMatrix = np.array([[1,0,1,0],[0,1,0,1],[0,0,1,0],[0,0,0,1]])
kf.measurementMatrix = 1.0 * np.eye(2, 4)
kf.processNoiseCov = 1e-5 * np.eye(4, 4)
kf.measurementNoiseCov = 1e-3 * np.eye(2, 2)# 初始化前100帧的像素均值
ret, frame = video.read()
frame_mean = np.mean(frame, axis=(0, 1))
measurements = np.array(frame_mean).reshape((1, 2))for f in range(1, frame_count):
ret, frame = video.read()
frame_mean = np.mean(frame, axis=(0, 1))
kf.correct(np.array(frame_mean).reshape((1, 2)))
state = kf.predict()
measurements = np.vstack((measurements, np.array(frame_mean).reshape((1, 2))))# 选取变化最大的100张关键帧
change = []
for i in range(1, frame_count):
change.append(np.linalg.norm(measurements[i] - measurements[i - 1]))key_frames = np.argsort(change)[-100:]# 保存关键帧
for index in key_frames:
video.set(cv2.CAP_PROP_POS_FRAMES, index)
ret, frame = video.read()
cv2.imwrite('keyframe_%d.jpg' % index, frame)