视频稳像代码，用orb实现特征点提取，暴力匹配实现特征点匹配，并剔除误匹配点，然后用仿射变换模型进行全局运动估计，得出运动参数，并用滑动平均算法进行平滑得到平均运动参数，最后用这些参数再利用仿射变换模型进行运动补偿。将视频输出并保存到本地文件

以下是基于 OpenCV 实现视频稳像的代码：

import cv2
import numpy as np

# 读取视频
cap = cv2.VideoCapture('input.mp4')

# 获取帧率、视频宽度、高度和总帧数
fps = int(cap.get(cv2.CAP_PROP_FPS))
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))

# 初始化特征点检测器和匹配器
orb = cv2.ORB_create()
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)

# 初始化滑动窗口和平均运动参数
window_size = 10
window = []
avg_motion = None

# 读取第一帧并提取特征点
ret, prev_frame = cap.read()
prev_gray = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)
prev_kp, prev_desc = orb.detectAndCompute(prev_gray, None)

while True:
    # 读取下一帧
    ret, curr_frame = cap.read()
    if not ret:
        break
    curr_gray = cv2.cvtColor(curr_frame, cv2.COLOR_BGR2GRAY)

    # 提取特征点并匹配
    curr_kp, curr_desc = orb.detectAndCompute(curr_gray, None)
    matches = bf.match(prev_desc, curr_desc)

    # 剔除误匹配点
    good_matches = []
    for match in matches:
        if match.distance < 50:
            good_matches.append(match)
    prev_pts = np.float32([prev_kp[match.queryIdx].pt for match in good_matches]).reshape(-1, 1, 2)
    curr_pts = np.float32([curr_kp[match.trainIdx].pt for match in good_matches]).reshape(-1, 1, 2)

    # 计算运动参数
    M, mask = cv2.estimateAffine2D(prev_pts, curr_pts)
    if M is None:
        # 如果无法估计出运动参数，则使用上一帧的平均运动参数
        M = avg_motion
    else:
        # 将当前帧的运动参数添加到滑动窗口中
        motion = np.linalg.inv(M)
        window.append(motion)
        if len(window) > window_size:
            window.pop(0)
        # 计算平均运动参数
        avg_motion = np.mean(window, axis=0)

    # 运动补偿
    curr_stable = cv2.warpAffine(curr_frame, avg_motion, (width, height))

    # 显示原视频和稳定后的视频
    cv2.imshow('Original Video', curr_frame)
    cv2.imshow('Stabilized Video', curr_stable)
    cv2.waitKey(int(1000 / fps))

    # 保存稳定后的视频到本地文件
    out.write(curr_stable)

    # 更新前一帧和前一帧的特征点
    prev_gray = curr_gray.copy()
    prev_kp = curr_kp
    prev_desc = curr_desc

# 释放视频和输出
cap.release()
out.release()
cv2.destroyAllWindows()