import cv2 # 定义阈值(相似度百分比) threshold = 90 # 加载存储在闪存中的视频码流 flash_video = cv2.VideoCapture('path/to/flash_video.mp4') # 加载接收到的视频码流 received_video = cv2.VideoCapture('path/to/received_video.mp4') # 检查视频是否成功打开 if not flash_video.isOpened() or not received_video.isOpened(): print("无法打开视频文件") exit() frame_count = min(flash_video.get(cv2.CAP_PROP_FRAME_COUNT), received_video.get(cv2.CAP_PROP_FRAME_COUNT)) match_count = 0 for i in range(int(frame_count)): # 从闪存视频和接收到的视频中读取帧 ret_flash, frame_flash = flash_video.read() ret_received, frame_received = received_video.read() if not ret_flash or not ret_received: print("视频读取错误") break # 将帧转换为灰度图像进行比较 gray_flash = cv2.cvtColor(frame_flash, cv2.COLOR_BGR2GRAY) gray_received = cv2.cvtColor(frame_received, cv2.COLOR_BGR2GRAY) # 使用均方差计算帧之间的相似度 mse = ((gray_flash - gray_received) ** 2).mean() # 计算相似度百分比 similarity = (1 - mse / 255) * 100 # 判断帧是否相似 if similarity >= threshold: match_count += 1 # 计算相似度百分比 match_percentage = match_count / frame_count * 100 # 判断是否通过 if match_percentage >= threshold: print("通过") else: print("失败") # 释放资源 flash_video.release() received_video.release() 请将这段程序用C语言实现
时间: 2024-04-09 19:34:12 浏览: 26
以下是将上述Python代码转换为C语言的示例实现:
```c
#include <stdio.h>
#include <stdlib.h>
#include <opencv2/opencv.hpp>
#define THRESHOLD 90.0
int main() {
cv::VideoCapture flashVideo("path/to/flash_video.mp4");
cv::VideoCapture receivedVideo("path/to/received_video.mp4");
if (!flashVideo.isOpened() || !receivedVideo.isOpened()) {
printf("无法打开视频文件\n");
return -1;
}
double frameCount = std::min(flashVideo.get(cv::CAP_PROP_FRAME_COUNT), receivedVideo.get(cv::CAP_PROP_FRAME_COUNT));
int matchCount = 0;
for (int i = 0; i < frameCount; i++) {
cv::Mat frameFlash, frameReceived;
bool retFlash = flashVideo.read(frameFlash);
bool retReceived = receivedVideo.read(frameReceived);
if (!retFlash || !retReceived) {
printf("视频读取错误\n");
break;
}
cv::Mat grayFlash, grayReceived;
cv::cvtColor(frameFlash, grayFlash, cv::COLOR_BGR2GRAY);
cv::cvtColor(frameReceived, grayReceived, cv::COLOR_BGR2GRAY);
cv::Mat diff;
cv::absdiff(grayFlash, grayReceived, diff);
cv::Scalar mse = cv::mean(diff.mul(diff));
double similarity = (1.0 - mse.val[0] / 255.0) * 100.0;
if (similarity >= THRESHOLD) {
matchCount++;
}
}
double matchPercentage = matchCount / frameCount * 100.0;
if (matchPercentage >= THRESHOLD) {
printf("通过\n");
} else {
printf("失败\n");
}
flashVideo.release();
receivedVideo.release();
return 0;
}
```
请确保已经安装了OpenCV库,并根据你的环境进行必要的配置和链接。此示例代码将使用OpenCV库进行视频读取、图像处理和比较,实现了与Python代码相同的功能。如果需要进一步优化和适配,你可以根据自己的需求进行修改。希望对你有所帮助!