七、OpenCV中的视频的读写

一、视频的播放

#include <opencv2/opencv.hpp>
#include <iostream>using namespace cv;
using namespace std;int main() {// 打开默认摄像头（0 表示第一个摄像头）VideoCapture cap(0);if (!cap.isOpened()) {cerr << "无法打开摄像头！" << endl;return -1;}// 获取摄像头帧率double fps = cap.get(CAP_PROP_FPS);cout << "Camera FPS: " << fps << endl;Mat frame;int imgCount = 0;while (true) {cap >> frame; // 捕获一帧if (frame.empty()) {cerr << "无法获取摄像头图像！" << endl;break;}imshow("Camera", frame);int key = waitKey(30);if (key == 27) { // ESC 退出break;} else if (key == 32) { // 空格键拍照string filename = "photo_" + to_string(imgCount++) + ".jpg";imwrite(filename, frame);cout << "已保存: " << filename << endl;}}cap.release();destroyAllWindows();return 0;
}

二、打开摄像头，并拍照

#include <opencv2/opencv.hpp>
#include <iostream>using namespace cv;
using namespace std;int main() {// 打开默认摄像头（0 表示第一个摄像头）VideoCapture cap(0);if (!cap.isOpened()) {cerr << "无法打开摄像头！" << endl;return -1;}// 获取摄像头帧率double fps = cap.get(CAP_PROP_FPS);cout << "Camera FPS: " << fps << endl;Mat frame;int imgCount = 0;while (true) {cap >> frame; // 捕获一帧if (frame.empty()) {cerr << "无法获取摄像头图像！" << endl;break;}imshow("Camera", frame);int key = waitKey(30);if (key == 27) { // ESC 退出break;} else if (key == 32) { // 空格键拍照string filename = "photo_" + to_string(imgCount++) + ".jpg";imwrite(filename, frame);cout << "已保存: " << filename << endl;}}cap.release();destroyAllWindows();return 0;
}

三、人脸检测 + 自动拍照（检测到人脸时保存照片）

#include <opencv2/opencv.hpp>
#include <iostream>using namespace cv;
using namespace std;int main() {// 加载人脸分类器（OpenCV 自带的 XML 文件）CascadeClassifier face_cascade;if (!face_cascade.load("haarcascade_frontalface_default.xml")) {cerr << "无法加载人脸检测模型！" << endl;return -1;}// 打开摄像头VideoCapture cap(0);if (!cap.isOpened()) {cerr << "无法打开摄像头！" << endl;return -1;}Mat frame, gray;while (true) {cap >> frame;if (frame.empty()) break;// 转灰度图（检测人脸时建议用灰度图）cvtColor(frame, gray, COLOR_BGR2GRAY);equalizeHist(gray, gray); // 直方图均衡化，提高检测效果// 检测人脸vector<Rect> faces;face_cascade.detectMultiScale(gray, faces,1.1,        // 缩放因子3,          // 最小邻居数0,          // 标志位Size(30, 30) // 最小检测目标);// 在原图上画矩形框for (size_t i = 0; i < faces.size(); i++) {rectangle(frame, faces[i], Scalar(0, 255, 0), 2); // 绿色框}imshow("Face Detection", frame);// 按 ESC 退出if (waitKey(30) == 27) break;}cap.release();destroyAllWindows();return 0;
}