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#include <opencv2/opencv.hpp> #include <iostream> int main() { // Load the pre-trained Haar Cascade for face detection cv::CascadeClassifier faceCascade; if (!faceCascade.load("haarcascade_frontalface_default.xml")) { std::cerr << "Error loading Haar Cascade file!" << std::endl; return -1; } // Open a video capture from the default camera cv::VideoCapture cap(0); if (!cap.isOpened()) { std::cerr << "Error opening video capture!" << std::endl; return -1; } cv::Mat frame; std::vector<cv::Rect> faces; while (true) { // Capture a new frame from the video feed cap >> frame; if (frame.empty()) { std::cerr << "Error capturing frame!" << std::endl; break; } // Convert the frame to grayscale cv::Mat gray; cv::cvtColor(frame, gray, cv::COLOR_BGR2GRAY); // Detect faces in the frame faceCascade.detectMultiScale(gray, faces, 1.1, 3, 0, cv::Size(30, 30)); // Draw rectangles around detected faces for (const auto& face : faces) { cv::rectangle(frame, face, cv::Scalar(255, 0, 0), 2); } // Display the frame with detected faces cv::imshow("Object Detection", frame); // Exit loop when 'q' is pressed if (cv::waitKey(30) >= 0) { break; } } // Release video capture and close windows cap.release(); cv::destroyAllWindows(); return 0; } |
Explanation:
- Include OpenCV Header:
#include <opencv2/opencv.hpp>: Includes the OpenCV core functionalities.
- Load Haar Cascade:
cv::CascadeClassifier faceCascade;: Creates an object to load and use Haar cascade classifiers.faceCascade.load("haarcascade_frontalface_default.xml");: Loads the pre-trained Haar cascade for face detection. Ensure that thehaarcascade_frontalface_default.xmlfile is available in your working directory or provide the correct path.
- Capture Video:
cv::VideoCapture cap(0);: Opens the default camera (usually the webcam).cap >> frame;: Captures a frame from the video feed.
- Processing Frames:
- Convert to Grayscale:
cv::cvtColor(frame, gray, cv::COLOR_BGR2GRAY);converts the captured frame to grayscale as the face detection algorithm works on grayscale images. - Detect Faces:
faceCascade.detectMultiScale(gray, faces, 1.1, 3, 0, cv::Size(30, 30));detects faces and stores their locations in thefacesvector.
- Convert to Grayscale:
- Draw Rectangles:
cv::rectangle(frame, face, cv::Scalar(255, 0, 0), 2);draws rectangles around detected faces in the frame using a blue color and a thickness of 2.
- Display the Frame:
cv::imshow("Object Detection", frame);displays the frame with detected faces.
- Exit Loop:
if (cv::waitKey(30) >= 0) { break; }waits for 30 milliseconds for a key press and exits the loop if any key is pressed.
- Cleanup:
cap.release();releases the video capture object.cv::destroyAllWindows();closes all OpenCV windows.
Prerequisites:
- OpenCV Library: Ensure OpenCV is installed and properly configured with your C++ project.
Haar Cascade File: Ensure you have the Haar cascade file (haarcascade_frontalface_default.xml) available.
Compilation and Execution:
- Compile with OpenCV:
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g++ -o object_detection object_detection.cpp `pkg-config --cflags --libs opencv4` |
- Run the Program:
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./object_detection |