- OpenCV - GUI
- OpenCV - Writing an Image
- OpenCV - Reading Images
- OpenCV - Storing Images
- OpenCV - Environment
- OpenCV - Overview
- OpenCV - Home
Types of Images
Image Conversion
Drawing Functions
- OpenCV - Adding Text
- OpenCV - Drawing Arrowed Lines
- OpenCV - Drawing Convex Polylines
- OpenCV - Drawing Polylines
- OpenCV - Drawing an Ellipse
- OpenCV - Drawing a Rectangle
- OpenCV - Drawing a Line
- OpenCV - Drawing a Circle
Blur
Filtering
- OpenCV - Image Pyramids
- OpenCV - Morphological Operations
- OpenCV - Erosion
- OpenCV - Dilation
- OpenCV - Filter2D
- OpenCV - SQRBox Filter
- OpenCV - Box Filter
- OpenCV - Bilateral Filter
Thresholding
Sobel Derivatives
Transformation Operations
Camera and Face Detection
Geometric Transformations
Miscellaneous Chapters
OpenCV Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
OpenCV - Face Detection in a Picture
The VideoCapture class of the org.opencv.videoio package contains classes and methods to capture video using the system camera. Let’s go step by step and learn how to do it.
Step 1: Load the OpenCV native pbrary
While writing Java code using OpenCV pbrary, the first step you need to do is to load the native pbrary of OpenCV using the loadLibrary(). Load the OpenCV native pbrary as shown below.
// Loading the core pbrary System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
Step 2: Instantiate the CascadeClassifier class
The CascadeClassifier class of the package org.opencv.objdetect is used to load the classifier file. Instantiate this class by passing the xml file lbpcascade_frontalface.xml as shown below.
// Instantiating the CascadeClassifier String xmlFile = "E:/OpenCV/facedetect/lbpcascade_frontalface.xml"; CascadeClassifier classifier = new CascadeClassifier(xmlFile);
Step 3: Detect the faces
You can detect the faces in the image using method detectMultiScale() of the class named CascadeClassifier. This method accepts an object of the class Mat holding the input image and an object of the class MatOfRect to store the detected faces.
// Detecting the face in the snap MatOfRect faceDetections = new MatOfRect(); classifier.detectMultiScale(src, faceDetections);
Example
The following program demonstrates how to detect faces in an image.
import org.opencv.core.Core; import org.opencv.core.Mat; import org.opencv.core.MatOfRect; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; import org.opencv.objdetect.CascadeClassifier; pubpc class FaceDetectionImage { pubpc static void main (String[] args) { // Loading the OpenCV core pbrary System.loadLibrary( Core.NATIVE_LIBRARY_NAME ); // Reading the Image from the file and storing it in to a Matrix object String file ="E:/OpenCV/chap23/facedetection_input.jpg"; Mat src = Imgcodecs.imread(file); // Instantiating the CascadeClassifier String xmlFile = "E:/OpenCV/facedetect/lbpcascade_frontalface.xml"; CascadeClassifier classifier = new CascadeClassifier(xmlFile); // Detecting the face in the snap MatOfRect faceDetections = new MatOfRect(); classifier.detectMultiScale(src, faceDetections); System.out.println(String.format("Detected %s faces", faceDetections.toArray().length)); // Drawing boxes for (Rect rect : faceDetections.toArray()) { Imgproc.rectangle( src, // where to draw the box new Point(rect.x, rect.y), // bottom left new Point(rect.x + rect.width, rect.y + rect.height), // top right new Scalar(0, 0, 255), 3 // RGB colour ); } // Writing the image Imgcodecs.imwrite("E:/OpenCV/chap23/facedetect_output1.jpg", src); System.out.println("Image Processed"); } }
Assume that following is the input image facedetection_input.jpg specified in the above program.
![FaceDetection Input](/opencv/images/facedetection_input.jpg)
Output
On executing the program, you will get the following output −
Detected 3 faces Image Processed
If you open the specified path, you can observe the output image as follows −
![FaceDetection Output](/opencv/images/facedetection_output.jpg)