整个项目的结构图
2.编写DetectFaceDemo.java,代码如下：
[java] view plaincopy
package com.njupt.zhb.test
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.highgui.Highgui
import org.opencv.objdetect.CascadeClassifier
//
// Detects faces in an image, draws boxes around them, and writes the results
// to "faceDetection.png".
//
public class DetectFaceDemo {
public void run() {
System.out.println("\nRunning DetectFaceDemo")
System.out.println(getClass().getResource("lbpcascade_frontalface.xml").getPath())
// Create a face detector from the cascade file in the resources
// directory.
//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource("lbpcascade_frontalface.xml").getPath())
//Mat image = Highgui.imread(getClass().getResource("lena.png").getPath())
//注意：源程序的路径会多打印一个‘/’，因此总是出现如下错误
/*
* Detected 0 faces Writing faceDetection.png libpng warning: Image
* width is zero in IHDR libpng warning: Image height is zero in IHDR
* libpng error: Invalid IHDR data
*/
//因此，我们将第一个字符去掉
String xmlfilePath=getClass().getResource("lbpcascade_frontalface.xml").getPath().substring(1)
CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath)
Mat image = Highgui.imread(getClass().getResource("we.jpg").getPath().substring(1))
// Detect faces in the image.
// MatOfRect is a special container class for Rect.
MatOfRect faceDetections = new MatOfRect()
faceDetector.detectMultiScale(image, faceDetections)
System.out.println(String.format("Detected %s faces", faceDetections.toArray().length))
// Draw a bounding box around each face.
for (Rect rect : faceDetections.toArray()) {
Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0))
}
// Save the visualized detection.
String filename = "faceDetection.png"
System.out.println(String.format("Writing %s", filename))
Highgui.imwrite(filename, image)
}
}
3.编写测试类：
[java] view plaincopy
package com.njupt.zhb.test
public class TestMain {
public static void main(String[] args) {
System.out.println("Hello, OpenCV")
// Load the native library.
System.loadLibrary("opencv_java246")
new DetectFaceDemo().run()
}
}
//运行结果:
//Hello, OpenCV
//
//Running DetectFaceDemo
///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml
//Detected 8 faces
//Writing faceDetection.png
单纯的java是不能的这东西应该属于图形图象的范畴,C++选择不错.Java的图形图象单看Java给准备的那些类库就晓得了,垃圾的要死,根本没有任何价值,本身图形图象这块Java就干不过别人,也就没有进行主流发展,靠它去做这些东西,做梦吧.你见过有人伐树拿绳子伐的吗?它确实可以做到,但是要多大的成本和代价啊,衡量一下,如果用Java做出来,恐怕要的MONEY不会单单是你着100分的问题了,你在后面加上三个0,然后换成$单位,恐怕还有人会去想一想.
C++. 首先OpenCV2和3本身就是用C++编写的, 用C++可以做到和OpenCV的"无缝对接", OpenCV的C++资料也最多, 其次人脸识别等与图像相关的代码需要很高的运行时效率, 而C++的运行时效率远大于java, 最后, 在人脸识别的计算过程中有协方差矩阵的计算需要很大的内存(空间复杂度O(n^2),n为图像像素数,本身又是边长的平方), 所以要有一个内存动态管理方案, 或者从线性代数上对协方差矩阵的计算进行简化, 而高级编程语言中只有C和C++这两种语言才能直接操作内存.
