检测OpenCV 2.4.8中的多尺度参数,Java
我正在尝试使用OpenCV 2.4.8和使用detectMultiScale的Java从视频流中检测人脸。在网上搜索时,我注意到它有两个不同的参数列表版本。比如: 当我在代码中使用它时,会出现一个错误:检测OpenCV 2.4.8中的多尺度参数,Java,java,opencv,parameters,Java,Opencv,Parameters,我正在尝试使用OpenCV 2.4.8和使用detectMultiScale的Java从视频流中检测人脸。在网上搜索时,我注意到它有两个不同的参数列表版本。比如: 当我在代码中使用它时,会出现一个错误: OpenCV Error: Bad flag (parameter or structure field) (Unrecognized or unsupported array type) in cvGetMat 调试代码时,我看到错误出现在第行: face_cascade.detectMul
OpenCV Error: Bad flag (parameter or structure field) (Unrecognized or unsupported array type) in cvGetMat
调试代码时,我看到错误出现在第行:
face_cascade.detectMultiScale(frame_gray, faces);
我对这两个参数的方法感到困惑,因为在OpenCV文档站点中,它们只有一个带有七个参数的方法
detectMultiScale(const Mat& image, vector<Rect>& objects, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
detectMultiScale(常数矩阵和图像,向量和对象,双尺度因子=1.1,int-minNeighbors=3,int-flags=0,Size-minSize=Size(),Size-maxSize=Size())
谁能描述一下这个双参数方法是什么,它和我代码中的错误有什么联系吗。以下是我检查的代码:
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.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
public class FaceDetectSVM {
/**
* @param args
*/
public static void main(String[] args) {
//load opencv native library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
CascadeClassifier face_cascade = new CascadeClassifier("haarcascade_frontalface_alt.xml");
CascadeClassifier eyes_cascade = new CascadeClassifier("haarcascade_eye.xml");
String window_name = "Capture - Face detection.jpg";
System.out.println("capture through camera "+Core.VERSION);
//load the face xml cascade
if(!face_cascade.load("haarcascade_frontalface_alt.xml"))
{
System.out.println("Error loading face cascade");
}
else
{
System.out.println("Success loading face cascade");
}
//load the eyes xml cascade
if(!eyes_cascade.load("haarcascade_eye.xml"))
{
System.out.println("Error loading eyes cascade");
}
else
{
System.out.println("Success loading eyes cascade");
}
//detect default camera
VideoCapture capture = new VideoCapture(0);
if(!capture.isOpened())
{
System.out.println("Did not connected to camera.");
}
else
{
System.out.println("Conected to camera: "+capture.toString());
}
//create new Mat image
Mat frame = new Mat();
while(true){
capture.retrieve(frame);
Mat frame_gray = new Mat();
Imgproc.cvtColor(frame, frame_gray, Imgproc.COLOR_BGRA2GRAY);
Imgproc.equalizeHist(frame_gray, frame_gray);
MatOfRect faces = new MatOfRect();
face_cascade.detectMultiScale(frame_gray, faces);
Rect[] facesArray = faces.toArray();
for(int i=0; i<facesArray.length; i++)
{
Point center = new Point(facesArray[i].x + facesArray[i].width * 0.5, facesArray[i].y + facesArray[i].height * 0.5);
Core.ellipse(frame, center, new Size(facesArray[i].width * 0.5, facesArray[i].height * 0.5), 0, 0, 360, new Scalar(255, 0, 255), 4, 8, 0);
Mat faceROI = frame_gray.submat(facesArray[i]);
MatOfRect eyes = new MatOfRect();
//-- In each face, detect eyes
eyes_cascade.detectMultiScale(faceROI, eyes, 1.1, 2, 0,new Size(30,30), new Size());
Rect[] eyesArray = eyes.toArray();
for (int j = 0; j < eyesArray.length; j++)
{
Point center1 = new Point(facesArray[i].x + eyesArray[i].x + eyesArray[i].width * 0.5, facesArray[i].y + eyesArray[i].y + eyesArray[i].height * 0.5);
int radius = (int) Math.round((eyesArray[i].width + eyesArray[i].height) * 0.25);
Core.circle(frame, center1, radius, new Scalar(255, 0, 0), 4, 8, 0);
}
}
Highgui.imwrite(window_name, frame);
capture.release();
}
}
}
import org.opencv.core.core;
导入org.opencv.core.Mat;
导入org.opencv.core.MatOfRect;
导入org.opencv.core.Point;
导入org.opencv.core.Rect;
导入org.opencv.core.Scalar;
导入org.opencv.core.Size;
导入org.opencv.highgui.highgui;
导入org.opencv.highgui.VideoCapture;
导入org.opencv.imgproc.imgproc;
导入org.opencv.objdetect.CascadeClassifier;
公共类FaceDetectSVM{
/**
*@param args
*/
公共静态void main(字符串[]args){
//加载opencv本机库
System.loadLibrary(Core.NATIVE\u LIBRARY\u NAME);
CascadeClassifier face_cascade=新的cascade分类器(“haarcascade_frontalface_alt.xml”);
CascadeClassifier eyes_cascade=新的CascadeClassifier(“haarcascade_eye.xml”);
String window_name=“Capture-Face detection.jpg”;
System.out.println(“通过摄像头捕获”+核心版);
//加载面xml级联
如果(!face_cascade.load(“haarcascade_frontalface_alt.xml”))
{
System.out.println(“错误加载面级联”);
}
其他的
{
System.out.println(“成功加载面级联”);
}
//加载xml级联
如果(!eyes\u cascade.load(“haarcascade\u eye.xml”))
{
System.out.println(“错误加载眼级联”);
}
其他的
{
System.out.println(“成功加载眼睛级联”);
}
//检测默认摄像机
视频捕获=新视频捕获(0);
如果(!capture.isOpened())
{
System.out.println(“未连接到摄像头”);
}
其他的
{
System.out.println(“连接到摄像头:+capture.toString());
}
//创建新的Mat图像
垫架=新垫();
while(true){
捕获。检索(帧);
垫框_灰色=新垫();
Imgproc.cvt颜色(帧、帧灰、Imgproc.COLOR\u BGRA2GRAY);
Imgproc.equalizeHist(帧灰,帧灰);
MatOfRect面=新的MatOfRect();
面层叠。检测多尺度(帧灰,面);
Rect[]facesArray=faces.toArray();
对于java(C++)java语言包装器允许通过JNI访问本机代码。与C++不同,Java不支持默认参数值。该文档是C++的,因此有一个函数有5个默认参数值。为了说明这个问题,OpenCV Java包装器有6种方法。您所得到的错误,理想上不应该是因为这个
试试下面
capture.release()
while(!done){…}
在capture.retrieve(frame);
之后,添加if(frame.empty()){continue;}
谢谢你的帮助:)无论如何,我都可以纠正它并获得所需的输出。仍然在用Java学习OpenCV的基础知识。
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.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
public class FaceDetectSVM {
/**
* @param args
*/
public static void main(String[] args) {
//load opencv native library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
CascadeClassifier face_cascade = new CascadeClassifier("haarcascade_frontalface_alt.xml");
CascadeClassifier eyes_cascade = new CascadeClassifier("haarcascade_eye.xml");
String window_name = "Capture - Face detection.jpg";
System.out.println("capture through camera "+Core.VERSION);
//load the face xml cascade
if(!face_cascade.load("haarcascade_frontalface_alt.xml"))
{
System.out.println("Error loading face cascade");
}
else
{
System.out.println("Success loading face cascade");
}
//load the eyes xml cascade
if(!eyes_cascade.load("haarcascade_eye.xml"))
{
System.out.println("Error loading eyes cascade");
}
else
{
System.out.println("Success loading eyes cascade");
}
//detect default camera
VideoCapture capture = new VideoCapture(0);
if(!capture.isOpened())
{
System.out.println("Did not connected to camera.");
}
else
{
System.out.println("Conected to camera: "+capture.toString());
}
//create new Mat image
Mat frame = new Mat();
while(true){
capture.retrieve(frame);
Mat frame_gray = new Mat();
Imgproc.cvtColor(frame, frame_gray, Imgproc.COLOR_BGRA2GRAY);
Imgproc.equalizeHist(frame_gray, frame_gray);
MatOfRect faces = new MatOfRect();
face_cascade.detectMultiScale(frame_gray, faces);
Rect[] facesArray = faces.toArray();
for(int i=0; i<facesArray.length; i++)
{
Point center = new Point(facesArray[i].x + facesArray[i].width * 0.5, facesArray[i].y + facesArray[i].height * 0.5);
Core.ellipse(frame, center, new Size(facesArray[i].width * 0.5, facesArray[i].height * 0.5), 0, 0, 360, new Scalar(255, 0, 255), 4, 8, 0);
Mat faceROI = frame_gray.submat(facesArray[i]);
MatOfRect eyes = new MatOfRect();
//-- In each face, detect eyes
eyes_cascade.detectMultiScale(faceROI, eyes, 1.1, 2, 0,new Size(30,30), new Size());
Rect[] eyesArray = eyes.toArray();
for (int j = 0; j < eyesArray.length; j++)
{
Point center1 = new Point(facesArray[i].x + eyesArray[i].x + eyesArray[i].width * 0.5, facesArray[i].y + eyesArray[i].y + eyesArray[i].height * 0.5);
int radius = (int) Math.round((eyesArray[i].width + eyesArray[i].height) * 0.25);
Core.circle(frame, center1, radius, new Scalar(255, 0, 0), 4, 8, 0);
}
}
Highgui.imwrite(window_name, frame);
capture.release();
}
}
}