Eclipse配置javaCV开发环境

Eclipse配置javaCV开发环境

JavaCV 是一款开源的视觉处理库，基于GPLv2协议。JavaCV是对各种常用计算机视觉库的封装后的一组jar包，其中封装了OpenCV、libdc1394、OpenKinect、videoInput和ARToolKitPlus等计算机视觉编程人员常用库的接口，可以通过其中的utility类方便的在包括Android在内的Java平台上调用这些接口。

1、需要软件

要想使用JavaCV, 需要先下载和配置以下软件：
（1）An implementation of Java SE 7 or newer:

• OpenJDK http://openjdk.java.net/install/ 

或者

• Sun JDK http://www.oracle.com/technetwork/java/javase/downloads/ 

或者

• IBM JDK http://www.ibm.com/developerworks/java/jdk/

（2）JavaCV下载

JavaCV下载地址：https://github.com/bytedeco/javacv/

这里下载的是javacv-platform-1.3-bin.zip。

javacv-platform-1.3-bin.zip解压后里面包含一个samples文件夹和若干jar文件。

（3）我的电脑已安装的软件Eclipse+JavaSE8。

3、安装配置

（1）新建java工程“Test_javaCV”。

（2）右击工程，选择Java Build Path ----> Libraries---->用户库(User Libray)-->新建(New)，给出用户库名，这里我设为javacv-1.3。
（3）添加JAR包，选择“Add External JARS”，选择下载的有关文件，javacpp.jar、javacv.jar、opencv.jar、opencv-windows-x86.jar等。然后把javacv-bin里的jar文件选中（根据自己的平台来），选OK即可

4、测试配置

在有些例程中import是这样的：

            import static com.googlecode.javacv.cpp.opencv_core.*;            import static com.googlecode.javacv.cpp.opencv_imgproc.*;            import static com.googlecode.javacv.cpp.opencv_highgui.*;

但按照我们的版本，应该是这样的：

                      import static org.bytedeco.javacpp.opencv_core.*;            import static org.bytedeco.javacpp.opencv_imgproc.*;            import static org.bytedeco.javacpp.opencv_highgui.*;

简言之，就是把com.googlecode.javacv.cpp 全改为org.bytedeco.javacpp。

测试实例

新建一个Resources文件夹，将待检测的图像放到此文件夹下。

Test_javaCV.java代码：

import javax.swing.JFrame;import org.bytedeco.javacpp.*;import org.bytedeco.javacv.*;import static org.bytedeco.javacpp.opencv_core.*;import static org.bytedeco.javacpp.opencv_imgproc.*;import static org.bytedeco.javacpp.opencv_imgcodecs.*;/** * C to Java translation of the houghlines.c sample provided in the c sample directory of OpenCV 2.1, * using the JavaCV Java wrapper of OpenCV 2.2 developped by Samuel Audet. * * @author Jeremy Nicola * [e-mail] */public class Test_javaCV {    /**     * usage: java HoughLines imageDir\imageName TransformType     */    public static void main(String[] args) {        String fileName = args.length >= 1 ? args[0] : "./Resources/pic1.png"; // if no params provided, compute the defaut image        IplImage src = cvLoadImage(fileName, 0);        IplImage dst;        IplImage colorDst;        CvMemStorage storage = cvCreateMemStorage(0);        CvSeq lines = new CvSeq();        CanvasFrame source = new CanvasFrame("Source");        CanvasFrame hough = new CanvasFrame("Hough");        OpenCVFrameConverter.ToIplImage sourceConverter = new OpenCVFrameConverter.ToIplImage();        OpenCVFrameConverter.ToIplImage houghConverter = new OpenCVFrameConverter.ToIplImage();        if (src == null) {            System.out.println("Couldn't load source image.");            return;        }        dst = cvCreateImage(cvGetSize(src), src.depth(), 1);        colorDst = cvCreateImage(cvGetSize(src), src.depth(), 3);        cvCanny(src, dst, 50, 200, 3);        cvCvtColor(dst, colorDst, CV_GRAY2BGR);        /*         * apply the probabilistic hough transform         * which returns for each line deteced two points ((x1, y1); (x2,y2))         * defining the detected segment         */        if (args.length == 2 && args[1].contentEquals("probabilistic")) {             System.out.println("Using the Probabilistic Hough Transform");            lines = cvHoughLines2(dst, storage, CV_HOUGH_PROBABILISTIC, 1, Math.PI / 180, 40, 50, 10, 0, CV_PI);            for (int i = 0; i < lines.total(); i++) {                // Based on JavaCPP, the equivalent of the C code:                // CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);                // CvPoint first=line[0], second=line[1]                // is:                Pointer line = cvGetSeqElem(lines, i);                CvPoint pt1  = new CvPoint(line).position(0);                CvPoint pt2  = new CvPoint(line).position(1);                System.out.println("Line spotted: ");                System.out.println("\t pt1: " + pt1);                System.out.println("\t pt2: " + pt2);                cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0); // draw the segment on the image            }        }        /*         * Apply the multiscale hough transform which returns for each line two float parameters (rho, theta)         * rho: distance from the origin of the image to the line         * theta: angle between the x-axis and the normal line of the detected line         */        else if(args.length==2 && args[1].contentEquals("multiscale")){                        System.out.println("Using the multiscale Hough Transform"); //            lines = cvHoughLines2(dst, storage, CV_HOUGH_MULTI_SCALE, 1, Math.PI / 180, 40, 1, 1, 0, CV_PI);            for (int i = 0; i < lines.total(); i++) {                CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));                float rho=point.x();                float theta=point.y();                double a = Math.cos((double) theta), b = Math.sin((double) theta);                double x0 = a * rho, y0 = b * rho;                CvPoint pt1 = cvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))), pt2 = cvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));                System.out.println("Line spoted: ");                System.out.println("\t rho= " + rho);                System.out.println("\t theta= " + theta);                cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);            }        }        /*         * Default: apply the standard hough transform. Outputs: same as the multiscale output.         */        else {            System.out.println("Using the Standard Hough Transform");            lines = cvHoughLines2(dst, storage, CV_HOUGH_STANDARD, 1, Math.PI / 180, 90, 0, 0, 0, CV_PI);            for (int i = 0; i < lines.total(); i++) {                CvPoint2D32f point = new CvPoint2D32f(cvGetSeqElem(lines, i));                float rho=point.x();                float theta=point.y();                double a = Math.cos((double) theta), b = Math.sin((double) theta);                double x0 = a * rho, y0 = b * rho;                CvPoint pt1 = cvPoint((int) Math.round(x0 + 1000 * (-b)), (int) Math.round(y0 + 1000 * (a))), pt2 = cvPoint((int) Math.round(x0 - 1000 * (-b)), (int) Math.round(y0 - 1000 * (a)));                System.out.println("Line spotted: ");                System.out.println("\t rho= " + rho);                System.out.println("\t theta= " + theta);                cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0);            }        }        source.showImage(sourceConverter.convert(src));        hough.showImage(houghConverter.convert(colorDst));        source.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);        hough.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);    }}

运行结果