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看到之前有248位小伙伴看我写的水文还是比较受鼓舞的,所以决定把这个细写一下:
就是javacv怎么实际应用一下:
其实无外乎导包,写测试代码。
这样 那我们先导包儿。
javacv-1.2-bin(jar包的下载在这里:找一样名字的就行:http://www.cnblogs.com/letben/p/5662619.html)
他好像可以去git上下载,我忘记了 下载地址了,所以 去找找吧。
然后解压缩F:\jarPackage\opencv\javacv-1.2-bin\javacv-bin一直到这层目录,下面有茫茫多的.jar 文件,所以 待会儿 我们我们把它们全部导入就可以了。
好了好了好了,,,又小小的写了一下,应该是没有什么问题了。
1、打开 eclipse 然后新建工程
2、导入刚下载的那一票java包(对了我下载的大小是169Mb的压缩包,解压以后是170Mb)
3、写写代码:
import org.bytedeco.javacpp.opencv_core.IplImage; import static org.bytedeco.javacpp.opencv_imgcodecs.cvLoadImage; import org.bytedeco.javacpp.opencv_core.CvMat; import org.bytedeco.javacv.CanvasFrame; import org.bytedeco.javacv.OpenCVFrameConverter; public class JustDisplay { public static void main(String args[]){ IplImage rawImage = null; rawImage = cvLoadImage("Rice.jpg"); ShowImage(rawImage, "RawImage", 256); } public static void ShowImage(IplImage image, String caption, int size) { if(size < 128) size = 128; CvMat mat = image.asCvMat(); int width = mat.cols(); if(width < 1) width = 1; int height = mat.rows(); if(height < 1) height = 1; double aspect = 1.0 * width / height; if(height != size) { height = size; width = (int) ( height * aspect ); } if(width != size) width = size; height = (int) ( width / aspect ); ShowImage(image, caption, width, height); } public static void ShowImage(IplImage image, String caption, int width, int height) { CanvasFrame canvas = new CanvasFrame(caption, 1); // gamma=1 canvas.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE); canvas.setCanvasSize(width, height); OpenCVFrameConverter converter = new OpenCVFrameConverter.ToIplImage(); canvas.showImage(converter.convert(image)); } }
反正都是逐句摘得,别问为什么,这就是 人家写包的原因,底层应该是 看不到的吧,然后 应该是 调的 现成的 写好的 c/c++ 的代码。也就是说,如果想改该算法或者优化的话还是要在vs的环境里面,这里面只能是调用(这是我瞎说的,我记得之前读到过这么句话,如果有异议的话,请告诉我如何在java的语言下优化图像处理的算法)
然后导入一张名叫Rice.jpg 的图片。这样就写好了。
今天懒就不截图了
然后这是一个简单版本的,所有代码都是从这个里面抄来的,上一篇那个javacv里面应该有相关源代码:这里面提供了更多的代码使用方式:可以看看:(下面的代码跑不了,应该是出在了 没有导入图片上)
如果还是有问题可以留邮箱,发代码~~~
import static org.bytedeco.javacpp.opencv_core.CV_8UC1; import static org.bytedeco.javacpp.opencv_core.IPL_DEPTH_8U; import static org.bytedeco.javacpp.opencv_core.cvCreateImage; import static org.bytedeco.javacpp.opencv_core.cvCreateMat; import static org.bytedeco.javacpp.opencv_core.cvFlip; import static org.bytedeco.javacpp.opencv_core.cvGetSize; import static org.bytedeco.javacpp.opencv_core.cvNot; import static org.bytedeco.javacpp.opencv_core.cvPoint; import static org.bytedeco.javacpp.opencv_core.cvReleaseImage; import static org.bytedeco.javacpp.opencv_core.cvScalar; import static org.bytedeco.javacpp.opencv_core.cvSetZero; import static org.bytedeco.javacpp.opencv_core.cvSize; import static org.bytedeco.javacpp.opencv_core.cvSum; import static org.bytedeco.javacpp.opencv_core.cvTranspose; import static org.bytedeco.javacpp.opencv_imgcodecs.cvLoadImage; import static org.bytedeco.javacpp.opencv_imgproc.CV_BGR2GRAY; import static org.bytedeco.javacpp.opencv_imgproc.CV_THRESH_BINARY; import static org.bytedeco.javacpp.opencv_imgproc.cvCvtColor; import static org.bytedeco.javacpp.opencv_imgproc.cvDilate; import static org.bytedeco.javacpp.opencv_imgproc.cvErode; import static org.bytedeco.javacpp.opencv_imgproc.cvRectangle; import static org.bytedeco.javacpp.opencv_imgproc.cvThreshold; import org.bytedeco.javacpp.opencv_core.CvMat; import org.bytedeco.javacpp.opencv_core.CvPoint; import org.bytedeco.javacpp.opencv_core.CvScalar; import org.bytedeco.javacpp.opencv_core.IplImage; import org.bytedeco.javacv.Blobs; import org.bytedeco.javacv.CanvasFrame; import org.bytedeco.javacv.OpenCVFrameConverter; public class tryy { public static void main(String[] args) { System.out.println("STARTING...\n"); demo(); System.out.println("ALL DONE"); } public static void demo() { int MinArea = 6; int ErodeCount =0; int DilateCount = 0; IplImage RawImage = null; // Read an image. for(int k = 0; k < 7; k++) { if(k == 0) { RawImage = cvLoadImage("BlackBalls.jpg"); MinArea = 250; ErodeCount = 0; DilateCount = 1; } else if(k == 1) { RawImage = cvLoadImage("Shapes1.jpg"); MinArea = 6; ErodeCount = 0; DilateCount = 1; } else if(k == 2) { RawImage = cvLoadImage("Shapes2.jpg"); MinArea = 250; ErodeCount = 0; DilateCount = 1; } else if(k == 3) { RawImage = cvLoadImage("Blob1.jpg"); MinArea = 2800; ErodeCount = 1; DilateCount = 1; } else if(k == 4) { RawImage = cvLoadImage("Blob2.jpg"); MinArea = 2800; ErodeCount = 1; DilateCount = 1; } else if(k == 5) { RawImage = cvLoadImage("Blob3.jpg"); MinArea = 2800; ErodeCount = 1; DilateCount = 1; } else if(k == 6) { RawImage = cvLoadImage("Rice.jpg"); MinArea = 30; ErodeCount = 2; DilateCount = 1; } //ShowImage(RawImage, "RawImage", 512); IplImage GrayImage = cvCreateImage(cvGetSize(RawImage), IPL_DEPTH_8U, 1); cvCvtColor(RawImage, GrayImage, CV_BGR2GRAY); //ShowImage(GrayImage, "GrayImage", 512); IplImage BWImage = cvCreateImage(cvGetSize(GrayImage), IPL_DEPTH_8U, 1); cvThreshold(GrayImage, BWImage, 127, 255, CV_THRESH_BINARY); //ShowImage(BWImage, "BWImage"); IplImage WorkingImage = cvCreateImage(cvGetSize(BWImage), IPL_DEPTH_8U, 1); cvErode(BWImage, WorkingImage, null, ErodeCount); cvDilate(WorkingImage, WorkingImage, null, DilateCount); //ShowImage(WorkingImage, "WorkingImage", 512); //cvSaveImage("Working.jpg", WorkingImage); //PrintGrayImage(WorkingImage, "WorkingImage"); //BinaryHistogram(WorkingImage); Blobs Regions = new Blobs(); Regions.BlobAnalysis( WorkingImage, // image -1, -1, // ROI start col, row -1, -1, // ROI cols, rows 1, // border (0 = black; 1 = white) MinArea); // minarea Regions.PrintRegionData(); for(int i = 1; i <= Blobs.MaxLabel; i++) { double [] Region = Blobs.RegionData[i]; int Parent = (int) Region[Blobs.BLOBPARENT]; int Color = (int) Region[Blobs.BLOBCOLOR]; int MinX = (int) Region[Blobs.BLOBMINX]; int MaxX = (int) Region[Blobs.BLOBMAXX]; int MinY = (int) Region[Blobs.BLOBMINY]; int MaxY = (int) Region[Blobs.BLOBMAXY]; Highlight(RawImage, MinX, MinY, MaxX, MaxY, 1); } ShowImage(RawImage, "RawImage", 256);//最后一个参数图片展示大小的。 cvReleaseImage(GrayImage); GrayImage = null; cvReleaseImage(BWImage); BWImage = null; cvReleaseImage(WorkingImage); WorkingImage = null; } cvReleaseImage(RawImage); RawImage = null; } // Versions with 2, 3, and 4 parms respectively public static void ShowImage(IplImage image, String caption) { CvMat mat = image.asCvMat(); int width = mat.cols(); if(width < 1) width = 1; int height = mat.rows(); if(height < 1) height = 1; double aspect = 1.0 * width / height; if(height < 128) { height = 128; width = (int) ( height * aspect ); } if(width < 128) width = 128; height = (int) ( width / aspect ); ShowImage(image, caption, width, height); } public static void ShowImage(IplImage image, String caption, int size) { if(size < 128) size = 128; CvMat mat = image.asCvMat(); int width = mat.cols(); if(width < 1) width = 1; int height = mat.rows(); if(height < 1) height = 1; double aspect = 1.0 * width / height; if(height != size) { height = size; width = (int) ( height * aspect ); } if(width != size) width = size; height = (int) ( width / aspect ); ShowImage(image, caption, width, height); } public static void ShowImage(IplImage image, String caption, int width, int height) { CanvasFrame canvas = new CanvasFrame(caption, 1); // gamma=1 canvas.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE); canvas.setCanvasSize(width, height); OpenCVFrameConverter converter = new OpenCVFrameConverter.ToIplImage(); canvas.showImage(converter.convert(image)); } public static void Highlight(IplImage image, int [] inVec) { Highlight(image, inVec[0], inVec[1], inVec[2], inVec[3], 1); } public static void Highlight(IplImage image, int [] inVec, int Thick) { Highlight(image, inVec[0], inVec[1], inVec[2], inVec[3], Thick); } public static void Highlight(IplImage image, int xMin, int yMin, int xMax, int yMax) { Highlight(image, xMin, yMin, xMax, yMax, 1); } public static void Highlight(IplImage image, int xMin, int yMin, int xMax, int yMax, int Thick) { CvPoint pt1 = cvPoint(xMin,yMin); CvPoint pt2 = cvPoint(xMax,yMax); CvScalar color = cvScalar(255,0,0,0); // blue [green] [red] cvRectangle(image, pt1, pt2, color, Thick, 4, 0); } public static void PrintGrayImage(IplImage image, String caption) { int size = 512; // impractical to print anything larger CvMat mat = image.asCvMat(); int cols = mat.cols(); if(cols < 1) cols = 1; int rows = mat.rows(); if(rows < 1) rows = 1; double aspect = 1.0 * cols / rows; if(rows > size) { rows = size; cols = (int) ( rows * aspect ); } if(cols > size) cols = size; rows = (int) ( cols / aspect ); PrintGrayImage(image, caption, 0, cols, 0, rows); } public static void PrintGrayImage(IplImage image, String caption, int MinX, int MaxX, int MinY, int MaxY) { int size = 512; // impractical to print anything larger CvMat mat = image.asCvMat(); int cols = mat.cols(); if(cols < 1) cols = 1; int rows = mat.rows(); if(rows < 1) rows = 1; if(MinX < 0) MinX = 0; if(MinX > cols) MinX = cols; if(MaxX < 0) MaxX = 0; if(MaxX > cols) MaxX = cols; if(MinY < 0) MinY = 0; if(MinY > rows) MinY = rows; if(MaxY < 0) MaxY = 0; if(MaxY > rows) MaxY = rows; System.out.println("\n" + caption); System.out.print(" +"); for(int icol = MinX; icol < MaxX; icol++) System.out.print("-"); System.out.println("+"); for(int irow = MinY; irow < MaxY; irow++) { if(irow<10) System.out.print(" "); if(irow<100) System.out.print(" "); System.out.print(irow); System.out.print("|"); for(int icol = MinX; icol < MaxX; icol++) { int val = (int) mat.get(irow,icol); String C = " "; if(val == 0) C = "*"; System.out.print(C); } System.out.println("|"); } System.out.print(" +"); for(int icol = MinX; icol < MaxX; icol++) System.out.print("-"); System.out.println("+"); } public static void PrintImageProperties(IplImage image) { CvMat mat = image.asCvMat(); int cols = mat.cols(); int rows = mat.rows(); int depth = mat.depth(); System.out.println("ImageProperties for " + image + " : cols=" + cols + " rows=" + rows + " depth=" + depth); } public static float BinaryHistogram(IplImage image) { CvScalar Sum = cvSum(image); float WhitePixels = (float) ( Sum.getVal(0) / 255 ); CvMat mat = image.asCvMat(); float TotalPixels = mat.cols() * mat.rows(); //float BlackPixels = TotalPixels - WhitePixels; return WhitePixels / TotalPixels; } // Counterclockwise small angle rotation by skewing - Does not stretch border pixels public static IplImage SkewGrayImage(IplImage Src, double angle) // angle is in radians { //double radians = - Math.PI * angle / 360.0; // Half because skew is horizontal and vertical double sin = - Math.sin(angle); double AbsSin = Math.abs(sin); int nChannels = Src.nChannels(); if(nChannels != 1) { System.out.println("ERROR: SkewGrayImage: Require 1 channel: nChannels=" + nChannels); System.exit(1); } CvMat SrcMat = Src.asCvMat(); int SrcCols = SrcMat.cols(); int SrcRows = SrcMat.rows(); double WidthSkew = AbsSin * SrcRows; double HeightSkew = AbsSin * SrcCols; int DstCols = (int) ( SrcCols + WidthSkew ); int DstRows = (int) ( SrcRows + HeightSkew ); CvMat DstMat = cvCreateMat(DstRows, DstCols, CV_8UC1); // Type matches IPL_DEPTH_8U cvSetZero(DstMat); cvNot(DstMat, DstMat); for(int irow = 0; irow < DstRows; irow++) { int dcol = (int) ( WidthSkew * irow / SrcRows ); for(int icol = 0; icol < DstCols; icol++) { int drow = (int) ( HeightSkew - HeightSkew * icol / SrcCols ); int jrow = irow - drow; int jcol = icol - dcol; if(jrow < 0 || jcol < 0 || jrow >= SrcRows || jcol >= SrcCols) DstMat.put(irow, icol, 255); else DstMat.put(irow, icol, (int) SrcMat.get(jrow,jcol)); } } IplImage Dst = cvCreateImage(cvSize(DstCols, DstRows), IPL_DEPTH_8U, 1); Dst = DstMat.asIplImage(); return Dst; } public static IplImage TransposeImage(IplImage SrcImage) { CvMat mat = SrcImage.asCvMat(); int cols = mat.cols(); int rows = mat.rows(); IplImage DstImage = cvCreateImage(cvSize(rows, cols), IPL_DEPTH_8U, 1); cvTranspose(SrcImage, DstImage); cvFlip(DstImage,DstImage,1); return DstImage; } }
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原文地址:http://www.cnblogs.com/letben/p/5885799.html