一共分为三步实现：
1，windows安装OpenCV 2，springboot整合OpenCV 3，实现全景图切割合并 windows安装OpenCV下载OpenCV
官网下载地址：https://opencv.org/releases/
这里下载的是windows版本的，如需下载安装lunix版本，请移步：
Lunix安装/编译/部署OpenCV4.5.2生成so文件
下载完成后得到exe程序安装包
运行exe安装包后得到
到这一步其实就已经完成了，特别简单！！！
但是我当时在网上看的时候好多都是配置环境变量，但我并没有配，照样可以用，不知道是因为什么
首先需要初始化一个springboot项目
然后找到我们刚才安装的OpenCV目录
opencvbuildjavax64opencv_java452.dll
opencvbuildjavaopencv-452.jar
把jar包和dll放入lib文件夹下
在项目中添加OpenCV依赖
配置pom.xml依赖（不配置这一步正常启动可以，但是打jar就不可以了）
org
opencv
4.5.2
system
${pom.basedir}srcmainresourceslibopencv-452.jar
true
到这一步算是已经整合完毕，也是挺简单的，下面就是具体全景图切割合并的代码
实现全景图切割合并ConverUtil.java
import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.*;
import java.net.URL;
public class ConverUtil {
public static final Mat matRead(String filePath) {
//return Highgui.imread("/home/night/webvr/vr.jpg");
// return Imgcodecs.imread("/home/night/webvr/vr.jpg");
return Imgcodecs.imread(filePath);
}
public static final BufferedImage bufferReadUrl(String urlStr) {
BufferedImage image = null;
try {
URL url = new URL(urlStr);
image = ImageIO.read(url);
} catch (Exception e) {
e.printStackTrace();
}
return image;
}
public static final void matSave(String fileName, Mat mat) {
//Highgui.imwrite(fileName, mat);
//Imgcodecs.imwrite(fileName, mat);
BufferedImage buff = matToBuffer(".jpg", mat);
bufferSave(fileName, buff);
}
public static final BufferedImage bufferRead(String filePath) {
try {
return ImageIO.read(new File(filePath));
} catch (IOException e) {
e.printStackTrace();
}
return null;
}
public static final void bufferSave(String fileName, BufferedImage buff) {
try {
ImageIO.write(buff, "JPEG", new File(fileName));
} catch (IOException e) {
e.printStackTrace();
}
}
public static final Mat matResize(Mat mat, int width, int height) {
Mat target = new Mat(width, height, mat.type());
//Imgproc.resize(src, dst, dsize);
Imgproc.resize(mat, target, new Size(width, height), 0, 0, Imgproc.INTER_LINEAR);
return target;
}
public static final BufferedImage matToBuffer(String fileExt, Mat mat) {
MatOfByte mob = new MatOfByte();
Imgcodecs.imencode(fileExt, mat, mob);
// convert the "matrix of bytes" into a byte array
byte[] byteArray = mob.toArray();
BufferedImage bufImage = null;
try {
InputStream in = new ByteArrayInputStream(byteArray);
bufImage = ImageIO.read(in);
} catch (Exception e) {
e.printStackTrace();
}
return bufImage;
}
public static Mat bufferToMat(BufferedImage bufferedImage, int imgType) {
final int matType = CvType.CV_8UC3;
if (bufferedImage == null) {
throw new IllegalArgumentException("bufferToMat-> BufferedImage == null");
}
if (bufferedImage.getType() != imgType) {
BufferedImage image = new BufferedImage(bufferedImage.getWidth(), bufferedImage.getHeight(), imgType);
Graphics2D g = image.createGraphics();
try {
g.setComposite(AlphaComposite.Src);
g.drawImage(bufferedImage, 0, 0, null);
} finally {
g.dispose();
}
}
byte[] pixels = ((DataBufferByte) bufferedImage.getRaster().getDataBuffer()).getData();
Mat mat = Mat.eye(bufferedImage.getHeight(), bufferedImage.getWidth(), matType);
mat.put(0, 0, pixels);
return mat;
}
public static Mat rotateRight(Mat src, int flipCode) {
Mat tmp = new Mat();
// 此函数是转置、（即将图像逆时针旋转90度，然后再关于x轴对称）
Core.transpose(src, tmp);
Mat result = new Mat();
// flipCode = 0 绕x轴旋转180， 也就是关于x轴对称
// flipCode = 1 绕y轴旋转180， 也就是关于y轴对称
// flipCode = -1 此函数关于原点对称
Core.flip(tmp, result, flipCode);
return result;
}
}
OpenCVUtil.java
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import java.awt.image.BufferedImage;
import java.io.File;
public class OpenCVUtil {
static {
String opencvDllName = "E:/Dowin_workspace/tjcloud-designer/tjcloud-designer-web/src/main/resources/lib/opencv_java452.dll"; //Linux 环境
//String opencvSoname = "/usr/local/share/java/opencv4/libopencv_java452.so"; //Linux中so文件地址
System.load(opencvDllName);
}
double[][] imageTransform =
{
{0, 0},
{Math.PI / 2, 0},
{Math.PI, 0},
{-Math.PI / 2, 0},
{0, -Math.PI / 2},
{0, Math.PI / 2}
};
public static void main(String[] args) {
OpenCVUtil util = new OpenCVUtil();
BufferedImage buff = ConverUtil.bufferRead("C:\Users\xQD\Desktop\kt.jpg");
//全景图切割
Mat[] cube = util.shear(buff, 1024, 1024);
//预览图合成
Mat preview = util.mergeImage(cube, 512);
}
public Mat[] shear(BufferedImage buff, int targetWidth, int targetHeight) {
Mat mat = ConverUtil.bufferToMat(buff, buff.getType());
Mat[] cube = new Mat[6];
for (int i = 0; i < 6; i++) {
cube[i] = sideCubeMapImage(mat, i, targetWidth, targetHeight);
}
return cube;
}
private Mat sideCubeMapImage(Mat source, final int sideId, final int sideWidth, final int sideHeight) {
Mat result = new Mat(sideWidth, sideHeight, source.type());
System.out.println("==========handle " + sideId + " start ===========");
// 获取图片的行列数量
float sourceWidth = source.cols();
float sourceHeight = source.rows();
//分配图的x,y轴
Mat mapx = new Mat(sideHeight, sideWidth, CvType.CV_32F);
Mat mapy = new Mat(sideHeight, sideWidth, CvType.CV_32F);
//计算相邻ak和相反an的三角形张成球体中心
final double an = Math.sin(Math.PI / 4);
final double ak = Math.cos(Math.PI / 4);
double ftu = imageTransform[sideId][0];
double ftv = imageTransform[sideId][1];
//对于每个图像计算相应的源坐标
for (int y = 0; y < sideHeight; y++) {
for (int x = 0; x < sideWidth; x++) {
//将坐标映射在平面上
float nx = (float) y / (float) sideHeight - 0.5f;
float ny = (float) x / (float) sideWidth - 0.5f;
nx *= 2;
ny *= 2;
// Map [-1, 1] plane coord to [-an, an]
// thats the coordinates in respect to a unit sphere
// that contains our box.
nx *= an;
ny *= an;
double u, v;
// Project from plane to sphere surface.
if (ftv == 0) {
// Center faces 中心面
u = Math.atan2(nx, ak);
v = Math.atan2(ny * Math.cos(u), ak);
u += ftu;
} else if (ftv > 0) {
// Bottom face 低面
double d = Math.sqrt(nx * nx + ny * ny);
v = Math.PI / 2 - Math.atan2(d, ak);
u = Math.atan2(ny, nx);
} else {
// Top face 顶面
//cout << "aaa";
double d = Math.sqrt(nx * nx + ny * ny);
v = -Math.PI / 2 + Math.atan2(d, ak);
u = Math.atan2(-ny, nx);
}
// Map from angular coordinates to [-1, 1], respectively.
u = u / (Math.PI);
v = v / (Math.PI / 2);
// Warp around, if our coordinates are out of bounds.
while (v < -1) {
v += 2;
u += 1;
}
while (v > 1) {
v -= 2;
u += 1;
}
while (u < -1) {
u += 2;
}
while (u > 1) {
u -= 2;
}
// Map from [-1, 1] to in texture space
u = u / 2.0f + 0.5f;
v = v / 2.0f + 0.5f;
u = u * (sourceWidth - 1);
v = v * (sourceHeight - 1);
mapx.put(x, y, u);
mapy.put(x, y, v);
}
}
// Do actual using OpenCV's remap
Imgproc.remap(source, result, mapx, mapy, Imgproc.INTER_LINEAR, Core.BORDER_CONSTANT, new Scalar(0, 0, 0));
if (sideId == 0) {
ConverUtil.matSave("E:\data\kct.tiles\a.jpg", result);
} else if (sideId == 1) {
ConverUtil.matSave("E:\data\kct.tiles\b.jpg", result);
} else if (sideId == 2) {
ConverUtil.matSave("E:\data\kct.tiles\c.jpg", result);
} else if (sideId == 3) {
ConverUtil.matSave("E:\data\kct.tiles\d.jpg", result);
} else if (sideId == 4) {
//旋转角度
result = ConverUtil.rotateRight(result, 1);
ConverUtil.matSave("E:\data\kct.tiles\e.jpg", result);
} else if (sideId == 5) {
//旋转角度
result = ConverUtil.rotateRight(result, 0);
ConverUtil.matSave("E:\data\kct.tiles\f.jpg", result);
}
System.out.println("==========handle " + sideId + " over ===========");
return result;
}
public Mat mergeImage(Mat[] cube, int width) {
Mat mat = new Mat(width * cube.length, width, cube[0].type());
for (int i = 0; i < cube.length; i++) {
Mat side = ConverUtil.matResize(cube[i], 512, 512);
mat.put(i * 512, 0, getByte(side));
}
ConverUtil.matSave("E:\data\kct.tiles\preview.jpg", mat);
return mat;
}
public byte[] getByte(Mat mat) {
int width = mat.cols();
int height = mat.rows();
int dims = mat.channels();
byte[] rgbdata = new byte[width * height * dims];
mat.get(0, 0, rgbdata);
return rgbdata;
}
}
效果图：
参考：https://blog.csdn.net/licheng989/article/details/79614833
