前言
今天微信群里聊天，群友问道有没有能让人脸露牙齿的接口，我记得想百度阿里的都应该有类似人脸识别，分析、融合的api,但是我百度了一下，确实没有找到，可能他们提供的都是最基础的接口，如果想实现自己的想要的某种效果，比如人脸微笑，露牙等，还需要自己开发。想这样让一张没有露牙的图片，变成露牙的照片，第一步肯能是先要再图片上检测到人脸，其次是嘴巴，然后再用算法合成到图像嘴边的位置。于是再网站搜搜，发现java 有人脸检测和识别的功能，于是想研究一下，百度很多，发现用java实现的检测和识别的代码都是1-2年前，代码比较老旧，文字太少，没说清楚，于是经过自己一下午的研究，终于搞出来了，分享给大家。
一、javaCV是什么？
javaCV是多种开源计算机视觉库组成的包装库。 JavaCV [1] 是一款基于JavaCPP [2] 调用方式（JNI的一层封装），由多种开源计算机视觉库组成的包装库，封装了包含FFmpeg、OpenCV、tensorflow、caffe、tesseract、libdc1394、OpenKinect、videoInput和ARToolKitPlus等在内的计算机视觉领域的常用库和实用程序类。 JavaCV基于Apache License Version 2.0协议和GPLv2两种协议 [3] ， JavaCV支持Windows、Linux、MacOS，Android、IOS在内的Java平台上调用这些接口。
二、使用步骤
1.引入库
maven只引入jar依赖
<!-- https://mvnrepository.com/artifact/org.bytedeco/javacv-platform --> <dependency> <groupId>org.bytedeco</groupId> <artifactId>javacv-platform</artifactId> <version>1.5.5</version> </dependency>
2.代码教程
代码如下：
import org.bytedeco.javacv.Frame; import org.bytedeco.javacv.Java2DFrameConverter; import org.bytedeco.javacv.OpenCVFrameConverter; import org.bytedeco.opencv.opencv_core.*; import org.bytedeco.opencv.opencv_objdetect.CascadeClassifier; import javax.imageio.ImageIO; import java.awt.image.BufferedImage; import java.io.File; import java.io.IOException; import static org.bytedeco.opencv.global.opencv_imgproc.*; /** * @author tarzan */ public class FaceDemo { public static void main(String[] args) throws IOException { faceDetection("C:\\Users\\Lenovo\\Desktop\\faceImg\\msk.png"); } /** * 人脸检测 * * @param filePath 图片路径 */ public static void faceDetection(String filePath) throws IOException { // 读取opencv人脸检测器 CascadeClassifier cascade = new CascadeClassifier("E:\\work_space\\reptile\\src\\main\\resources\\lbpcascade_frontalface.xml"); File file=new File(filePath); BufferedImage image = ImageIO.read(file); Java2DFrameConverter imageConverter = new Java2DFrameConverter(); Frame frame = imageConverter.convert(image); //类型转换 OpenCVFrameConverter.ToMat converter = new OpenCVFrameConverter.ToMat(); Mat original = converter.convertToMat(frame); //存放灰度图 Mat grayImg = new Mat(); //模式设置成ImageMode.Gray下不需要再做灰度 摄像头获取的是彩色图像，所以先灰度化下 cvtColor(original, grayImg, COLOR_BGRA2GRAY); // 均衡化直方图 equalizeHist(grayImg, grayImg); // 检测到的人脸 RectVector faces = new RectVector(); //多人脸检测 cascade.detectMultiScale(grayImg, faces); // 遍历人脸 for (int i = 0; i < faces.size(); i++) { Rect face_i = faces.get(i); //绘制人脸矩形区域，scalar色彩顺序：BGR(蓝绿红) rectangle(original, face_i, new Scalar(0, 255, 0, 1)); int pos_x = Math.max(face_i.tl().x() - 10, 0); int pos_y = Math.max(face_i.tl().y() - 10, 0); // 在人脸矩形上方绘制提示文字（中文会乱码） putText(original, "people face", new Point(pos_x, pos_y), FONT_HERSHEY_COMPLEX, 1.0, new Scalar(0, 0, 255, 2.0)); } frame = converter.convert(original); image = imageConverter.convert(frame); String fileName=file.getName(); String extension=fileName.substring(fileName.lastIndexOf(".")+1); String newFileName=fileName.substring(0,fileName.lastIndexOf("."))+"_result."+extension; ImageIO.write(image, extension, new File(file.getParent()+File.separator+newFileName)); } }
lbpcascade_frontalface.xml 文件内容
<?xml version="1.0"?> <!-- number of positive samples 3000 number of negative samples 1500 --> <opencv_storage> <cascade type_id="opencv-cascade-classifier"> <stageType>BOOST</stageType> <featureType>LBP</featureType> <height>24</height> <width>24</width> <stageParams> <boostType>GAB</boostType> <minHitRate>0.9950000047683716</minHitRate> <maxFalseAlarm>0.5000000000000000</maxFalseAlarm> <weightTrimRate>0.9500000000000000</weightTrimRate> <maxDepth>1</maxDepth> <maxWeakCount>100</maxWeakCount></stageParams> <featureParams> <maxCatCount>256</maxCatCount></featureParams> <stageNum>20</stageNum> <stages> <!-- stage 0 --> <_> <maxWeakCount>3</maxWeakCount> <stageThreshold>-0.7520892024040222</stageThreshold> <weakClassifiers> <!-- tree 0 --> <_> <internalNodes> 0 -1 46 -67130709 -21569 -1426120013 -1275125205 -21585 -16385 587145899 -24005</internalNodes> <leafValues> -0.6543210148811340 0.8888888955116272</leafValues></_> <!-- tree 1 --> <_> <internalNodes> 0 -1 13 -163512766 -769593758 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3</rect></_> <_> <rect> 11 5 4 6</rect></_> <_> <rect> 11 6 1 1</rect></_> <_> <rect> 11 7 2 2</rect></_> <_> <rect> 11 8 1 2</rect></_> <_> <rect> 11 10 1 1</rect></_> <_> <rect> 11 10 1 2</rect></_> <_> <rect> 11 15 1 1</rect></_> <_> <rect> 11 17 1 1</rect></_> <_> <rect> 11 18 1 1</rect></_> <_> <rect> 12 0 2 2</rect></_> <_> <rect> 12 1 2 5</rect></_> <_> <rect> 12 2 4 1</rect></_> <_> <rect> 12 3 1 3</rect></_> <_> <rect> 12 7 3 4</rect></_> <_> <rect> 12 10 3 2</rect></_> <_> <rect> 12 11 1 1</rect></_> <_> <rect> 12 12 3 2</rect></_> <_> <rect> 12 14 4 3</rect></_> <_> <rect> 12 17 1 1</rect></_> <_> <rect> 12 21 2 1</rect></_> <_> <rect> 13 6 2 5</rect></_> <_> <rect> 13 7 3 5</rect></_> <_> <rect> 13 11 3 2</rect></_> <_> <rect> 13 17 2 2</rect></_> <_> <rect> 13 17 3 2</rect></_> <_> <rect> 13 18 1 2</rect></_> <_> <rect> 13 18 2 2</rect></_> <_> <rect> 14 0 2 2</rect></_> <_> <rect> 14 1 1 3</rect></_> <_> <rect> 14 2 3 2</rect></_> <_> <rect> 14 7 2 1</rect></_> <_> <rect> 14 13 2 1</rect></_> <_> <rect> 14 13 3 3</rect></_> <_> <rect> 14 17 2 2</rect></_> <_> <rect> 15 0 2 2</rect></_> <_> <rect> 15 0 2 3</rect></_> <_> <rect> 15 4 3 2</rect></_> <_> <rect> 15 4 3 6</rect></_> <_> <rect> 15 6 3 2</rect></_> <_> <rect> 15 11 3 4</rect></_> <_> <rect> 15 13 3 2</rect></_> <_> <rect> 15 17 2 2</rect></_> <_> <rect> 15 17 3 2</rect></_> <_> <rect> 16 1 2 3</rect></_> <_> <rect> 16 3 2 4</rect></_> <_> <rect> 16 6 1 1</rect></_> <_> <rect> 16 16 2 2</rect></_> <_> <rect> 17 1 2 2</rect></_> <_> <rect> 17 1 2 5</rect></_> <_> <rect> 17 12 2 2</rect></_> <_> <rect> 18 0 2 2</rect></_></features></cascade> </opencv_storage>
生成图片（图片来源于网络）
原图
编辑
结果图
编辑
总结
javaCV功能实在是太强大了，这些只是其中的很小一部分功能，还有很多好用的功能，等待被你使用，我之前的文章中也写的好几篇javacv 视频图像的文章，感兴趣的到我主页里去看一下。
注意：未经本人允许文章禁止转载。
