JavaCV 实现图片中人脸检测完整代码教程
Posted 洛阳泰山
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目录
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 -->
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