JavaCV 实现图片中人脸检测完整代码教程

我会带着你远行 2024-04-01 16:11 96阅读 0赞

##  ##

**目录**

前言

一、javaCV是什么？

二、使用步骤

1.引入库

2.代码教程

--------------------

## 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

<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"?>
    
    <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>
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生成图片（图片来源于网络）

原图

![a16af131ac8a4bf69a8ca543b036bc6e.png][]

结果图

![d9fca2fa71bf4f62a338f60d00adcf5c.png][]

--------------------

## **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。

## 相关知识 ##

JavaCV是一个基于OpenCV和FFmpeg的Java开发库，它提供了在Java应用程序中使用计算机视觉和多媒体处理的功能。下面将详细解释JavaCV的特点和用法。

1.  特点：
    
     *  基于OpenCV和FFmpeg：JavaCV集成了OpenCV和FFmpeg等流行的计算机视觉和多媒体处理库，使得在Java中使用这些功能变得更加便捷。
     *  跨平台支持：JavaCV可以在多个操作系统上运行，包括Windows、Linux和macOS等。
     *  多样的功能：JavaCV提供了广泛的计算机视觉和多媒体处理功能，如图像处理、视频处理、特征提取、人脸识别等。
     *  友好的API：JavaCV提供了简单易用的API，使得开发人员能够轻松地使用计算机视觉和多媒体处理功能。
     *  并发性能优化：JavaCV通过并发处理来提高性能，利用多线程和GPU加速等技术来加快图像和视频处理速度。
2.  用法：
    
     *  安装和配置：下载JavaCV的JAR文件，并将其添加到Java项目的类路径中。根据需要，还需要安装对应平台的OpenCV和FFmpeg库。
     *  导入库和类：在Java代码中导入相关的类和方法。
     *  使用功能：根据需要，使用JavaCV提供的类和方法来实现各种计算机视觉和多媒体处理功能。例如，图像处理可以使用**`opencv_core`**包中的类和方法，视频处理可以使用**`javacv_ffmpeg`**包中的类和方法。
    
    示例代码
    
        import org.bytedeco.ffmpeg.global.avcodec;
        import org.bytedeco.javacv.FFmpegFrameGrabber;
        import org.bytedeco.opencv.global.opencv_core;
        import org.bytedeco.opencv.opencv_core.Mat;
        
        public class JavaCVExample {
            public static void main(String[] args) {
                String videoFile = "input.mp4";
        
                try (FFmpegFrameGrabber grabber = new FFmpegFrameGrabber(videoFile)) {
                    grabber.start();
                    Mat frame;
                    while ((frame = grabber.grabFrame()) != null) {
                        // 对每一帧进行处理...
                        opencv_core.flip(frame, frame, 1);
                    }
                    grabber.stop();
                } catch (Exception e) {
                    e.printStackTrace();
                }
            }
        }
    
    在上述示例中，我们使用JavaCV读取名为`input.mp4`的视频文件，并对每一帧进行处理（这里是简单地水平翻转）。通过导入相关的类和方法，我们可以直接使用JavaCV提供的功能。

总结： JavaCV是一个强大的Java开发库，它基于OpenCV和FFmpeg等计算机视觉和多媒体处理库，为Java应用程序提供了丰富的功能。通过JavaCV，开发人员可以轻松地在Java中使用计算机视觉和多媒体处理技术。希望以上内容对您有所帮助，如有任何疑问，请随时提问。

注意：未经本人允许文章禁止转载。

[a16af131ac8a4bf69a8ca543b036bc6e.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/01/5b3a6dd507b644b5ae8cd8cefe812d5a.png
[d9fca2fa71bf4f62a338f60d00adcf5c.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/01/99c5e1a999f24a218713ebd5ead6aa1a.png