Java基于百度AI+JavaCV+OpenCV 实现摄像头人数动态统计

【Java】人流量统计-动态版之视频转图识别请访问 http://ai.baidu.com/forum/topic/show/940413

本文是基于上一篇进行迭代的。本文主要是以摄像头画面进行人流量统计。并对返回图像进行展示。需要额外了解JavaCV OpenCV swing awt等

也许JavaCV OpenCV 不需要也可以实现效果。但是小帅丶就先用这样的方式实现了。别的方式大家就自己尝试吧

有可能显示的in out不对。请设置帧率试试。鄙人不是专业的。所以对帧率也不是很懂。以下代码加入也没有明显的变化。

grabber.setFrameRate(10);
grabber.setFrameNumber(10);

项目代码地址 https://gitee.com/xshuai/bodyTrack

注意的问题

1.动态识别的area参数为矩阵的4个顶点的xy坐标(即像素) 顺序是上左下右也就是顺时针一圈4个点的坐标点 2.case_id 为int 请不要给大于int范围的值。或非int类型的值即正整数就行 3.area的值不要大于图片本身的宽高
需要用到的jar 通过maven引入(下载的jar较多。需要等待较长时间)
UTF-8 1.8 1.8 3.2.1-1.3 1.4.1
org.bytedeco.javacpp-presets ffmpeg-platform ${ffmpeg.version} com.alibaba fastjson 1.2.35 org.bytedeco javacv ${javacv.version}
```
<dependency>
    <groupId>org.bytedeco.javacpp-presets</groupId>
    <artifactId>opencv-platform</artifactId>
    <version>3.4.1-1.4.1</version>
</dependency>
```
需要用到的Java工具类

HttpUtil https://ai.baidu.com/file/544D677F5D4E4F17B4122FBD60DB82B3

调用接口示例代码(需要自己的电脑有摄像头哦)

import java.awt.image.BufferedImage; import java.awt.image.DataBufferByte; import java.awt.image.WritableRaster; import java.io.ByteArrayInputStream; import java.io.ByteArrayOutputStream; import java.io.FileOutputStream; import java.io.OutputStream; import java.net.URLEncoder; import java.util.Base64; import java.util.Base64.Decoder; import java.util.Base64.Encoder;

import javax.imageio.ImageIO; import javax.swing.JFrame;

import org.bytedeco.javacpp.BytePointer; import org.bytedeco.javacpp.opencv_core.IplImage; import org.bytedeco.javacv.CanvasFrame; import org.bytedeco.javacv.Frame; import org.bytedeco.javacv.Java2DFrameConverter; import org.bytedeco.javacv.OpenCVFrameConverter; import org.bytedeco.javacv.OpenCVFrameConverter.ToIplImage; import org.bytedeco.javacv.OpenCVFrameGrabber;

import com.alibaba.fastjson.JSONObject;

import cn.xsshome.body.util.HttpUtil; /**

获取摄像头画面进行处理并回显图片在画面中
人流量统计（动态版）JavaAPI示例代码
@author 小帅丶

*/ public class JavavcCameraTest {

static OpenCVFrameConverter.ToIplImage converter = new OpenCVFrameConverter.ToIplImage();
//人流量统计（动态版）接口地址
private static String BODY_TRACKING_URL="https://aip.baidubce.com/rest/2.0/image-classify/v1/body_tracking";

private static String ACCESS_TOKEN ="";//接口的token
/**
 * 每个case的初始化信号，为true时对该case下的跟踪算法进行初始化，为false时重载该case的跟踪状态。当为false且读取不到相应case的信息时，直接重新初始化
 * caseId=0 第一次请求  case_init=true  caseId>0 非第一次请求  case_init=false
 */
static int caseId = 0;
public static void main(String[] args) throws Exception,
        InterruptedException {
    OpenCVFrameGrabber grabber = new OpenCVFrameGrabber(0);
    grabber.start(); // 开始获取摄像头数据
    CanvasFrame canvas = new CanvasFrame("人流量实时统计");// 新建一个窗口
    canvas.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    canvas.setAlwaysOnTop(true);
    int ex = 0;
    while (true) {
        if (!canvas.isDisplayable()) {// 窗口是否关闭
            grabber.stop();// 停止抓取
            System.exit(2);// 退出
            grabber.close();
        }
        // canvas.showImage(grabber.grab());//显示摄像头抓取的画面
        Java2DFrameConverter java2dFrameConverter = new Java2DFrameConverter();
        // 摄像头抓取的画面转BufferedImage
        BufferedImage bufferedImage = java2dFrameConverter.getBufferedImage(grabber.grabFrame());
        // bufferedImage 请求API接口 检测人流量
        String result = getBodyTrack(bufferedImage);
        BufferedImage bufferedImageAPI = getAPIResult(result);
        // 如果识别为空 则显示摄像头抓取的画面
        if (null == bufferedImageAPI) {
            canvas.showImage(grabber.grab());
        } else {
            // BufferedImage转IplImage
            IplImage iplImageAPI = BufImgToIplData(bufferedImageAPI);
            // 将IplImage转为Frame 并显示在窗口中
            Frame convertFrame = converter.convert(iplImageAPI);
            canvas.showImage(convertFrame);
        }
        ex++;

// Thread.sleep(100);// 100毫秒刷新一次图像.因为接口返回需要时间。所以看到的画面还是会有一定的延迟 } } /** * BufferedImage转IplImage * @param bufferedImageAPI * @return / private static IplImage BufImgToIplData(BufferedImage bufferedImageAPI) { IplImage iplImage = null; ToIplImage iplConverter = new OpenCVFrameConverter.ToIplImage(); Java2DFrameConverter java2dConverter = new Java2DFrameConverter(); iplImage = iplConverter.convert(java2dConverter.convert(bufferedImageAPI)); return iplImage; } /* * IplImage 转 BufferedImage * @param mat * @return BufferedImage / public static BufferedImage iplToBufImgData(IplImage mat) { if (mat.height() > 0 && mat.width() > 0) { //TYPE_3BYTE_BGR 表示一个具有 8 位 RGB 颜色分量的图像，对应于 Windows 风格的 BGR 颜色模型，具有用 3 字节存储的 Blue、Green 和 Red 三种颜色。 BufferedImage image = new BufferedImage(mat.width(), mat.height(),BufferedImage.TYPE_3BYTE_BGR); WritableRaster raster = image.getRaster(); DataBufferByte dataBuffer = (DataBufferByte) raster.getDataBuffer(); byte[] data = dataBuffer.getData(); BytePointer bytePointer = new BytePointer(data); mat.imageData(bytePointer); return image; } return null; } /* * 接口结果转bufferimage * @param result * @return BufferedImage * @throws Exception */ private static BufferedImage getAPIResult(String result) throws Exception { JSONObject object = JSONObject.parseObject(result); BufferedImage bufferedImage = null; if(object.getInteger("person_num")>=1){ Decoder decoder = Base64.getDecoder(); byte [] b = decoder.decode(object.getString("image")); ByteArrayInputStream in = new ByteArrayInputStream(b);
bufferedImage = ImageIO.read(in);

        ByteArrayOutputStream baos = new ByteArrayOutputStream(); 
        ImageIO.write(bufferedImage,"jpg", baos); 
         byte[] imageInByte = baos.toByteArray(); 
        // Base64解码
        for (int i = 0; i < imageInByte.length; ++i) {
            if (imageInByte[i] < 0) {// 调整异常数据
                imageInByte[i] += 256;
            }
         }
         OutputStream out = new FileOutputStream("G:/testimg/xiaoshuairesult.jpg");//接口返回的渲染图
         out.write(imageInByte);
         out.flush();
         out.close();
        return bufferedImage;
    }else{
        return null;
    }
}
/**
 * 获取接口处理结果图
 * @param bufferedImage
 * @return String
 * @throws Exception
 */
public static String getBodyTrack(BufferedImage bufferedImage) throws Exception{
     ByteArrayOutputStream baos = new ByteArrayOutputStream(); 
     ImageIO.write(bufferedImage,"jpg",baos); 
     byte[] imageInByte = baos.toByteArray(); 
     Encoder base64 = Base64.getEncoder();
     String imageBase64 = base64.encodeToString(imageInByte);
    // Base64解码
    for (int i = 0; i < imageInByte.length; ++i) {
        if (imageInByte[i] < 0) {// 调整异常数据
            imageInByte[i] += 256;
        }
     }
     // 生成jpeg图片
     OutputStream out = new FileOutputStream("G:/testimg/xiaoshuai.jpg");// 新生成的图片
     out.write(imageInByte);
     out.flush();
     out.close();
     System.out.println("保存成功");  
     baos.flush();       
     baos.close();
     String access_token = ACCESS_TOKEN;
            String case_id = "2018";
     String case_init = "";
     String area = "10,10,630,10,630,470,10,469";
     String params = "";
     if(caseId==0){
        case_init = "true";
        params = "image=" + URLEncoder.encode(imageBase64, "utf-8")
                 + "&dynamic=true&show=true&case_id=" + case_id
                 + "&case_init="+case_init +"&area="+area;
     }else{
         case_init = "false";
         params = "image=" + URLEncoder.encode(imageBase64, "utf-8")
                 + "&dynamic=true&show=true&case_id=" + case_id
                 + "&case_init="+case_init +"&area="+area; 
     }
     //静态识别

// String params = "image=" + URLEncoder.encode(imageBase64, "utf-8")+"&dynamic=false&show=true"; String result = HttpUtil.post(BODY_TRACKING_URL, access_token, params); System.out.println("接口内容==>"+result); return result; } /** * IplImage 转 BufferedImage * @param mat * @return BufferedImage */ public static BufferedImage bufferimgToBase64(IplImage mat) { if (mat.height() > 0 && mat.width() > 0) { BufferedImage image = new BufferedImage(mat.width(), mat.height(),BufferedImage.TYPE_3BYTE_BGR); WritableRaster raster = image.getRaster(); DataBufferByte dataBuffer = (DataBufferByte) raster.getDataBuffer(); byte[] data = dataBuffer.getData(); BytePointer bytePointer = new BytePointer(data); mat.imageData(bytePointer); return image; } return null; } }