人脸识别demo

examples/src/main/java/smartai/examples/face/FaceDemo.java

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+package smartai.examples.face;
+
+import cn.smartjavaai.common.entity.Rectangle;
+import cn.smartjavaai.face.FaceAlgorithm;
+import cn.smartjavaai.face.FaceAlgorithmFactory;
+import cn.smartjavaai.face.FaceDetectedResult;
+import cn.smartjavaai.face.ModelConfig;
+import com.alibaba.fastjson.JSONObject;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import smartai.examples.utils.ImageUtils;
+
+import javax.imageio.ImageIO;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+import java.io.File;
+import java.io.FileInputStream;
+import java.net.URL;
+import java.nio.file.Files;
+import java.nio.file.LinkOption;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+
+/**
+ * @author dwj
+ */
+public class FaceDemo {
+
+    // 创建 Logger 实例
+    private static final Logger logger = LoggerFactory.getLogger(FaceDemo.class);
+
+
+    public static void main(String[] args) {
+        try {
+            //detectFace();
+            //verifyIDCard();
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 人脸检测（服务端模型）
+     * 人脸模型：retinaface
+     * 特点：识别精度高，高速
+     * 应用场景：如监控摄像头、智能安防系统等需要高精度检测的场合
+     */
+    public static void detectFace() throws Exception {
+        //创建人脸算法
+        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm();
+        //使用图片路径检测
+        FaceDetectedResult result = currentAlgorithm.detect("src/main/resources/largest_selfie.jpg");
+        logger.info("人脸检测结果：{}", JSONObject.toJSONString(result));
+        //使用图片流检测
+        //File imageFile = new File("/Users/wenjie/Downloads/djl-master/examples/src/test/resources/largest_selfie.jpg");
+        //FaceDetectedResult result = currentAlgorithm.detect(new FileInputStream(imageFile));
+        File input = new File("src/main/resources/largest_selfie.jpg");
+        BufferedImage image = ImageIO.read(input);
+        //创建保存路径
+        Path imagePath = Paths.get("output").resolve("retinaface_detected.jpg");
+        //绘制人脸框
+        ImageUtils.drawBoundingBoxes(image, result, imagePath.toAbsolutePath().toString());
+    }
+
+
+    /**
+     * 人脸检测（轻量模型）
+     * 人脸模型：Ultra-Light-Fast-Generic-Face-Detector-1MB
+     * 特点：高速，准确率略低
+     * 应用场景：如监控摄像头、智能安防系统等需要高精度检测的场合
+     */
+    public static void detectFace2() throws Exception {
+        //创建轻量人脸算法
+        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createLightFaceAlgorithm();
+        //使用图片路径检测
+        FaceDetectedResult result = currentAlgorithm.detect("src/main/resources/largest_selfie.jpg");
+        logger.info("轻量人脸检测结果：{}", JSONObject.toJSONString(result));
+        //使用图片流检测
+        //File imageFile = new File("/Users/wenjie/Downloads/djl-master/examples/src/test/resources/largest_selfie.jpg");
+        //FaceDetectedResult result = currentAlgorithm.detect(new FileInputStream(imageFile));
+        File input = new File("src/main/resources/largest_selfie.jpg");
+        BufferedImage image = ImageIO.read(input);
+        //创建保存路径
+        Path imagePath = Paths.get("output").resolve("retinaface_detected.jpg");
+        //绘制人脸框
+        ImageUtils.drawBoundingBoxes(image, result, imagePath.toAbsolutePath().toString());
+    }
+
+    /**
+     * 人证核验
+     * @throws Exception
+     */
+    public static void verifyIDCard() throws Exception {
+        //创建脸算法
+        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm();
+        //提取身份证人脸特征（图片仅供测试）
+        float[] featureIdCard = currentAlgorithm.featureExtraction("src/main/resources/kana1.jpg");
+        //提取身份证人脸特征（从图片流获取）
+        //File imageFile = new File("/Users/wenjie/Downloads/djl-master/examples/src/test/resources/largest_selfie.jpg");
+        //float[] featureIdCard = currentAlgorithm.featureExtraction(new FileInputStream(imageFile));
+        logger.info("身份证人脸特征：{}", JSONObject.toJSONString(featureIdCard));
+        //提取实时人脸特征（图片仅供测试）
+        float[] realTimeFeature = currentAlgorithm.featureExtraction("src/main/resources/kana2.jpg");
+        logger.info("实时人脸特征：{}", JSONObject.toJSONString(realTimeFeature));
+        if(realTimeFeature != null){
+            if(currentAlgorithm.calculSimilar(featureIdCard, realTimeFeature) > 0.8){
+                logger.info("人脸核验通过");
+            }else{
+                logger.info("人脸核验不通过");
+            }
+        }
+    }
+
+}

examples/src/main/java/smartai/examples/utils/ImageUtils.java

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+package smartai.examples.utils;
+
+import cn.smartjavaai.face.FaceDetectedResult;
+
+import javax.imageio.ImageIO;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+import java.io.File;
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+
+/**
+ * @author dwj
+ */
+public class ImageUtils {
+
+    /**
+     * 绘制人脸框
+     * @param sourceImage
+     * @param faceDetectedResult
+     * @param savePath
+     * @throws IOException
+     */
+    public static void drawBoundingBoxes(BufferedImage sourceImage, FaceDetectedResult faceDetectedResult,String savePath) throws IOException {
+        Graphics2D graphics = sourceImage.createGraphics();
+        graphics.setColor(Color.RED);// 边框颜色
+        graphics.setStroke(new BasicStroke(2));   // 线宽2像素
+        graphics.setRenderingHint(RenderingHints.KEY_ANTIALIASING,
+                RenderingHints.VALUE_ANTIALIAS_ON); // 抗锯齿
+        int stroke = 2;
+        for(cn.smartjavaai.common.entity.Rectangle rectangle : faceDetectedResult.getRectangles()){
+            graphics.setColor(Color.RED);// 边框颜色
+            graphics.drawRect(rectangle.getPointList().get(0).getX(),
+                    rectangle.getPointList().get(0).getY(), rectangle.getWidth(),  rectangle.getHeight());
+            drawText(graphics, "face", rectangle.getPointList().get(0).getX(), rectangle.getPointList().get(0).getY(), stroke, 4);
+        }
+        graphics.dispose();
+        ImageIO.write(sourceImage, "jpg", new File(savePath));
+
+    }
+
+    private static void drawText(Graphics2D g, String text, int x, int y, int stroke, int padding) {
+        FontMetrics metrics = g.getFontMetrics();
+        x += stroke / 2;
+        y += stroke / 2;
+        int width = metrics.stringWidth(text) + padding * 2 - stroke / 2;
+        int height = metrics.getHeight() + metrics.getDescent();
+        int ascent = metrics.getAscent();
+        java.awt.Rectangle background = new java.awt.Rectangle(x, y, width, height);
+        g.fill(background);
+        g.setPaint(Color.WHITE);
+        g.drawString(text, x + padding, y + ascent);
+    }
+}

examples/src/main/resources/logback.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<!-- 步骤2: 配置文件 (src/main/resources/logback.xml) -->
+<configuration scan="true" scanPeriod="30 seconds">
+    <!-- 控制台日志输出 -->
+    <appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
+        <encoder>
+            <pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %highlight(%-5level) %cyan(%logger{36}) - %msg%n</pattern>
+        </encoder>
+    </appender>
+
+    <root level="INFO">
+        <appender-ref ref="CONSOLE" />
+    </root>
+</configuration>