集成算法seetaface6

2026-09-10 03:28:49 +00:00 · 2025-03-26 17:09:22 +08:00
parent 45cb7a9edc
commit 72a4c2c058
78 changed files with 1843 additions and 264 deletions
--- a/examples/face_offline.md
+++ b/examples/face_offline.md
@@ -1,99 +0,0 @@
-# SmartJavaAI离线下载模型案例
-
-**SmartJavaAI**如果未指定模型地址，系统将自动下载模型至本地。因此，无论模型是否通过离线方式下载，SmartJavaAI 最终都会在离线环境下运行模型。
-
-### 1. 安装人脸算法依赖
-
-在 Maven 项目的 `pom.xml` 中添加 SmartJavaAI的人脸算法依赖：
-
-```xml
-<dependencies>
-     <dependency>
-        <groupId>ink.numberone</groupId>
-        <artifactId>smartjavaai-face</artifactId>
-        <version>1.0.4</version>
-     </dependency>
-</dependencies>
-```
-
-### 2. 下载模型
-
-|         模型名称          |                           下载地址                           | 文件大小 |    适用场景    |
-| :-----------------------: | :----------------------------------------------------------: | :------: | :------------: |
-|        retinaface         | [下载](https://resources.djl.ai/test-models/pytorch/retinaface.zip) |  110MB   | 高精度人脸检测 |
-| ultralightfastgenericface | [下载](https://resources.djl.ai/test-models/pytorch/ultranet.zip) |  1.7MB   |  高速人脸检测  |
-|     featureExtraction     | [下载](https://resources.djl.ai/test-models/pytorch/face_feature.zip) |  104MB   |  人脸特征提取  |
-
-### 3. 人脸检测代码示例（离线下载模型）
-
-```java
-// 初始化配置
-ModelConfig config = new ModelConfig();
-config.setAlgorithmName("retinaface");//人脸算法模型，目前支持：retinaface及ultralightfastgenericface
-//config.setAlgorithmName("ultralightfastgenericface");//轻量模型
-config.setConfidenceThreshold(FaceConfig.DEFAULT_CONFIDENCE_THRESHOLD);//置信度阈值
-config.setMaxFaceCount(FaceConfig.MAX_FACE_LIMIT);//每张特征图保留的最大候选框数量
-//nms阈值:控制重叠框的合并程度,取值越低，合并越多重叠框（减少误检但可能漏检）；取值越高，保留更多框（增加检出但可能引入冗余）
-config.setNmsThresh(FaceConfig.NMS_THRESHOLD);
-//模型下载地址：
-//retinaface: https://resources.djl.ai/test-models/pytorch/retinaface.zip
-//ultralightfastgenericface: https://resources.djl.ai/test-models/pytorch/ultranet.zip
-//改为模型存放路径
-config.setModelPath("/Users/xxx/Documents/develop/face_model/retinaface.pt");
-//创建人脸算法
-FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
-//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 input = new File("src/main/resources/largest_selfie.jpg");
-//FaceDetectedResult result = currentAlgorithm.detect(new FileInputStream(input));
-//logger.info("人脸检测结果：{}", JSONObject.toJSONString(result));
-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());
-```
-
-### 4. 人证核验示例（离线下载模型）
-
-人证核验步骤：
-
-（1）提取身份证人脸特征，
-
-（2）提取实时人脸特征
-
-（3）特征比对
-
-```java
-// 初始化配置
-ModelConfig config = new ModelConfig();
-config.setAlgorithmName("featureExtraction");
-//模型下载地址：https://resources.djl.ai/test-models/pytorch/face_feature.zip
-//改为模型存放路径
-config.setModelPath("/Users/xxx/Documents/develop/face_model/face_feature.pt");
-//创建脸算法
-FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceFeatureAlgorithm(config);
-//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 input = new File("src/main/resources/kana1.jpg");
-//float[] featureIdCard = currentAlgorithm.featureExtraction(new FileInputStream(input));
-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");
-    }
-}
-```
-
-## 完整代码
-
-`📁 examples/src/main/java/smartai/examples/face`  
- └── 📄[FaceDemo.java](https://github.com/geekwenjie/SmartJavaAI/blob/master/examples/src/main/java/smartai/examples/face/FaceDemo.java)  <sub>*（基于JDK11构建的完整可执行示例）*</sub>
--- a/examples/output/retinaface_detected.jpg
+++ b/examples/output/retinaface_detected.jpg
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -43,7 +43,7 @@
        <dependency>
            <groupId>ink.numberone</groupId>
            <artifactId>smartjavaai-face</artifactId>
-            <version>1.0.4</version>
+            <version>1.0.5</version>
        </dependency>

        <dependency>
@@ -62,6 +62,54 @@
            <artifactId>fastjson</artifactId>
            <version>1.2.83</version>
        </dependency>
+
+        <dependency>
+            <groupId>ai.djl.onnxruntime</groupId>
+            <artifactId>onnxruntime-engine</artifactId>
+            <version>0.20.0</version>
+        </dependency>
    </dependencies>

+    <build>
+        <finalName>example</finalName>
+        <plugins>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-assembly-plugin</artifactId>
+                <version>2.3</version>
+                <configuration>
+                    <!--如果不想在打包的后缀加上assembly.xml中设置的id，可以加上下面的配置-->
+                    <appendAssemblyId>false</appendAssemblyId>
+                    <descriptorRefs>
+                        <descriptorRef>jar-with-dependencies</descriptorRef>
+                    </descriptorRefs>
+                    <archive>
+                        <manifest>
+                            <!-- 是否绑定依赖，将外部jar包依赖加入到classPath中 -->
+                            <addClasspath>true</addClasspath>
+                            <!-- 依赖前缀，与之前设置的文件夹路径要匹配 -->
+                            <classpathPrefix>lib/</classpathPrefix>
+                            <!-- 执行的主程序入口 -->
+                            <mainClass>smartai.examples.face.FaceDemo</mainClass>
+                        </manifest>
+                    </archive>
+                </configuration>
+                <executions>
+                    <execution>
+                        <id>make-assembly</id>
+                        <!--绑定的maven操作-->
+                        <phase>package</phase>
+                        <goals>
+                            <goal>assembly</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+        </plugins>
+    </build>
+
+
+
+
+
 </project>
--- a/examples/src/main/java/smartai/examples/face/FaceDemo.java
+++ b/examples/src/main/java/smartai/examples/face/FaceDemo.java
@@ -2,7 +2,9 @@ package smartai.examples.face;

 import cn.smartjavaai.common.entity.Rectangle;
 import cn.smartjavaai.face.*;
+import cn.smartjavaai.face.entity.FaceResult;
 import com.alibaba.fastjson.JSONObject;
+import lombok.extern.slf4j.Slf4j;
 import org.apache.commons.lang3.time.StopWatch;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
@@ -22,14 +24,13 @@ import java.nio.file.Paths;
 /**
 * @author dwj
 */
+@Slf4j
 public class FaceDemo {

-    private static final Logger logger = LoggerFactory.getLogger(FaceDemo.class);
-

    public static void main(String[] args) {
        try {
-            verifyIDCard();
+            featureComparison();
            //detectFace2();
            //verifyIDCard();
        } catch (Exception e) {
@@ -49,18 +50,18 @@ public class FaceDemo {
        //创建人脸算法
        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm();
        sw.stop();
-        logger.info("创建人脸算法耗时：" + sw.getTime() + "ms");
+        log.info("创建人脸算法耗时：" + sw.getTime() + "ms");
        sw.reset();
        sw.start();
        //使用图片路径检测
        FaceDetectedResult result = currentAlgorithm.detect("src/main/resources/largest_selfie.jpg");
        sw.stop();
-        logger.info("人脸检测耗时：" + sw.getTime() + "ms");
-        logger.info("人脸检测结果：{}", JSONObject.toJSONString(result));
+        log.info("人脸检测耗时：" + sw.getTime() + "ms");
+        log.info("人脸检测结果：{}", JSONObject.toJSONString(result));
        //使用图片流检测
        File input = new File("src/main/resources/largest_selfie.jpg");
        //FaceDetectedResult result = currentAlgorithm.detect(new FileInputStream(input));
-        //logger.info("人脸检测结果：{}", JSONObject.toJSONString(result));
+        //log.info("人脸检测结果：{}", JSONObject.toJSONString(result));
        BufferedImage image = ImageIO.read(input);
        //创建保存路径
        Path imagePath = Paths.get("output").resolve("retinaface_detected.jpg");
@@ -81,14 +82,14 @@ public class FaceDemo {
        //创建轻量人脸算法
        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createLightFaceAlgorithm();
        sw.stop();
-        logger.info("创建人脸算法耗时：" + sw.getTime() + "ms");
+        log.info("创建人脸算法耗时：" + sw.getTime() + "ms");
        sw.reset();
        sw.start();
        //使用图片路径检测
        FaceDetectedResult result = currentAlgorithm.detect("src/main/resources/largest_selfie.jpg");
        sw.stop();
-        logger.info("人脸检测耗时：" + sw.getTime() + "ms");
-        logger.info("轻量人脸检测结果：{}", JSONObject.toJSONString(result));
+        log.info("人脸检测耗时：" + sw.getTime() + "ms");
+        log.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));
@@ -100,39 +101,7 @@ public class FaceDemo {
        ImageUtils.drawBoundingBoxes(image, result, imagePath.toAbsolutePath().toString());
    }

-    /**
-     * 人证核验
-     * @throws Exception
-     */
-    public static void verifyIDCard() throws Exception {
-        // 创建并启动计时器
-        StopWatch sw = StopWatch.createStarted();
-        //创建脸算法
-        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceFeatureAlgorithm();
-        sw.stop();
-        logger.info("创建人脸算法耗时：" + sw.getTime() + "ms");
-        sw.reset();
-        sw.start();
-        //提取身份证人脸特征（图片仅供测试）
-        float[] featureIdCard = currentAlgorithm.featureExtraction("src/main/resources/MJ_20250213_155245.png");
-        sw.stop();
-        logger.info("人脸特征提取耗时：" + sw.getTime() + "ms");
-        //提取身份证人脸特征（从图片流获取）
-        //File input = new File("src/main/resources/kana1.jpg");
-        //float[] featureIdCard = currentAlgorithm.featureExtraction(new FileInputStream(input));
-        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/MJ_20250213_155228.png");
-        logger.info("实时人脸特征：{}", JSONObject.toJSONString(realTimeFeature));
-        if(realTimeFeature != null){
-            System.out.println("相似度：" + currentAlgorithm.calculSimilar(featureIdCard, realTimeFeature));
-            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");
-            }
-        }
-    }
+

    /**
     * 人脸检测（离线模型）
@@ -143,7 +112,7 @@ public class FaceDemo {
    public static void detectFaceOffine() throws Exception {
        // 初始化配置
        ModelConfig config = new ModelConfig();
-        config.setAlgorithmName("retinaface");//人脸算法模型，目前支持：retinaface及ultralightfastgenericface
+        config.setAlgorithmName("retinaface");//人脸算法模型，目前支持：retinaface/ultralightfastgenericface/seetaface6
        //config.setAlgorithmName("ultralightfastgenericface");//轻量模型
        config.setConfidenceThreshold(FaceConfig.DEFAULT_CONFIDENCE_THRESHOLD);//置信度阈值
        config.setMaxFaceCount(FaceConfig.MAX_FACE_LIMIT);//每张特征图保留的最大候选框数量
@@ -158,7 +127,7 @@ public class FaceDemo {
        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
        //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));
+        log.info("人脸检测结果：{}", JSONObject.toJSONString(result));
        //使用图片流检测
        File input = new File("src/main/resources/largest_selfie.jpg");
        //FaceDetectedResult result = currentAlgorithm.detect(new FileInputStream(input));
@@ -171,34 +140,113 @@ public class FaceDemo {
    }

    /**
-     * 人证核验(离线模型)
+     * 人脸比对（1：1）
     * @throws Exception
     */
-    public static void verifyIDCardOffine() throws Exception {
-        // 初始化配置
-        ModelConfig config = new ModelConfig();
-        config.setAlgorithmName("featureExtraction");
-        //模型下载地址：https://resources.djl.ai/test-models/pytorch/face_feature.zip
-        //改为模型存放路径
-        config.setModelPath("/Users/xxx/Documents/develop/face_model/face_feature.pt");
-        //创建脸算法
-        FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceFeatureAlgorithm(config);
-        //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 input = new File("src/main/resources/kana1.jpg");
-        //float[] featureIdCard = currentAlgorithm.featureExtraction(new FileInputStream(input));
-        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");
-            }
+    public static void featureComparison(){
+        try {
+            // 初始化配置
+            ModelConfig config = new ModelConfig();
+            config.setAlgorithmName("seetaface6");//目前支持人脸比对的算法只有：seetaface6
+            //人脸库路径 如果不指定人脸库，无法使用 1:N人脸搜索
+            config.setFaceDbPath("C:/Users/Administrator/Downloads/faces-data.db");
+            //改为模型存放路径
+            config.setModelPath("/opt/sf3.0_models");
+            //创建人脸算法
+            FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
+            //自动裁剪人脸并比对人脸特征
+            float similar = currentAlgorithm.featureComparison("src/main/resources/kana1.jpg","src/main/resources/kana2.jpg");
+            log.info("相似度：{}", similar);
+        }
+        catch (Exception e){
+            e.printStackTrace();
        }
    }

+    /**
+     * 人脸特征提取及比对
+     */
+    public static void featureExtractionAndCompare(){
+        try {
+            // 初始化配置
+            ModelConfig config = new ModelConfig();
+            config.setAlgorithmName("seetaface6");
+            //人脸库路径 如果不指定人脸库，无法使用 1:N人脸搜索
+            config.setFaceDbPath("C:/Users/Administrator/Downloads/faces-data.db");
+            //改为模型存放路径
+            config.setModelPath("C:/Users/Administrator/Downloads/sf3.0_models/sf3.0_models");
+            //创建人脸算法
+            FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
+            //提取图像中最大人脸的特征
+            float[] feature1 = currentAlgorithm.featureExtraction("src/main/resources/kana1.jpg");
+            float[] feature2 = currentAlgorithm.featureExtraction("src/main/resources/kana2.jpg");
+            float similar = currentAlgorithm.calculSimilar(feature1, feature2);
+            log.info("相似度：{}", similar);
+        }
+        catch (Exception e){
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 注册人脸及搜索人脸（1：N）
+     */
+    public static void registerAndSearchFace(){
+        try {
+            // 初始化配置
+            ModelConfig config = new ModelConfig();
+            config.setAlgorithmName("seetaface6");
+            //人脸库路径 如果不指定人脸库，无法使用 1:N人脸搜索
+            config.setFaceDbPath("C:/Users/Administrator/Downloads/faces-data.db");
+            //改为模型存放路径
+            config.setModelPath("C:/Users/Administrator/Downloads/sf3.0_models/sf3.0_models");
+            //创建人脸算法 自动将人脸库加载到内存中
+            FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
+            //等待人脸库加载完毕
+            Thread.sleep(1000);
+            //注册kana1人脸，参数key建议设置为人名
+            boolean isSuccss = currentAlgorithm.register("kana1","src/main/resources/kana1.jpg");
+            //注册jsy人脸，参数key建议设置为人名
+            isSuccss = currentAlgorithm.register("jsy","src/main/resources/jsy.jpg");
+            FaceResult faceResult = currentAlgorithm.search("src/main/resources/kana2.jpg");
+            if(faceResult != null){
+                log.info("查询到人脸：{}", faceResult.toString());
+            }else{
+                log.info("未查询到人脸");
+            }
+
+        }
+        catch (Exception e){
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 删除已注册人脸
+     */
+    public static void removeRegisterFace(){
+        try {
+            // 初始化配置
+            ModelConfig config = new ModelConfig();
+            config.setAlgorithmName("seetaface6");
+            //人脸库路径 如果不指定人脸库，无法使用 1:N人脸搜索
+            config.setFaceDbPath("C:/Users/Administrator/Downloads/faces-data.db");
+            //改为模型存放路径
+            config.setModelPath("C:/Users/Administrator/Downloads/sf3.0_models/sf3.0_models");
+            //创建人脸算法 自动将人脸库加载到内存中
+            FaceAlgorithm currentAlgorithm = FaceAlgorithmFactory.createFaceAlgorithm(config);
+            //等待人脸库加载完毕
+            Thread.sleep(1000);
+            //使用注册人脸时的key值删除，可一次性删除单个
+            long num = currentAlgorithm.removeRegister("kana1");
+            //删除全部人脸
+            //long num = currentAlgorithm.clearFace();
+            log.info("删除成功数量：" + num);
+        }
+        catch (Exception e){
+            e.printStackTrace();
+        }
+    }
+
+
 }
--- a/examples/src/main/java/smartai/examples/utils/ImageUtils.java
+++ b/examples/src/main/java/smartai/examples/utils/ImageUtils.java
@@ -48,7 +48,7 @@ public class ImageUtils {
        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);
+        Rectangle background = new Rectangle(x, y, width, height);
        g.fill(background);
        g.setPaint(Color.WHITE);
        g.drawString(text, x + padding, y + ascent);
--- a/examples/src/main/resources/jsy.jpg
+++ b/examples/src/main/resources/jsy.jpg