新增目标检测功能

smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModelFactory.java

@@ -0,0 +1,127 @@
+package cn.smartjavaai.face;
+
+import cn.smartjavaai.face.exception.FaceException;
+import cn.smartjavaai.face.model.FeatureExtractionModel;
+import cn.smartjavaai.face.model.RetinaFaceModel;
+import cn.smartjavaai.face.model.SeetaFace6Model;
+import cn.smartjavaai.face.model.UltraLightFastGenericFaceModel;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.Map;
+import java.util.Objects;
+import java.util.concurrent.ConcurrentHashMap;
+
+/**
+ * 人脸算法工厂
+ * @author dwj
+ */
+@Slf4j
+public class FaceModelFactory {
+
+    // 使用 volatile 和双重检查锁定来确保线程安全的单例模式
+    private static volatile FaceModelFactory instance;
+
+    private static final ConcurrentHashMap<String, FaceModel> modelMap = new ConcurrentHashMap<>();
+
+    /**
+     * 算法注册表
+     */
+    private static final Map<String, Class<? extends FaceModel>> registry =
+            new ConcurrentHashMap<>();
+
+
+    public static FaceModelFactory getInstance() {
+        if (instance == null) {
+            synchronized (FaceModelFactory.class) {
+                if (instance == null) {
+                    instance = new FaceModelFactory();
+                }
+            }
+        }
+        return instance;
+    }
+
+
+
+    /**
+     * 注册算法
+     * @param name
+     * @param clazz
+     */
+    private static void registerAlgorithm(String name, Class<? extends FaceModel> clazz) {
+        registry.put(name.toLowerCase(), clazz);
+    }
+
+
+    /**
+     * 获取模型（通过配置）
+     * @param config
+     * @return
+     */
+    public FaceModel getModel(FaceModelConfig config) {
+        if(Objects.isNull(config) || Objects.isNull(config.getModelEnum())){
+            throw new FaceException("未配置人脸模型");
+        }
+        return modelMap.computeIfAbsent(config.getModelEnum().name(), k -> {
+            return createFaceModel(config);
+        });
+    }
+
+    /**
+     * 获取默认模型
+     * @return
+     */
+    public FaceModel getModel() {
+        // 初始化默认配置
+        FaceModelConfig config = new FaceModelConfig();
+        config.setModelEnum(FaceModelEnum.RETINA_FACE);
+        config.setConfidenceThreshold(FaceConfig.DEFAULT_CONFIDENCE_THRESHOLD);
+        config.setNmsThresh(FaceConfig.NMS_THRESHOLD);
+        return getModel(config);
+    }
+
+    /**
+     * 使用ModelConfig创建算法
+     * @param config
+     * @return
+     */
+    private FaceModel createFaceModel(FaceModelConfig config) {
+        Class<?> clazz = registry.get(config.getModelEnum().getModelClassName().toLowerCase());
+        if(clazz == null){
+            throw new FaceException("Unsupported algorithm");
+        }
+        FaceModel algorithm = null;
+        try {
+            algorithm = (FaceModel) clazz.newInstance();
+        } catch (InstantiationException | IllegalAccessException e) {
+            throw new FaceException(e);
+        }
+        algorithm.loadModel(config);
+        return algorithm;
+    }
+
+
+    /**
+     * 获取轻量级人脸模型
+     * @return
+     */
+    public FaceModel getLightFaceModel() {
+        // 初始化默认配置
+        FaceModelConfig config = new FaceModelConfig();
+        config.setModelEnum(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE);
+        config.setConfidenceThreshold(FaceConfig.DEFAULT_CONFIDENCE_THRESHOLD);
+        config.setNmsThresh(FaceConfig.NMS_THRESHOLD);
+        return getModel(config);
+    }
+
+
+    // 初始化默认算法
+    static {
+        registerAlgorithm("retinafacemodel", RetinaFaceModel.class);
+        registerAlgorithm("ultralightfastgenericfacemodel", UltraLightFastGenericFaceModel.class);
+        //人脸特征提取
+        registerAlgorithm("featureextractionmodel", FeatureExtractionModel.class);
+        registerAlgorithm("seetaface6model", SeetaFace6Model.class);
+    }
+
+}