1、人脸模块：新增小视科技（MiniVision）活体检测模型

2、人脸模块：新增阿里通义工作室活体检测模型
3、人脸模块：新增2个表情识别模型
4、人脸模块：新增InsightFace、ElasticFace人脸识别模型
5、人脸模块：新增Seetaface6质量评估模型
6、目标检测模块：开放更多自定义模型参数
7、人脸模块：支持base64图片
8、实现接口 AutoCloseable，支持资源的自动释放
9、OCR模块：解决加方向矫正后无法连续识别bug
10、人脸模块：解决人脸更新后缓存问题
11、优化部分功能

smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/config/DetectorModelConfig.java

@@ -5,6 +5,9 @@ import cn.smartjavaai.objectdetection.constant.DetectorConstant;
 import cn.smartjavaai.objectdetection.enums.DetectorModelEnum;
 import lombok.Data;
 
+import java.util.HashMap;
+import java.util.Map;
+
 /**
  * 目标检测模型参数配置
  *
@@ -41,6 +44,11 @@ public class DetectorModelConfig {
      */
     private int maxBox;
 
+    /**
+     * 个性化配置
+     */
+    private Map<String, Object> customParams = new HashMap<>();
+
     public DetectorModelConfig() {
     }
 
@@ -52,4 +60,20 @@ public class DetectorModelConfig {
     public DetectorModelConfig(DetectorModelEnum modelEnum) {
         this.modelEnum = modelEnum;
     }
+
+    public <T> T getCustomParam(String key, Class<T> clazz) {
+        Object value = customParams.get(key);
+        if (value == null) return null;
+        return clazz.cast(value);
+    }
+
+    /**
+     * 添加个性化配置项
+     */
+    public void putCustomParam(String key, Object value) {
+        if (customParams == null) {
+            customParams = new HashMap<>();
+        }
+        customParams.put(key, value);
+    }
 }

smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/criteria/DJLModelCriteriaBuilder.java

@@ -33,6 +33,7 @@ public class DJLModelCriteriaBuilder implements CriteriaBuilderStrategy {
                 .optArgument("threshold", config.getThreshold() > 0 ? config.getThreshold() : DetectorConstant.DEFAULT_THRESHOLD)
                 .optModelUrls(DJL_MODEL_PREFIX + config.getModelEnum().getModelUri())
                 .optDevice(device)
+                //.optOption("ortDevice", "TensorRT")
                 .optProgress(new ProgressBar())
                 .build();
         return criteria;

smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/criteria/YoloCriteriaBuilder.java

@@ -1,14 +1,19 @@
 package cn.smartjavaai.objectdetection.criteria;
 
+import ai.djl.Device;
 import ai.djl.modality.cv.Image;
 import ai.djl.modality.cv.output.DetectedObjects;
 import ai.djl.modality.cv.translator.YoloV8TranslatorFactory;
 import ai.djl.repository.zoo.Criteria;
 import ai.djl.training.util.ProgressBar;
+import cn.smartjavaai.common.enums.DeviceEnum;
 import cn.smartjavaai.objectdetection.constant.DetectorConstant;
 import cn.smartjavaai.objectdetection.config.DetectorModelConfig;
 
 import java.nio.file.Paths;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.Objects;
 
 /**
  * YOLO模型Criteria 构建器
@@ -18,16 +23,25 @@ import java.nio.file.Paths;
 public class YoloCriteriaBuilder implements CriteriaBuilderStrategy {
     @Override
     public Criteria<Image, DetectedObjects> buildCriteria(DetectorModelConfig config) {
+        Device device = null;
+        if(!Objects.isNull(config.getDevice())){
+            device = config.getDevice() == DeviceEnum.CPU ? Device.cpu() : Device.gpu();
+        }
+
+        Map<String, Object> customParams = getDefaultConfig();
+        // 合并用户自定义参数（如有重复，覆盖默认默认值）
+        if (config.getCustomParams() != null) {
+            customParams.putAll(config.getCustomParams());
+        }
+
         Criteria.Builder criteriaBuilder = Criteria.builder()
                 .setTypes(Image.class, DetectedObjects.class)
                 //.optModelUrls("/Users/wenjie/Documents/develop/face_model/yolo")
                 .optModelPath(Paths.get(config.getModelPath()))
                 .optEngine("OnnxRuntime")
-                .optArgument("width", 640) //将输入图像的宽度缩放为 640 像素
-                .optArgument("height", 640)
-                .optArgument("resize", true)
-                .optArgument("toTensor", true)
-                .optArgument("applyRatio", true)
+                //.optOption("ortDevice", "TensorRT")
+                .optArguments(customParams)
+                .optDevice(device)
                 .optTranslatorFactory(new YoloV8TranslatorFactory())
                 .optProgress(new ProgressBar())
                 .optArgument("threshold", config.getThreshold() > 0 ? config.getThreshold() : DetectorConstant.DEFAULT_THRESHOLD);
@@ -37,4 +51,15 @@ public class YoloCriteriaBuilder implements CriteriaBuilderStrategy {
         Criteria<Image, DetectedObjects> criteria = criteriaBuilder.build();
         return criteria;
     }
+
+    public Map<String, Object> getDefaultConfig(){
+        Map<String, Object> arguments = new HashMap<>();
+        // 添加默认参数
+        arguments.put("width", 640);
+        arguments.put("height", 640);
+        arguments.put("resize", true);
+        arguments.put("toTensor", true);
+        arguments.put("applyRatio", true);
+        return arguments;
+    }
 }

smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/model/DetectorModel.java

@@ -41,10 +41,6 @@ public class DetectorModel implements AutoCloseable{
 
     private ZooModel<Image, DetectedObjects> model;
 
-    //private Predictor<Image, DetectedObjects> predictor;
-
-
-
     private ObjectPool<Predictor<Image, DetectedObjects>> predictorPool;
 
     public void loadModel(DetectorModelConfig config){
@@ -193,12 +189,23 @@ public class DetectorModel implements AutoCloseable{
 
 
     /**
-     * 显式释放资源（必须调用！）
+     * 显式释放资源
      */
     @Override
     public void close() {
-        if (predictorPool != null) {
-            predictorPool.close();
+        try {
+            if (predictorPool != null) {
+                predictorPool.close();
+            }
+        } catch (Exception e) {
+            log.warn("关闭 predictorPool 失败", e);
+        }
+        try {
+            if (model != null) {
+                model.close();
+            }
+        } catch (Exception e) {
+            log.warn("关闭 model 失败", e);
         }
     }
 }