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1、目标检测：支持自己训练的模型推理

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2、目标检测：支持yolo12模型
3、支持JDK8使用
4、引入离线依赖库，支持完全离线使用
5、优化FaceNet人脸比对速度
6、支持4通道图片检测
This commit is contained in:
dengwenjie
2025-05-17 11:19:46 +08:00
parent ab669d58e3
commit a7a118c5aa
27 changed files with 401 additions and 237 deletions
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24
examples/src/main/java/smartai/examples/face/facerec/FaceNetDemo.java
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@@ -54,14 +54,17 @@ public class FaceNetDemo {
@Test
public void testExtractFeaturesWithCustomConfig(){
try {
//人脸特征提取模型
FaceModel faceModel = FaceModelFactory.getInstance().getModel(
new FaceModelConfig(FaceModelEnum.FACENET_FEATURE_EXTRACTION));
//人脸模型参数
FaceModelConfig config = new FaceModelConfig();
config.setModelEnum(FaceModelEnum.FACENET_FEATURE_EXTRACTION);
//人脸特征提取参数
FaceExtractConfig extractConfig = new FaceExtractConfig();
//人脸检测模型配置
extractConfig.setDetectModelConfig(new FaceModelConfig(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE));
List<float[]> faceResult = faceModel.extractFeatures("src/main/resources/kana1.jpg",extractConfig);
extractConfig.setDetectModel(FaceModelFactory.getInstance().getModel(new FaceModelConfig(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE)));
config.setExtractConfig(extractConfig);
//人脸特征提取模型
FaceModel faceModel = FaceModelFactory.getInstance().getModel(config);
List<float[]> faceResult = faceModel.extractFeatures("src/main/resources/kana1.jpg");
log.info("人脸特征提取结果：{}", JSONObject.toJSONString(faceResult));
}catch (Exception e){
e.printStackTrace();
@@ -94,13 +97,16 @@ public class FaceNetDemo {
@Test
public void testExtractTopFaceFeatureWithCustomConfig(){
try {
//人脸特征提取模型
FaceModel faceModel = FaceModelFactory.getInstance().getModel(
new FaceModelConfig(FaceModelEnum.FACENET_FEATURE_EXTRACTION));
//人脸模型参数
FaceModelConfig config = new FaceModelConfig();
config.setModelEnum(FaceModelEnum.FACENET_FEATURE_EXTRACTION);
//人脸特征提取参数
FaceExtractConfig extractConfig = new FaceExtractConfig();
//人脸检测模型配置
extractConfig.setDetectModelConfig(new FaceModelConfig(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE));
extractConfig.setDetectModel(FaceModelFactory.getInstance().getModel(new FaceModelConfig(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE)));
config.setExtractConfig(extractConfig);
//人脸特征提取模型
FaceModel faceModel = FaceModelFactory.getInstance().getModel(config);
float[] faceResult = faceModel.extractTopFaceFeature("src/main/resources/kana1.jpg");
log.info("人脸特征提取结果：{}", JSONObject.toJSONString(faceResult));
}catch (Exception e){

36
examples/src/main/java/smartai/examples/objectdetection/ObjectDetection.java
View File

@@ -13,8 +13,8 @@ import ai.djl.repository.zoo.ZooModel;
import ai.djl.training.util.ProgressBar;
import cn.smartjavaai.common.entity.DetectionResponse;
import cn.smartjavaai.common.enums.DeviceEnum;
import cn.smartjavaai.objectdetection.DetectorModelConfig;
import cn.smartjavaai.objectdetection.DetectorModelEnum;
import cn.smartjavaai.objectdetection.config.DetectorModelConfig;
import cn.smartjavaai.objectdetection.enums.DetectorModelEnum;
import cn.smartjavaai.objectdetection.exception.DetectionException;
import cn.smartjavaai.objectdetection.model.DetectorModel;
import cn.smartjavaai.objectdetection.model.ObjectDetectionModelFactory;
@@ -62,7 +62,7 @@ public class ObjectDetection {
@Test
public void objectDetection2(){
DetectorModelConfig config = new DetectorModelConfig();
config.setModelEnum(DetectorModelEnum.SSD_300_RESNET50);//检测模型，目前支持19种模型
config.setModelEnum(DetectorModelEnum.SSD_300_RESNET50);//检测模型，目前支持19种预置模型
DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config);
DetectionResponse detectionResponse = detectorModel.detect("src/main/resources/dog_bike_car.jpg");
log.info("目标检测结果：{}", JSONObject.toJSONString(detectionResponse));
@@ -110,5 +110,35 @@ public class ObjectDetection {
}
/**
* 使用yolo官方模型检测
*/
@Test
public void objectDetectionWithOfficialModel(){
DetectorModelConfig config = new DetectorModelConfig();
//也支持YoloV8：YOLOV8_OFFICIAL 模型可以从文档中提供的地址下载
config.setModelEnum(DetectorModelEnum.YOLOV12_OFFICIAL);//检测模型，目前支持19种模型
// 指定模型路径，需要更改为自己的模型路径
config.setModelPath("/Users/xxx/Documents/develop/face_model/yolov12n.onnx");
DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config);
//一定要将yolo官方的类别文件：synset.txt（文档中下载）放在模型同目录下，否则报错
detectorModel.detectAndDraw("src/main/resources/object_detection.jpg","output/object_detection_detected.png");
}
/**
* 使用自己训练的模型检测
*/
@Test
public void objectDetectionWithCustomModel(){
DetectorModelConfig config = new DetectorModelConfig();
//也支持YoloV8：YOLOV8_CUSTOM 模型需要自己训练，训练教程可以查看文档
config.setModelEnum(DetectorModelEnum.YOLOV12_CUSTOM);//自定义YOLOV12模型
// 指定模型路径，需要更改为自己的模型路径
config.setModelPath("/Users/xxx/Documents/develop/fire_model/best.onnx");
DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config);
//一定要将类别文件：synset.txt 放在模型同目录下，否则报错(具体请参看文档)
detectorModel.detectAndDraw("/Users/xxx/Downloads/test.jpg","output/test_detected.jpg");
}
}