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

examples/objectdetection-example/src/main/java/smartai/examples/objectdetection/ObjectDetection.java

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+package smartai.examples.objectdetection;
+
+import ai.djl.Application;
+import ai.djl.MalformedModelException;
+import ai.djl.modality.cv.Image;
+import ai.djl.modality.cv.ImageFactory;
+import ai.djl.modality.cv.output.*;
+import ai.djl.modality.cv.output.Rectangle;
+import ai.djl.repository.zoo.Criteria;
+import ai.djl.repository.zoo.ModelNotFoundException;
+import ai.djl.repository.zoo.ModelZoo;
+import ai.djl.repository.zoo.ZooModel;
+import ai.djl.training.util.ProgressBar;
+import cn.smartjavaai.common.entity.DetectionInfo;
+import cn.smartjavaai.common.entity.DetectionRectangle;
+import cn.smartjavaai.common.entity.DetectionResponse;
+import cn.smartjavaai.common.entity.R;
+import cn.smartjavaai.common.enums.DeviceEnum;
+import cn.smartjavaai.common.enums.face.LivenessStatus;
+import cn.smartjavaai.common.utils.ImageUtils;
+import cn.smartjavaai.common.utils.OpenCVUtils;
+import cn.smartjavaai.face.model.liveness.LivenessDetModel;
+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;
+import com.alibaba.fastjson.JSONObject;
+import lombok.extern.slf4j.Slf4j;
+import nu.pattern.OpenCV;
+import org.junit.Assert;
+import org.junit.Test;
+import org.opencv.core.Mat;
+import org.opencv.core.Size;
+import org.opencv.imgproc.Imgproc;
+import org.opencv.videoio.VideoCapture;
+import org.opencv.videoio.Videoio;
+
+import javax.imageio.ImageIO;
+import javax.swing.*;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+import java.io.File;
+import java.io.IOException;
+import java.nio.file.Paths;
+import java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Objects;
+import java.util.concurrent.Callable;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import java.util.concurrent.Future;
+
+/**
+ * 目标检测模型demo
+ * 支持功能：目标检测
+ * 模型下载地址：https://pan.baidu.com/s/10aTOLBlR6EG-sq6g0OkAWg?pwd=1234 提取码: 1234
+ * @author dwj
+ */
+@Slf4j
+public class ObjectDetection {
+
+
+    //设备类型
+    public static DeviceEnum device = DeviceEnum.CPU;
+
+
+
+    /**
+     * 使用默认模型检测：YOLO11N
+     */
+    @Test
+    public void objectDetection(){
+        //默认cpu
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel()){
+            DetectionResponse detectionResponse = detectorModel.detect("src/main/resources/object_detection.jpg");
+            log.info("目标检测结果：{}", JSONObject.toJSONString(detectionResponse));
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 指定模型检测(19种模型可选)
+     */
+    @Test
+    public void objectDetection2(){
+        DetectorModelConfig config = new DetectorModelConfig();
+        config.setModelEnum(DetectorModelEnum.SSD_300_RESNET50);//检测模型，目前支持19种预置模型
+        config.setDevice(device);
+        try (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));
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 人脸检测并绘制检测结果
+     */
+    @Test
+    public void objectDetectionAndDraw(){
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel()){
+            detectorModel.detectAndDraw("src/main/resources/object_detection.jpg","output/object_detection_detected.png");
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 人脸检测并绘制检测结果,返回BufferedImage
+     */
+    @Test
+    public void objectDetectionAndDraw2(){
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel()){
+            String imagePath = "src/main/resources/object_detection.jpg";
+            BufferedImage image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString()));
+            //可以根据后续业务场景使用detectedImage
+            BufferedImage detectedImage = detectorModel.detectAndDraw(image);
+            Assert.assertNotNull("detectedImage null", detectedImage);
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+
+    }
+
+
+
+    /**
+     * 使用yolo官方模型检测物品识别
+     */
+    @Test
+    public void objectDetectionWithOfficialModel(){
+        DetectorModelConfig config = new DetectorModelConfig();
+        config.setThreshold(0.3f);
+        //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/yolov12n.onnx");
+        config.setDevice(device);
+        //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
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config)){
+            DetectionResponse detect = detectorModel.detect("src/main/resources/dog_bike_car.jpg");
+            log.info("目标检测结果：{}", JSONObject.toJSONString(detect));
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 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");
+        config.putCustomParam("width", 640);//resize 宽
+        config.putCustomParam("height", 640);// resize 高
+        config.putCustomParam("nmsThreshold", 0.5f);
+        config.setDevice(device);
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel(config)){
+            DetectionResponse detect = detectorModel.detect("src/main/resources/dog_bike_car.jpg");
+            log.info("目标检测结果：{}", JSONObject.toJSONString(detect));
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+
+    /**
+     * 摄像头目标检测
+     * 注意事项：如果视频比较卡，可以使用轻量的检测模型
+     */
+    @Test
+    public void testDetectCamera(){
+        try (DetectorModel detectorModel = ObjectDetectionModelFactory.getInstance().getModel()){
+            OpenCV.loadShared();
+            VideoCapture capture = new VideoCapture(0);
+            if (!capture.isOpened()) {
+                System.out.println("No camera detected");
+                return;
+            }
+
+            double ratio =
+                    capture.get(Videoio.CAP_PROP_FRAME_WIDTH)
+                            / capture.get(Videoio.CAP_PROP_FRAME_HEIGHT);
+            Dimension screenSize = Toolkit.getDefaultToolkit().getScreenSize();
+            int height = (int) (screenSize.height * 0.65f);
+            int width = (int) (height * ratio);
+            if (width > screenSize.width) {
+                width = screenSize.width;
+            }
+
+            Mat image = new Mat();
+            boolean captured = false;
+            for (int i = 0; i < 10; ++i) {
+                captured = capture.read(image);
+                if (captured) {
+                    break;
+                }
+
+                try {
+                    Thread.sleep(50);
+                } catch (InterruptedException ignore) {
+                    // ignore
+                }
+            }
+            if (!captured) {
+                JOptionPane.showConfirmDialog(null, "Failed to capture image from WebCam.");
+            }
+            ViewerFrame frame = new ViewerFrame(width, height);
+            ImageFactory factory = ImageFactory.getInstance();
+            Size size = new Size(width, height);
+
+            while (capture.isOpened()) {
+                if (!capture.read(image)) {
+                    break;
+                }
+                Mat resizeImage = new Mat();
+                Imgproc.resize(image, resizeImage, size);
+                Image img = factory.fromImage(resizeImage);
+                BufferedImage bufferedImage = OpenCVUtils.mat2Image(resizeImage);
+                DetectionResponse detectedResult = detectorModel.detect(bufferedImage);
+                if (Objects.isNull(detectedResult) || Objects.isNull(detectedResult.getDetectionInfoList()) || detectedResult.getDetectionInfoList().size() == 0){
+                    log.debug("未检测到物体");
+                    continue;
+                }
+                for(DetectionInfo detectionInfo : detectedResult.getDetectionInfoList()){
+                    DetectionRectangle detectionRectangle = detectionInfo.getDetectionRectangle();
+                    String text = detectionInfo.getObjectDetInfo().getClassName();
+                    ImageUtils.drawImageRectWithText(bufferedImage, detectionRectangle, text, Color.RED);
+                }
+                frame.showImage(bufferedImage);
+            }
+
+            capture.release();
+            System.exit(0);
+        } catch (Exception e) {
+            throw new RuntimeException(e);
+        }
+    }
+
+
+}

examples/objectdetection-example/src/main/java/smartai/examples/objectdetection/ViewerFrame.java

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+/*
+ * Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
+ * with the License. A copy of the License is located at
+ *
+ * http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
+ * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
+ * and limitations under the License.
+ */
+package smartai.examples.objectdetection;
+
+import javax.swing.*;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+
+public class ViewerFrame {
+
+    private JFrame frame;
+    private ImagePanel imagePanel;
+
+    public ViewerFrame(int width, int height) {
+        frame = new JFrame("Demo");
+        imagePanel = new ImagePanel();
+        frame.setLayout(new BorderLayout());
+        frame.add(BorderLayout.CENTER, imagePanel);
+
+        JOptionPane.setRootFrame(frame);
+        Dimension screenSize = Toolkit.getDefaultToolkit().getScreenSize();
+        if (width > screenSize.width) {
+            width = screenSize.width;
+        }
+        Dimension frameSize = new Dimension(width, height);
+        frame.setSize(frameSize);
+        frame.setLocation((screenSize.width - width) / 2, (screenSize.height - height) / 2);
+        frame.setDefaultCloseOperation(WindowConstants.EXIT_ON_CLOSE);
+        frame.setVisible(true);
+    }
+
+    public void showImage(BufferedImage image) {
+        imagePanel.setImage(image);
+        SwingUtilities.invokeLater(
+                () -> {
+                    frame.repaint();
+                    frame.pack();
+                });
+    }
+
+    private static final class ImagePanel extends JPanel {
+
+        private BufferedImage image;
+
+        void setImage(BufferedImage image) {
+            this.image = image;
+        }
+
+        @Override
+        public void paintComponent(Graphics g) {
+            super.paintComponent(g);
+            if (image == null) {
+                return;
+            }
+
+            g.drawImage(image, 0, 0, null);
+            setPreferredSize(new Dimension(image.getWidth(), image.getHeight()));
+        }
+    }
+}

examples/objectdetection-example/src/main/resources/META-INF/MANIFEST.MF

@@ -0,0 +1,3 @@
+Manifest-Version: 1.0
+Main-Class: smartai.examples.face.SeetaFace6LinuxDemo
+

examples/objectdetection-example/src/main/resources/logback.xml

@@ -0,0 +1,14 @@
+<?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="DEBUG">
+        <appender-ref ref="CONSOLE" />
+    </root>
+</configuration>