1、目标检测：支持自己训练的模型推理

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
2026-09-12 20:58:51 +00:00 · 2025-05-17 11:19:46 +08:00
parent ab669d58e3
commit a7a118c5aa
27 changed files with 401 additions and 237 deletions
--- a/smartjavaai-face/pom.xml
+++ b/smartjavaai-face/pom.xml
@@ -6,11 +6,11 @@
    <parent>
        <groupId>cn.smartjavaai</groupId>
        <artifactId>smartjavaai-parent</artifactId>
-        <version>1.0.12</version>
+        <version>1.0.13</version>
    </parent>

    <artifactId>smartjavaai-face</artifactId>
-    <version>1.0.12</version>
+    <version>1.0.13</version>
    <name>smartjavaai-face</name>
    <description>SmartJavaAI</description>
    <url>https://github.com/geekwenjie/SmartJavaAI</url>
@@ -22,8 +22,8 @@
    </licenses>

    <properties>
-        <maven.compiler.source>11</maven.compiler.source>
-        <maven.compiler.target>11</maven.compiler.target>
+<!--        <maven.compiler.source>11</maven.compiler.source>-->
+<!--        <maven.compiler.target>11</maven.compiler.target>-->
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <maven.test.skip>true</maven.test.skip>
        <javacv.version>1.5.8</javacv.version>
@@ -87,7 +87,7 @@
                <artifactId>maven-javadoc-plugin</artifactId>
                <version>3.1.0</version>
                <configuration>
-                    <javadocExecutable>${java.home}/bin/javadoc</javadocExecutable>
+<!--                    <javadocExecutable>${java.home}/bin/javadoc</javadocExecutable>-->
                    <doclint>none</doclint>
                    <additionalJOptions>
                        <additionalJOption>-Xdoclint:none</additionalJOption>
--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/config/FaceExtractConfig.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/config/FaceExtractConfig.java
@@ -1,5 +1,6 @@
 package cn.smartjavaai.face.config;

+import cn.smartjavaai.face.model.facerec.FaceModel;
 import lombok.Data;

 /**
@@ -21,17 +22,17 @@ public class FaceExtractConfig {
    private boolean align = true;

    /**
-     * 人脸检测模型配置
+     * 人脸检测模型
     */
-    private FaceModelConfig detectModelConfig;
+    private FaceModel detectModel;

    public FaceExtractConfig() {
    }

-    public FaceExtractConfig(boolean cropFace, boolean align, FaceModelConfig detectModelConfig) {
+    public FaceExtractConfig(boolean cropFace, boolean align, FaceModel detectModel) {
        this.cropFace = cropFace;
        this.align = align;
-        this.detectModelConfig = detectModelConfig;
+        this.detectModel = detectModel;
    }


--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/config/FaceModelConfig.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/config/FaceModelConfig.java
@@ -52,6 +52,11 @@ public class FaceModelConfig {
     */
    private int gpuId = 0;

+    /**
+     * 人脸特征提取配置
+     */
+    private FaceExtractConfig extractConfig;
+
    public FaceModelConfig() {
    }

--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/AbstractFaceModel.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/AbstractFaceModel.java
@@ -140,21 +140,6 @@ public abstract class AbstractFaceModel implements FaceModel {
        throw new UnsupportedOperationException("默认不支持该功能");
    }

-    @Override
-    public List<float[]> extractFeatures(BufferedImage image, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }
-
-    @Override
-    public List<float[]> extractFeatures(String imagePath, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }
-
-    @Override
-    public List<float[]> extractFeatures(byte[] imageData, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }
-
    @Override
    public float[] extractTopFaceFeature(BufferedImage image) {
        throw new UnsupportedOperationException("默认不支持该功能");
@@ -170,18 +155,5 @@ public abstract class AbstractFaceModel implements FaceModel {
        throw new UnsupportedOperationException("默认不支持该功能");
    }

-    @Override
-    public float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }

-    @Override
-    public float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }
-
-    @Override
-    public float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config) {
-        throw new UnsupportedOperationException("默认不支持该功能");
-    }
 }
--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/FaceModel.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/FaceModel.java
@@ -199,30 +199,6 @@ public interface FaceModel {
     */
    List<float[]> extractFeatures(BufferedImage image);

-    /**
-     * 特征提取（使用自定义配置）
-     * 强制裁剪操作
-     * @param image BufferedImage
-     * @param config
-     * @return
-     */
-    List<float[]> extractFeatures(BufferedImage image, FaceExtractConfig config);
-
-    /**
-     * 特征提取（使用自定义配置）
-     * @param imagePath 图片路径
-     * @param config
-     * @return
-     */
-    List<float[]> extractFeatures(String imagePath, FaceExtractConfig config);
-
-    /**
-     * 特征提取（使用自定义配置）
-     * @param imageData 图片字节流
-     * @param config
-     * @return
-     */
-    List<float[]> extractFeatures(byte[] imageData, FaceExtractConfig config);

    /**
     * 提取分数最高人脸特征（使用默认配置）
@@ -245,27 +221,6 @@ public interface FaceModel {
     */
    float[] extractTopFaceFeature(byte[] imageData);

-    /**
-     * 提取分数最高人脸特征（使用自定义配置）
-     * @param image BufferedImage
-     * @return
-     */
-    float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config);

-    /**
-     * 提取分数最高人脸特征（使用自定义配置）
-     * @param imagePath 图片路径
-     * @param config
-     * @return
-     */
-    float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config);
-
-    /**
-     * 提取分数最高人脸特征（使用自定义配置）
-     * @param imageData 图片字节流
-     * @param config
-     * @return
-     */
-    float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config);

 }
--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/FeatureExtractionModel.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/FeatureExtractionModel.java
@@ -59,6 +59,8 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo

    private ZooModel<Image, float[]> model;

+    private FaceModelConfig config;
+
    public static final List<Float> mean =
            Arrays.asList(
                    127.5f / 255.0f,
@@ -75,10 +77,21 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
     */
    @Override
    public void loadModel(FaceModelConfig config) {
+        if(Objects.isNull(config)){
+            throw new FaceException("config为null");
+        }
+        if(Objects.isNull(config.getExtractConfig())){
+            config.setExtractConfig(getDefaultConfig());
+        }else{
+            if(Objects.isNull(config.getExtractConfig().getDetectModel())){
+                throw new FaceException("请设置人脸检测模型");
+            }
+        }
        Device device = null;
        if(!Objects.isNull(config.getDevice())){
            device = config.getDevice() == DeviceEnum.CPU ? Device.cpu() : Device.gpu();
        }
+        this.config = config;
        String normalize = mean.stream().map(Object::toString).collect(Collectors.joining(","));
        Criteria<Image, float[]> faceFeatureCriteria =
                Criteria.builder()
@@ -162,7 +175,8 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
        }
        float[] feature1 = extractTopFaceFeature(imagePath1);
        float[] feature2 = extractTopFaceFeature(imagePath2);
-        return calculSimilar(feature1, feature2);
+        float ret = calculSimilar(feature1, feature2);
+        return ret;
    }


@@ -194,37 +208,18 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
        FaceExtractConfig config = new FaceExtractConfig();
        FaceModelConfig detectModelConfig = new FaceModelConfig();
        detectModelConfig.setModelEnum(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE);
-        config.setDetectModelConfig(detectModelConfig);
+        log.debug("创建默认检测模型：ULTRA_LIGHT_FAST_GENERIC_FACE");
+        FaceModel detectModel = FaceModelFactory.getInstance().getModel(detectModelConfig);
+        log.debug("创建检测模型完毕");
+        config.setDetectModel(detectModel);
        return config;
    }

-    @Override
-    public List<float[]> extractFeatures(String imagePath) {
-        return extractFeatures(imagePath, getDefaultConfig());
-    }
-
-    @Override
-    public List<float[]> extractFeatures(byte[] imageData) {
-        return extractFeatures(imageData, getDefaultConfig());
-    }
-
    @Override
    public List<float[]> extractFeatures(BufferedImage image) {
-        return extractFeatures(image, getDefaultConfig());
-    }

-
-    @Override
-    public List<float[]> extractFeatures(BufferedImage image, FaceExtractConfig config) {
-        if(Objects.isNull(config)){
-            throw new FaceException("config为null");
-        }
        List<float[]> featureList = new ArrayList<float[]>();
-        if(Objects.isNull(config.getDetectModelConfig())){
-            throw new FaceException("config.detectModelConfig为null");
-        }
-        FaceModel faceModel = FaceModelFactory.getInstance().getModel(config.getDetectModelConfig());
-        DetectionResponse detectedResult = faceModel.detect(image);
+        DetectionResponse detectedResult = config.getExtractConfig().getDetectModel().detect(image);
        if(Objects.isNull(detectedResult) || Objects.isNull(detectedResult.getDetectionInfoList()) || detectedResult.getDetectionInfoList().isEmpty()){
            throw new FaceException("未检测到人脸");
        }
@@ -237,7 +232,7 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
            //裁剪人脸
            Image subImage = djlImage.getSubImage(rectangle.getX(), rectangle.getY() , rectangle.getWidth() , rectangle.getHeight());
            //人脸对齐
-            if(config.isAlign()){
+            if(config.getExtractConfig().isAlign()){
                //获取子图中人脸关键点坐标
                double[][] pointsArray = FaceUtils.facePoints(detectionInfo.getFaceInfo().getKeyPoints());
                NDArray srcPoints = manager.create(pointsArray);
@@ -263,8 +258,21 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
        return featureList;
    }

+
    @Override
-    public List<float[]> extractFeatures(String imagePath, FaceExtractConfig config) {
+    public List<float[]> extractFeatures(byte[] imageData) {
+        if(Objects.isNull(imageData)){
+            throw new FaceException("图像无效");
+        }
+        try {
+            return extractFeatures(ImageIO.read(new ByteArrayInputStream(imageData)));
+        } catch (IOException e) {
+            throw new FaceException("错误的图像", e);
+        }
+    }
+
+    @Override
+    public List<float[]> extractFeatures(String imagePath) {
        if(!FileUtils.isFileExists(imagePath)){
            throw new FaceException("图像文件不存在");
        }
@@ -275,49 +283,15 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
        } catch (IOException e) {
            throw new FaceException("无效图片路径", e);
        }
-        return extractFeatures(image, config);
-    }
-
-    @Override
-    public List<float[]> extractFeatures(byte[] imageData, FaceExtractConfig config) {
-        if(Objects.isNull(imageData)){
-            throw new FaceException("图像无效");
-        }
-        try {
-            return extractFeatures(ImageIO.read(new ByteArrayInputStream(imageData)), config);
-        } catch (IOException e) {
-            throw new FaceException("错误的图像", e);
-        }
+        return extractFeatures(image);
    }

    @Override
    public float[] extractTopFaceFeature(BufferedImage image) {
-        return extractTopFaceFeature(image, getDefaultConfig());
-    }
-
-    @Override
-    public float[] extractTopFaceFeature(String imagePath) {
-        return extractTopFaceFeature(imagePath, getDefaultConfig());
-    }
-
-    @Override
-    public float[] extractTopFaceFeature(byte[] imageData) {
-        return extractTopFaceFeature(imageData, getDefaultConfig());
-    }
-
-    @Override
-    public float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config) {
-        if(Objects.isNull(config)){
-            throw new FaceException("config为null");
-        }
-        if(Objects.isNull(config.getDetectModelConfig())){
-            throw new FaceException("config.detectModelConfig为null");
-        }
        Image djlImage = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image));
        float[] features = null;
-        if(config.isCropFace()){
-            FaceModel faceModel = FaceModelFactory.getInstance().getModel(config.getDetectModelConfig());
-            DetectionResponse detectedResult = faceModel.detect(image);
+        if(config.getExtractConfig().isCropFace()){
+            DetectionResponse detectedResult = config.getExtractConfig().getDetectModel().detect(image);
            if(Objects.isNull(detectedResult) || Objects.isNull(detectedResult.getDetectionInfoList()) || detectedResult.getDetectionInfoList().isEmpty()){
                throw new FaceException("未检测到人脸");
            }
@@ -327,7 +301,7 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
            //裁剪人脸
            Image subImage = djlImage.getSubImage(rectangle.getX(), rectangle.getY() , rectangle.getWidth() , rectangle.getHeight());
            //人脸对齐
-            if(config.isAlign()){
+            if(config.getExtractConfig().isAlign()){
                NDManager manager = NDManager.newBaseManager();
                //获取子图中人脸关键点坐标
                double[][] pointsArray = FaceUtils.facePoints(detectionInfo.getFaceInfo().getKeyPoints());
@@ -355,7 +329,7 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
    }

    @Override
-    public float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config) {
+    public float[] extractTopFaceFeature(String imagePath) {
        if(!FileUtils.isFileExists(imagePath)){
            throw new FaceException("图像文件不存在");
        }
@@ -366,16 +340,16 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo
        } catch (IOException e) {
            throw new FaceException("无效图片路径", e);
        }
-        return extractTopFaceFeature(image, config);
+        return extractTopFaceFeature(image);
    }

    @Override
-    public float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config) {
+    public float[] extractTopFaceFeature(byte[] imageData) {
        if(Objects.isNull(imageData)){
            throw new FaceException("图像无效");
        }
        try {
-            return extractTopFaceFeature(ImageIO.read(new ByteArrayInputStream(imageData)), config);
+            return extractTopFaceFeature(ImageIO.read(new ByteArrayInputStream(imageData)));
        } catch (IOException e) {
            throw new FaceException("错误的图像", e);
        }
--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/SeetaFace6Model.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/facerec/SeetaFace6Model.java
@@ -629,6 +629,7 @@ public class SeetaFace6Model extends AbstractFaceModel {

    @Override
    public FaceResult search(BufferedImage image) {
+        long time1 = System.currentTimeMillis();
        if(!ImageUtils.isImageValid(image)){
            throw new FaceException("图像无效");
        }
@@ -648,7 +649,12 @@ public class SeetaFace6Model extends AbstractFaceModel {
            if(similarity[0] < config.getSimilarityThreshold()){
                return null;
            }
-            return searchFaceDb(index[0], similarity[0]);
+            long time2 = System.currentTimeMillis();
+            System.out.println("总耗时1：" + (time2 - time1) + " ms");
+            FaceResult faceResult = searchFaceDb(index[0], similarity[0]);
+            long time3 = System.currentTimeMillis();
+            System.out.println("总耗时2：" + (time3 - time2) + " ms");
+            return faceResult;
        } catch (FaceException e) {
            throw e;
        } catch (Exception e) {
--- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/OpenCVUtils.java
+++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/OpenCVUtils.java
@@ -111,8 +111,26 @@ public class OpenCVUtils {
    public static Mat image2Mat(BufferedImage img) {
        int width = img.getWidth();
        int height = img.getHeight();
+        int channels;
+
+        // 获取图像类型
+        int imageType = img.getType();
+
+        // 判断是3通道还是4通道
+        if (imageType == BufferedImage.TYPE_3BYTE_BGR) {
+            channels = 3;
+        } else if (imageType == BufferedImage.TYPE_4BYTE_ABGR || imageType == BufferedImage.TYPE_4BYTE_ABGR_PRE) {
+            channels = 4;
+        } else {
+            // 如果不是已知格式，强制转换为 3 通道 BGR
+            BufferedImage convertedImg = new BufferedImage(width, height, BufferedImage.TYPE_3BYTE_BGR);
+            convertedImg.getGraphics().drawImage(img, 0, 0, null);
+            img = convertedImg;
+            channels = 3;
+        }
+
        byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData();
-        Mat mat = new Mat(height, width, CvType.CV_8UC3);
+        Mat mat = new Mat(height, width, CvType.CV_8UC(channels));
        mat.put(0, 0, data);
        return mat;
    }