优化模型及添加图片存储实现，实现自动调度刷新milvus数据

face-search-client/src/main/java/com/visual/face/search/FaceCompare.java

@@ -0,0 +1,47 @@
+package com.visual.face.search;
+
+import java.util.Map;
+import java.util.concurrent.ConcurrentHashMap;
+import com.visual.face.search.handle.CompareHandler;
+
+public class FaceCompare {
+    /**服务地址**/
+    private String serverHost;
+    /**实例对象**/
+    private final static Map<String, FaceCompare> ins = new ConcurrentHashMap<>();
+
+    /**
+     * 构建集合对象
+     * @param serverHost        服务地址
+     * @return
+     */
+    private FaceCompare(String serverHost){
+        this.serverHost = serverHost;
+    }
+
+    /**
+     * 构建集合对象
+     * @param serverHost        服务地址
+     * @return
+     */
+    public static FaceCompare build (String serverHost){
+        String key = serverHost;
+        if(!ins.containsKey(key)){
+            synchronized (FaceCompare.class){
+                if(!ins.containsKey(key)){
+                    ins.put(key, new FaceCompare(serverHost));
+                }
+            }
+        }
+        return ins.get(key);
+    }
+    /**
+     * 人脸比对操作对象
+     * @return CollectHandler
+     */
+    public CompareHandler compare(){
+        return CompareHandler.build(serverHost);
+    }
+
+
+}

face-search-client/src/main/java/com/visual/face/search/common/Api.java

@@ -17,6 +17,7 @@ public class Api {
     public static final String face_create = "/visual/face/create";
 
     public static final String visual_search = "/visual/search/do";
+    public static final String visual_compare = "/visual/compare/do";
 
     public static String getUrl(String host, String uri){
         host = host.replaceAll ("/+$", "");

face-search-client/src/main/java/com/visual/face/search/handle/CollectHandler.java

@@ -47,7 +47,9 @@ public class CollectHandler extends BaseHandler<CollectHandler>{
                 .setSampleColumns(collect.getSampleColumns())
                 .setFaceColumns(collect.getFaceColumns())
                 .setSyncBinLog(collect.isSyncBinLog())
-                .setShardsNum(collect.getShardsNum());
+                .setShardsNum(collect.getShardsNum())
+                .setStorageFaceInfo(collect.getStorageFaceInfo())
+                .setStorageEngine(collect.getStorageEngine());
         return HttpClient.post(Api.getUrl(this.serverHost, Api.collect_create), collectReq);
     }
 

face-search-client/src/main/java/com/visual/face/search/handle/CompareHandler.java

@@ -0,0 +1,58 @@
+package com.visual.face.search.handle;
+
+import com.alibaba.fastjson.TypeReference;
+import com.visual.face.search.common.Api;
+import com.visual.face.search.http.HttpClient;
+import com.visual.face.search.model.*;
+
+import java.util.Map;
+import java.util.concurrent.ConcurrentHashMap;
+
+public class CompareHandler {
+
+    /**服务地址**/
+    protected String serverHost;
+    /**实例对象**/
+    private final static Map<String, CompareHandler> ins = new ConcurrentHashMap<>();
+
+    public String getServerHost() {
+        return serverHost;
+    }
+
+    public CompareHandler setServerHost(String serverHost) {
+        this.serverHost = serverHost;
+        return this;
+    }
+
+    /**
+     * 构建集合对象
+     * @param serverHost        服务地址
+     * @return
+     */
+    public static CompareHandler build(String serverHost){
+        String key = serverHost;
+        if(!ins.containsKey(key)){
+            synchronized (CollectHandler.class){
+                if(!ins.containsKey(key)){
+                    ins.put(key, new CompareHandler().setServerHost(serverHost));
+                }
+            }
+        }
+        return ins.get(key);
+    }
+
+    /**
+     * 人脸比对
+     * @param compare 集合的定义信息
+     * @return  是否创建成功
+     */
+    public Response<CompareRep> faceCompare(Compare compare){
+        CompareReq compareReq = CompareReq.build()
+                .setImageBase64A(compare.getImageBase64A())
+                .setImageBase64B(compare.getImageBase64B())
+                .setFaceScoreThreshold(compare.getFaceScoreThreshold())
+                .setNeedFaceInfo(compare.getNeedFaceInfo());
+        return HttpClient.post(Api.getUrl(this.serverHost, Api.visual_compare), compareReq, new TypeReference<Response<CompareRep>>() {});
+    }
+
+}

face-search-client/src/main/java/com/visual/face/search/model/Collect.java

@@ -20,6 +20,10 @@ public class Collect<ExtendsVo extends Collect<ExtendsVo>> implements Serializab
     private List<FiledColumn> faceColumns = new ArrayList<>();
     /**启用binlog同步**/
     private Boolean syncBinLog = false;
+    /**是否保留图片及人脸信息**/
+    private Boolean storageFaceInfo = false;
+    /**保留图片及人脸信息的存储组件**/
+    private StorageEngine storageEngine;
 
     /**
      * 构建集合对象
@@ -92,4 +96,26 @@ public class Collect<ExtendsVo extends Collect<ExtendsVo>> implements Serializab
         }
         return (ExtendsVo) this;
     }
+
+    public boolean getStorageFaceInfo() {
+        return null == storageFaceInfo ? false : storageFaceInfo;
+    }
+
+    public ExtendsVo setStorageFaceInfo(Boolean storageFaceInfo) {
+        if(null != storageFaceInfo){
+            this.storageFaceInfo = storageFaceInfo;
+        }
+        return (ExtendsVo) this;
+    }
+
+    public StorageEngine getStorageEngine() {
+        return storageEngine;
+    }
+
+    public ExtendsVo setStorageEngine(StorageEngine storageEngine) {
+        if(null != storageEngine){
+            this.storageEngine = storageEngine;
+        }
+        return (ExtendsVo) this;
+    }
 }

face-search-client/src/main/java/com/visual/face/search/model/Compare.java

@@ -0,0 +1,67 @@
+package com.visual.face.search.model;
+
+import java.io.Serializable;
+
+public class Compare <ExtendsVo extends Compare<ExtendsVo>> implements Serializable {
+
+    /**图像Base64编码值**/
+    private String imageBase64A;
+
+    /**图像Base64编码值**/
+    private String imageBase64B;
+
+    /**人脸质量分数阈值:人脸质量分数阈值,范围：[0,100]：默认0。当设置为0时，会默认使用当前模型的默认值，该方法为推荐使用方式**/
+    private Float faceScoreThreshold = 0f;
+
+    /**是否需要人脸信息**/
+    private Boolean needFaceInfo = true;
+
+    /**
+     * 构建比对对象
+     * @return
+     */
+    public static Compare build(){
+        return new Compare();
+    }
+
+
+    public String getImageBase64A() {
+        return imageBase64A;
+    }
+
+    public ExtendsVo setImageBase64A(String imageBase64A) {
+        this.imageBase64A = imageBase64A;
+        return (ExtendsVo) this;
+    }
+
+    public String getImageBase64B() {
+        return imageBase64B;
+    }
+
+    public ExtendsVo setImageBase64B(String imageBase64B) {
+        this.imageBase64B = imageBase64B;
+        return (ExtendsVo) this;
+    }
+
+    public Float getFaceScoreThreshold() {
+        return faceScoreThreshold;
+    }
+
+    public ExtendsVo setFaceScoreThreshold(Float faceScoreThreshold) {
+        if(null != faceScoreThreshold && faceScoreThreshold >= 0 && faceScoreThreshold <= 100){
+            this.faceScoreThreshold = faceScoreThreshold;
+        }
+        return (ExtendsVo) this;
+    }
+
+    public Boolean getNeedFaceInfo() {
+        return needFaceInfo;
+    }
+
+    public ExtendsVo setNeedFaceInfo(Boolean needFaceInfo) {
+        if(null != needFaceInfo){
+            this.needFaceInfo = needFaceInfo;
+        }
+        return (ExtendsVo) this;
+    }
+}

face-search-client/src/main/java/com/visual/face/search/model/CompareFace.java

@@ -0,0 +1,47 @@
+package com.visual.face.search.model;
+
+public class CompareFace {
+
+    /**A图片人脸分数:[0,100]**/
+    private Float faceScoreA;
+    /**B图片人脸分数:[0,100]**/
+    private Float faceScoreB;
+
+    /**A图片人脸位置信息**/
+    private FaceLocation locationA;
+    /**B图片人脸位置信息**/
+    private FaceLocation locationB;
+
+
+    public Float getFaceScoreA() {
+        return faceScoreA;
+    }
+
+    public void setFaceScoreA(Float faceScoreA) {
+        this.faceScoreA = faceScoreA;
+    }
+
+    public FaceLocation getLocationA() {
+        return locationA;
+    }
+
+    public void setLocationA(FaceLocation locationA) {
+        this.locationA = locationA;
+    }
+
+    public Float getFaceScoreB() {
+        return faceScoreB;
+    }
+
+    public void setFaceScoreB(Float faceScoreB) {
+        this.faceScoreB = faceScoreB;
+    }
+
+    public FaceLocation getLocationB() {
+        return locationB;
+    }
+
+    public void setLocationB(FaceLocation locationB) {
+        this.locationB = locationB;
+    }
+}

face-search-client/src/main/java/com/visual/face/search/model/CompareRep.java

@@ -0,0 +1,40 @@
+package com.visual.face.search.model;
+
+import java.io.Serializable;
+
+public class CompareRep implements Serializable {
+    /**向量欧式距离:>=0**/
+    private Float distance;
+    /**余弦距离转换后的置信度:[-100,100]，值越大，相似度越高。**/
+    private Float confidence;
+    /**人脸信息,参数needFaceInfo=false时，值为null**/
+    private CompareFace faceInfo;
+
+    public Float getDistance() {
+        return distance;
+    }
+
+    public CompareRep setDistance(Float distance) {
+        this.distance = distance;
+        return this;
+    }
+
+    public Float getConfidence() {
+        return confidence;
+    }
+
+    public CompareRep setConfidence(Float confidence) {
+        this.confidence = confidence;
+        return this;
+    }
+
+    public CompareFace getFaceInfo() {
+        return faceInfo;
+    }
+
+    public CompareRep setFaceInfo(CompareFace faceInfo) {
+        this.faceInfo = faceInfo;
+        return this;
+    }
+
+}

face-search-client/src/main/java/com/visual/face/search/model/CompareReq.java

@@ -0,0 +1,13 @@
+package com.visual.face.search.model;
+
+public class CompareReq extends Compare<CompareReq> {
+
+    /**
+     * 构建比对对象
+     * @return
+     */
+    public static CompareReq build(){
+        return new CompareReq();
+    }
+
+}

face-search-client/src/main/java/com/visual/face/search/model/StorageEngine.java

@@ -0,0 +1,8 @@
+package com.visual.face.search.model;
+
+public enum StorageEngine {
+    CURR_DB,
+    ALI_OSS,
+    TCE_COS,
+    MIN_IO
+}

face-search-core/src/main/java/com/visual/face/search/core/utils/ArrayUtil.java

@@ -0,0 +1,37 @@
+package com.visual.face.search.core.utils;
+
+public class ArrayUtil {
+
+    public static double [] floatToDouble(float[] input){
+        if (input == null){
+            return null;
+        }
+        double[] output = new double[input.length];
+        for (int i = 0; i < input.length; i++){
+            output[i] = input[i];
+        }
+        return output;
+    }
+
+    public static float [] doubleToFloat(double[] input){
+        if (input == null){
+            return null;
+        }
+        float[] output = new float[input.length];
+        for (int i = 0; i < input.length; i++){
+            output[i] = Double.valueOf(input[i]).floatValue();
+        }
+        return output;
+    }
+
+    public static double matrixNorm(double[][] matrix){
+        double sum=0.0;
+        for(double[] temp1:matrix){
+            for(double temp2:temp1){
+                sum+=Math.pow(temp2,2);
+            }
+        }
+        return Math.sqrt(sum);
+    }
+
+}

face-search-core/src/main/java/com/visual/face/search/core/utils/MatUtil.java

@@ -1,6 +1,8 @@
 package com.visual.face.search.core.utils;
 
 import org.opencv.core.Mat;
+import org.opencv.core.Range;
+
 import javax.imageio.ImageIO;
 import java.awt.image.BufferedImage;
 import java.io.ByteArrayOutputStream;
@@ -42,9 +44,6 @@ public class MatUtil {
             byteArrayOutputStream = new ByteArrayOutputStream();
             ImageIO.write(matToBufferedImage(mat), "jpg", byteArrayOutputStream);
             byte[] bytes = byteArrayOutputStream.toByteArray();
-            // 新版本JDK被移除，替换为Base64.Encoder
-//            BASE64Encoder encoder = new BASE64Encoder();
-//            return encoder.encodeBuffer(Objects.requireNonNull(bytes));
             Base64.Encoder encoder = Base64.getMimeEncoder();
             return encoder.encodeToString(Objects.requireNonNull(bytes));
         }catch (Exception e){
@@ -58,4 +57,41 @@ public class MatUtil {
         }
     }
 
+    /**
+     * 横向拼接两个图像的数据（Mat），该两个图像的类型必须是相同的类型，如：均为CvType.CV_8UC3类型
+     * @author bailichun
+     * @since 2020.02.20 15:00
+     * @param m1 要合并的图像1（左图）
+     * @param m2 要合并的图像2（右图）
+     * @return 拼接好的Mat图像数据集。其高度等于两个图像中高度较大者的高度；其宽度等于两个图像的宽度之和。类型与两个输入图像相同。
+     * @throws Exception 当两个图像数据的类型不同时，抛出异常
+     */
+    public static Mat concat(Mat m1, Mat m2){
+        if(m1.type() != m2.type()){
+            throw new RuntimeException("concat:两个图像数据的类型不同！");
+        }
+        long time = System.currentTimeMillis();
+        //宽度为两图的宽度之和
+        double w = m1.size().width + m2.size().width;
+        //高度取两个矩阵中的较大者的高度
+        double h = m1.size().height > m2.size().height ? m1.size().height : m2.size().height;
+        //创建一个大矩阵对象
+        Mat des = Mat.zeros((int)h, (int)w, m1.type());
+        //在最终的大图上标记一块区域，用于存放复制图1（左图）的数据，大小为从第0列到m1.cols()列
+        Mat rectForM1 = des.colRange(new Range(0, m1.cols()));
+        //标记出位于rectForM1的垂直方向上中间位置的区域，高度为图1的高度，此时该区域的大小已经和图1的大小相同。（用于存放复制图1（左图）的数据）
+        int rowOffset1 = (int)(rectForM1.size().height-m1.rows())/2;
+        rectForM1 = rectForM1.rowRange(rowOffset1, rowOffset1 + m1.rows());
+        //在最终的大图上标记一块区域，用于存放复制图2（右图）的数据
+        Mat rectForM2 = des.colRange(new Range(m1.cols(), des.cols()));
+        //标记出位于rectForM2的垂直方向上中间位置的区域，高度为图2的高度，此时该区域的大小已经和图2的大小相同。（用于存放复制图2（右图）的数据）
+        int rowOffset2 = (int)(rectForM2.size().height-m2.rows())/2;
+        rectForM2 = rectForM2.rowRange(rowOffset2, rowOffset2 + m2.rows());
+        //将图1拷贝到des的指定区域 rectForM1
+        m1.copyTo(rectForM1);
+        //将图2拷贝到des的指定区域 rectForM2
+        m2.copyTo(rectForM2);
+        return des;
+    }
+
 }

face-search-core/src/main/java/com/visual/face/search/core/utils/Similarity.java

@@ -1,5 +1,8 @@
 package com.visual.face.search.core.utils;
 
+import org.apache.commons.math3.linear.RealMatrix;
+import static com.visual.face.search.core.utils.ArrayUtil.matrixNorm;
+
 public class Similarity {
 
     /**
@@ -52,4 +55,25 @@ public class Similarity {
         return (float) distance;
     }
 
+    /**
+     * 向量余弦相似度,加入了norm变换
+     * @param leftVector
+     * @param rightVector
+     * @return
+     */
+    public static float cosineSimilarityNorm(float[] leftVector, float[] rightVector) {
+        RealMatrix rm1 = MathUtil.createMatrix(1, ArrayUtil.floatToDouble(leftVector));
+        RealMatrix rm2 = MathUtil.createMatrix(1, ArrayUtil.floatToDouble(rightVector));
+        RealMatrix num = rm1.multiply(rm2.transpose());
+        double deco = matrixNorm(rm1.getData()) * matrixNorm(rm2.getData());
+        double cos = num.getEntry(0, 0) / deco;
+        double sim = cos;
+        if(cos >= 0.5){
+            sim = cos + 2 * (cos - 0.5) * (1 - cos);
+        }else if(cos >= 0){
+            sim = cos - 2 * (cos - 0.5) * (0 - cos);
+        }
+        return Double.valueOf(sim).floatValue();
+    }
+
 }