人脸搜索1:N，postgreSql(pgvector) ，mybatis-plus操作向量数据库

本文链接：https://blog.youkuaiyun.com/weixin_38378957/article/details/143192409

package com.lyc.entities;

import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import com.lyc.typeHandler.DoubleArray2DTypeHandler;
import com.lyc.typeHandler.VectorTypeHandler;

import java.io.Serializable;
import java.util.Date;


@TableName(value = "seeta_face_info", autoResultMap = true)
public class FaceInfo implements Serializable {
    @TableId(type = IdType.AUTO)
    private Integer id;
    // 文件名
    private String fileName;

    // 文件路径
    private String filePath;

    // 人脸向量特征
    @TableField(typeHandler = VectorTypeHandler.class)
    private float[] features;
    // SeetaRect 人脸在图片中的位置和长宽
    public Integer x;
    public Integer y;
    public Integer width;
    public Integer height;

    // 人脸关键点，相对于原始图片的位置
    @TableField(typeHandler = DoubleArray2DTypeHandler.class)
    private double[][] points;

    // 创建时间
    private Date createTime;

    // 更新时间
    private Date updateTime;

    // get set省略了

}

创建类型转换器

package com.lyc.typeHandler;

import org.apache.ibatis.type.BaseTypeHandler;
import org.apache.ibatis.type.JdbcType;
import org.postgresql.util.PGobject;

import java.sql.CallableStatement;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

/**
 * pgsql 中向量类型转成float数组
 * 很多向量是double类型的，seetaface6是float类型的
 */
public class VectorTypeHandler extends BaseTypeHandler<float[]> {

    @Override
    public void setNonNullParameter(PreparedStatement ps, int i, float[] parameter, JdbcType jdbcType) throws SQLException {
        PGobject vector = new PGobject();
        vector.setType("vector");
        StringBuilder sb = new StringBuilder();
        //
        sb.append("[");
        for (int j = 0; j < parameter.length; j++) {
            if (j > 0) sb.append(",");
            sb.append(parameter[j]);
        }
        sb.append("]");
        vector.setValue(sb.toString());
        ps.setObject(i, vector);
    }

    @Override
    public float[] getNullableResult(ResultSet rs, String columnName) throws SQLException {
        String vectorString = rs.getString(columnName);
        if (vectorString == null) {
            return null;
        }
        return parseVectorString(vectorString);
    }

    @Override
    public float[] getNullableResult(ResultSet rs, int columnIndex) throws SQLException {
        String vectorString = rs.getString(columnIndex);
        if (vectorString == null) {
            return null;
        }
        return parseVectorString(vectorString);
    }

    @Override
    public float[] getNullableResult(CallableStatement cs, int columnIndex) throws SQLException {
        String vectorString = cs.getString(columnIndex);
        if (vectorString == null) {
            return null;
        }
        return parseVectorString(vectorString);
    }

    private float[] parseVectorString(String vectorString) {
        vectorString = vectorString.substring(1, vectorString.length() - 1); // Remove the curly braces
        String[] parts = vectorString.split(",");
        float[] vector = new float[parts.length];
        for (int i = 0; i < parts.length; i++) {
            vector[i] = Float.parseFloat(parts[i].trim());
        }
        return vector;
    }

}

package com.lyc.typeHandler;

import org.apache.ibatis.type.BaseTypeHandler;
import org.apache.ibatis.type.JdbcType;
import org.postgresql.util.PGobject;

import java.sql.CallableStatement;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

/**
 * pgsql二维数组转换，点坐标
 */
public class DoubleArray2DTypeHandler extends BaseTypeHandler<double[][]> {

    @Override
    public void setNonNullParameter(PreparedStatement ps, int i, double[][] parameter, JdbcType jdbcType) throws SQLException {
        PGobject pgo = new PGobject();
        pgo.setType("float8[]");
        pgo.setValue(arrayToString(parameter));

        ps.setObject(i, pgo, JdbcType.OTHER.TYPE_CODE);
        //ps.setObject(i, pgo);
    }

    @Override
    public double[][] getNullableResult(ResultSet rs, String columnName) throws SQLException {
        String value = rs.getString(columnName);
        if (value == null) {
            return null;
        }
        return stringToArray(value);
    }

    @Override
    public double[][] getNullableResult(ResultSet rs, int columnIndex) throws SQLException {
        String value = rs.getString(columnIndex);
        if (value == null) {
            return null;
        }
        return stringToArray(value);
    }

    @Override
    public double[][] getNullableResult(CallableStatement cs, int columnIndex) throws SQLException {
        String value = cs.getString(columnIndex);
        if (value == null) {
            return null;
        }
        return stringToArray(value);
    }

    private String arrayToString(double[][] array) {
        StringBuilder sb = new StringBuilder("{");
        for (double[] row : array) {
            sb.append("{");
            for (double value : row) {
                sb.append(value).append(",");
            }
            sb.setLength(sb.length() - 1); // Remove the last comma
            sb.append("},");
        }
        sb.setLength(sb.length() - 1); // Remove the last comma
        sb.append("}");
        return sb.toString();
    }

    private double[][] stringToArray(String value) {
        value = value.substring(1, value.length() - 1); // Remove outer braces
        String[] rows = value.split("\\},\\{");
        double[][] array = new double[rows.length][];

        for (int i = 0; i < rows.length; i++) {
            String row = rows[i];
            row = row.trim(); // Remove leading and trailing whitespace
            if (row.startsWith("{")) {
                row = row.substring(1);
            }
            if (row.endsWith("}")) {
                row = row.substring(0, row.length() - 1);
            }

            String[] values = row.split(",");
            array[i] = new double[values.length];
            for (int j = 0; j < values.length; j++) {
                array[i][j] = Double.parseDouble(values[j].trim());
            }
        }
        return array;
    }
}

mybatis mapper, bo对象只是加了个score分数字段

package com.lyc.mapper;

import com.baomidou.mybatisplus.core.mapper.BaseMapper;
import com.lyc.entities.FaceInfo;
import com.lyc.entities.FaceInfoBo;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import org.apache.ibatis.annotations.Select;
import org.apache.ibatis.annotations.Update;

import java.util.List;

@Mapper
public interface FaceInfoMapper extends BaseMapper<FaceInfo> {

    /**
     * 大模型回答：
     * 当你在每次查询之前执行 SET pgvector.ef_search = 200; 这条 SQL 语句时，你是在设置一个会话级别的参数，该参数会影响随后执行的向量相似度搜索的性能和准确性。以下是这条语句的具体作用：
     * 1.提高查询准确性：通过将 ef_search 设置为较高的值（如 200），你可以让查询算法检查更多的候选点，从而提高找到最相似向量的准确性。
     * 2.影响查询性能：虽然更高的 ef_search 值可以提高准确性，但它也会增加查询时间，因为需要处理更多的候选点。因此，你需要在这两者之间找到一个平衡点。
     * 3.会话级别设置：SET 语句是会话级别的，这意味着它只对当前会话有效。如果你有多个并发查询，每个查询都可以独立设置不同的 ef_search 值。
     */
    @Update("SET pgvector.ef_search = 200")
    void setEfSearch();

    /**
     * 向量余弦相似度搜索
     * @param targetFeatures 输入的向量
     * @param topN 返回最接近的前N个
     * @return list
     */
    @Select("SELECT *, (1 - (features <=> #{targetFeatures})) as score FROM public.seeta_face_info " +
            "ORDER BY features <=> #{targetFeatures} " +
            "LIMIT ${topN}")
    List<FaceInfoBo> queryByFeatures(@Param("targetFeatures") float[] targetFeatures, @Param("topN") int topN);

  
}

serviceImpl,保存和查询

package com.lyc.service.impl;

import cn.hutool.core.io.FileUtil;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import com.lyc.entities.FaceInfo;
import com.lyc.entities.FaceInfoBo;
import com.lyc.mapper.FaceInfoMapper;
import com.lyc.service.FaceInfoService;
import com.lyc.service.FileManageService;
import com.lyc.service.Seetaface6Service;
import com.qiwenshare.ufop.operation.upload.domain.UploadFileResult;
import org.apache.ibatis.executor.BatchResult;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.stereotype.Service;
import org.springframework.web.multipart.MultipartFile;

import javax.annotation.Resource;
import javax.servlet.http.HttpServletRequest;
import java.io.File;
import java.util.List;

@Service
public class FaceInfoServiceImpl implements FaceInfoService {

    Logger logger = LoggerFactory.getLogger(FaceInfoServiceImpl.class);

    @Resource
    FaceInfoMapper faceInfoMapper;

    /**
     * 人脸解释器
     */
    @Resource
    Seetaface6Service seetaface6Service;

    /**
     * 需要上传文件的话可以用这个
     */
    @Resource
    FileManageService fileManageService;

    @Override
    public FaceInfo getOne(Integer id) {

        return faceInfoMapper.selectById(id);
    }

    @Override
    public int save(FaceInfo faceInfo) {

        return faceInfoMapper.insert(faceInfo);
    }

    @Override
    public int save(String path) throws Exception {

        File file = new File(path);

        boolean exist = FileUtil.exist(file);
        if (exist) {
            // 一张照片可能有多个人脸
            List<FaceInfo> faceInfoList = seetaface6Service.getFaceInfo(file);
            if (faceInfoList != null && !faceInfoList.isEmpty()) {

                // 批量保存
                List<BatchResult> insert = faceInfoMapper.insert(faceInfoList);
                logger.info("insert： {}", insert);
                return insert.size();
            }
            return 0;
        } else {
            logger.error("文件不存在： {}", file.getAbsolutePath());
        }
        return 0;
    }

    @Override
    public int save(MultipartFile face, HttpServletRequest servletRequest) throws Exception {
        // 上传到本地文件服务
        List<UploadFileResult> uploadFileResults = fileManageService.uploadFile(servletRequest);
        if (uploadFileResults != null && !uploadFileResults.isEmpty()) {
            UploadFileResult uploadFileResult = uploadFileResults.get(0);
            List<FaceInfo> faceInfo = seetaface6Service.getFaceInfo(face, uploadFileResult.getFileUrl());
            if (faceInfo != null && !faceInfo.isEmpty()) {
                // 批量保存
                List<BatchResult> insert = faceInfoMapper.insert(faceInfo);
                logger.info("insert： {}", insert);
                return insert.size();
            }
        }
        return 0;
    }

    @Override
    public List<FaceInfo> getAll() {
        return faceInfoMapper.selectList(new QueryWrapper<>());
    }

    @Override
    public List<FaceInfoBo> queryTopN(MultipartFile face, int topN) {

        float[] oneFaceFeature = seetaface6Service.getOneFaceFeature(face);

        if (oneFaceFeature != null && oneFaceFeature.length > 0) {
            FaceInfo faceInfo = new FaceInfo();
            faceInfo.setFeatures(oneFaceFeature);

            // 设置参数，session 范围内有效
            faceInfoMapper.setEfSearch();
            // 执行向量查询
            List<FaceInfoBo> list = faceInfoMapper.queryByFeatures(oneFaceFeature, topN);

            // 这里可以做一下其他业务操作
            // .....

            return list;
        }

        return null;
    }


}

建表语句

-- 进入PostgreSQL数据库后，使用以下命令启用PGVector扩展
CREATE EXTENSION IF NOT EXISTS vector;

-- ----------------------------
-- Table structure for seeta_face_info
-- ----------------------------
-- 人脸信息表
CREATE TABLE IF NOT EXISTS public.seeta_face_info (
    id SERIAL PRIMARY KEY, -- 自增ID
    features vector(1024), -- 显式指定向量的维度， 维度根据自己的人脸模型而定，有256，516，1024等维度
    file_name varchar(127),
    file_path varchar(256),
    x int4,
    y int4,
    width int4,
    height int4,
    create_time date,
    update_time date,
    points float8[][]
);

COMMENT ON COLUMN "public"."seeta_face_info"."id" IS '自增ID';
COMMENT ON COLUMN "public"."seeta_face_info"."features" IS '人脸向量';
COMMENT ON COLUMN "public"."seeta_face_info"."file_name" IS '原始文件名';
COMMENT ON COLUMN "public"."seeta_face_info"."file_path" IS '文件保存路径';
COMMENT ON COLUMN "public"."seeta_face_info"."x" IS '人脸在图片中的x轴位置';
COMMENT ON COLUMN "public"."seeta_face_info"."y" IS '人脸在图片中的y轴位置';
COMMENT ON COLUMN "public"."seeta_face_info"."width" IS '宽';
COMMENT ON COLUMN "public"."seeta_face_info"."height" IS '高';
COMMENT ON COLUMN "public"."seeta_face_info"."create_time" IS '创建时间';
COMMENT ON COLUMN "public"."seeta_face_info"."update_time" IS '更新时间';
COMMENT ON COLUMN "public"."seeta_face_info"."points" IS '人脸五点关键点';

-- ----------------------------
-- Records of seeta_face_info
-- ----------------------------
-- 添加一条测试数据
INSERT INTO "public"."seeta_face_info" ( "features", "file_name", "file_path", "x", "y", "width", "height", "create_time", "update_time", "points") VALUES ('[0.012936536,0,0.007195695,0.0010175805,0,0.007792639,0.015118308,0.011674433,0.009080521,0.014190655,0.044781953,0,0,0.02231579,0.0028997012,0.014974379,0.012804734,0.0037977195,0.0076714647,0.094358526,0.008663135,0.009487498,0.0055931387,0,0.018194415,0.008644766,0.086220555,0.009462898,0,0,0.0071884613,0.017078964,0.005971099,0.037262347,0,0.011930267,0.020462526,0.008314524,0.008506452,0,0.08382535,0.0043841833,0.01740133,0.012599094,0.024398023,0,0.022921681,0.035706557,0.007167895,0,0,0.01608521,0,0.014278957,0,0.05967452,0.005382457,0.009898098,0.028123062,0.10590437,0,0.018057222,0.016698858,0,0.0042912154,0.05017243,0,0.012554585,0,0.017572744,0.010788352,0.013510452,0,0.0068368926,0.028482487,0.03135618,0.010059538,0.013481353,0.008319363,0,0,0.003842533,0,0.015337106,0,0.012159346,0,0,0,0.02166239,0,0.016810121,0,0.002882563,0.014977325,0,0,0,0.028035989,0.054355,0.06605609,0.006695213,0.008298104,0.0070924135,0.010430695,0.052303135,0,0.013470027,0.012022528,0,0.051299147,0,0.058759604,0.010825306,0.018810216,0.009120669,0,0,0,0.021069858,0.06479335,0.010269384,0.022222854,0.0031150924,0,0.07087145,0.015606145,0.042596396,0.008097757,0.04202775,0.09486199,0.00927597,0,0.009832303,0.010240598,0.02286381,0.01631102,0.037719354,0.034105,0.09498593,0.010083296,0,0.03363972,0.091432266,0,0.0136626,0,0.060525417,0,0.0053605065,0.0141740525,0.053591624,0.022475224,0,0.044024613,0,0,0,0.047528785,0,0.041255392,0,0.026546773,0.016530082,0,0.013645481,0,0.018284744,0,0.049734954,0.013108354,0.0049782405,0.0034352227,0.054873597,0.005992258,0.027922483,0.062608026,0,0,0.009454261,0.063707955,0.08825763,0,0,0,0.0035791588,0.03670636,0.027578294,0.004111979,0.016055308,0.022207845,0.013669315,0.0184831,0.07337876,0.0060850573,0.04881681,0,0.0046898867,0,0.017978372,0,0.013703404,0.050636627,0.016924303,0.011133711,0.032126762,0.009875268,0,0.006539482,0.04149861,0.014229679,0.014637744,0.013330922,0.013252046,0.059673995,0,0,0.021640522,0.06237336,0.04687985,0,0.004836014,0.05147407,0.08285213,0,0.065025195,0.005084097,0.013403868,0,0.04430367,0.035835903,0,0,0.011138198,0,0.007573752,0.065894485,0,0.011623726,0.061509542,0.023587737,0.050479546,0.062357567,0.012624956,0.18149832,0,0.00991907,0.008969357,0.019379236,0.017703474,0.014122228,0.012409378,0.015835313,0.014909128,0.015797265,0.023986887,0.03605708,0,0.00484181,0.009798406,0,0.059107587,0.018749353,0.019966034,0.00075713336,0,0.009042693,0.04916493,0.024364747,0.0040479815,0.06552736,0.005386103,0.0149867395,0.009196071,0.059709586,0.110087544,0.03433313,0.004109531,0,0,0,0,0.03006751,0.04320631,0,0.04058286,0.023070406,0,0.003243711,0.02739622,0.0068308455,0,0.010815314,0.009077117,0.012960999,0.04238911,0.11240821,0.024731508,0.0069392575,0.01047473,0.086186536,0.006744124,0.06877251,0.027786484,0,0,0.01919137,0.035305697,0,0.014672417,0,0.010933243,0.014637537,0,0.010504993,0.010986123,0.011860298,0.014868989,0.023254147,0,0,0,0,0.026480256,0.0016338569,0.020332512,0.02371761,0.015045777,0,0,0,0,0,0.0053659203,0.011822672,0,0.0418138,0.00969026,0.013813995,0.017136646,0.011614178,0.06715224,0.012186076,0.004297241,0,0.08306359,0.030226767,0.008540841,0.03748476,0.01408638,0.076160826,0.011186378,0.0038412164,0.0055577685,0,0.008968809,0.0072584567,0,0.011027888,0.036231082,0,0.031956665,0.036360916,0.015415539,0.13346262,0,0,0.0083580855,0.023822602,0,0.027539948,0,0.01437315,0.023282068,0,0.00447503,0,0.011323216,0.0060033617,0.06053584,0,0.010618792,0,0.010148928,0.017687304,0,0.04178323,0.038190316,0,0.013922283,0,0.026840324,0.020681903,0.0040813996,0,0,0.0104454495,0.13480082,0.014522614,0,0.05382975,0.008104056,0.0048422986,0.043376617,0.0075269663,0,0.0074544055,0.015421718,0,0.007237645,0.011400381,0,0.0060491944,0.031341672,0.017193757,0,0,0.01113649,0.0035488072,0.01090996,0.014570169,0,0.028932387,0,0.01049893,0.010295641,0.052135974,0,0,0,0.08585738,0.009569165,0,0.016140802,0,0,0,0.01856908,0.010976821,0.008810176,0.006731395,0.015923157,0.01686836,0.012791781,0.010417162,0.015028711,0.006390597,0.018609561,0.060831644,0,0,0.00914265,0.026932271,0.014621711,0.0017739309,0,0.039525736,0.017013721,0.008868712,0.0037233206,0.007595041,0,0,0.07526842,0.012743788,0.00583687,0.012538236,0,0,0.0069439476,0.020589983,0.025325656,0.012636953,0.007814401,0.112313606,0.05582911,0.06509585,0,0.016695222,0,0.011220647,0.011739086,0.028447311,0,0.020543499,0.061481602,0,0.003007268,0.010969699,0,0.02220266,0.059171494,0.011578273,0,0.01423173,0,0.024742452,0,0.008418887,0.0099330945,0.008668409,0.0073191784,0,0,0,0,0.005542668,0.010724416,0.0012712771,0.08968355,0.0019512589,0.069424525,0.09707316,0.025636597,0,0.019025654,0.0065706577,0.02629586,0.019322807,0.0059510753,0.03560242,0.011190751,0.009083113,0,0,0,0.11616014,0.011153892,0.029643577,0,0.08584766,0.0011586623,0.012883163,0.006347931,0.064442284,0.007183812,0,0.043087702,0.009957424,0.082864076,0.1350576,0.0068540527,0.008172071,0.025571685,0.008150873,0,0.11180381,0.020926114,0.09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'李俊.jpg', 'upload/20241023/de9b2482-fe13-4697-96c1-06aba8dac72b.jpg', 521, 501, 296, 399, '2024-10-23', '2024-10-23', '{{590.1159049770085,665.3062513372861},{736.8112287976801,663.8625748373834},{661.2410654412943,740.2610476701484},{611.6704869216974,812.4751519212405},{713.8414231123716,811.3582018521156}}');

创建向量索引

-- 创建向量索引，向量搜索更快
CREATE INDEX idx_seeta_face_info_features_hnsw ON public.seeta_face_info USING hnsw (features vector_cosine_ops) WITH (m = 32, ef_construction = 200);

代码地址：https://gitee.com/crazy-of-pig/spring-boot-seetaface6.git