虹软1:N 基于mysql的插件udf查询速度优化。。。。

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环境

linux x64

刚开始是将人脸特征数据全部加载到内存，然后遍历内存，进行比较。

后面偶尔看到了 mysql UDF(Userdefined function)的开发，用户自定义函数

#include <mysql.h>
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include <string.h>
#include "udf_face_comparison.h"
#include "arcsoft_face_sdk.h"
#include "amcomdef.h"
#include "asvloffscreen.h"
#include "merror.h"
using namespace std;

#define APPID "HnS2rSQq1ewRDDLsdz5KuTNvyoTbMm8rX2jFqZkpd4Fa"
#define SDKKEY "CmEstwumE52p5zGSBt8CJtkQtk5fSpqGm8M8ZxZFFuXt"
#define ACTIVEKEY "8281-1111-M125-XXKM"

#define NSCALE 16 
#define FACENUM	5
#define SafeFree(p) { if ((p)) free(p); (p) = NULL; }
#define SafeArrayDelete(p) { if ((p)) delete [] (p); (p) = NULL; } 
#define SafeDelete(p) { if ((p)) delete (p); (p) = NULL; } 
MHandle faceHandle = 0;

const char * base64char = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
int base64_decode( const char * base64, unsigned char * bindata )
{
    int i, j;
    unsigned char k;
    unsigned char temp[4];
    for ( i = 0, j = 0; base64[i] != '\0' ; i += 4 )
    {
        memset( temp, 0xFF, sizeof(temp) );
        for ( k = 0 ; k < 64 ; k ++ )
        {
            if ( base64char[k] == base64[i] )
                temp[0]= k;
        }
        for ( k = 0 ; k < 64 ; k ++ )
        {
            if ( base64char[k] == base64[i+1] )
                temp[1]= k;
        }
        for ( k = 0 ; k < 64 ; k ++ )
        {
            if ( base64char[k] == base64[i+2] )
                temp[2]= k;
        }
        for ( k = 0 ; k < 64 ; k ++ )
        {
            if ( base64char[k] == base64[i+3] )
                temp[3]= k;
        }

        bindata[j++] = ((unsigned char)(((unsigned char)(temp[0] << 2))&0xFC)) |
                ((unsigned char)((unsigned char)(temp[1]>>4)&0x03));
        if ( base64[i+2] == '=' )
            break;

        bindata[j++] = ((unsigned char)(((unsigned char)(temp[1] << 4))&0xF0)) |
                ((unsigned char)((unsigned char)(temp[2]>>2)&0x0F));
        if ( base64[i+3] == '=' )
            break;

        bindata[j++] = ((unsigned char)(((unsigned char)(temp[2] << 6))&0xF0)) |
                ((unsigned char)(temp[3]&0x3F));
    }
    return j;
}

extern "C" double face_comparison(UDF_INIT *initid, UDF_ARGS *args, char *is_null, char *error)
{
    
    MRESULT res = MOK;
    if(faceHandle == 0){
        return -1.0;
    }
    unsigned char bindata[2048];
    int iRet = base64_decode(args->args[0], bindata);
    ASF_FaceFeature feature1 = {0}, feature2 = {0};
    feature1.feature = (MByte *)malloc(iRet); 
    feature1.featureSize = iRet;

	memcpy(feature1.feature, bindata, feature1.featureSize);

    feature2.feature = (MByte *)malloc(args->lengths[1]); 
    feature2.featureSize = args->lengths[1];
  	memcpy(feature2.feature, args->args[1], feature2.featureSize);

    MFloat confidenceLevel = 0.0f;
    res = ASFFaceFeatureCompare(faceHandle, &feature1, &feature2, &confidenceLevel);

    printf("dqist_face_comparison_init_init");
    SafeFree(feature1.feature);		//释放内存
    SafeFree(feature2.feature);		//释放内存


    return confidenceLevel;
}


extern "C"  my_bool face_comparison_init(UDF_INIT *inited, UDF_ARGS *args, char*message)
{
    inited->decimals = 2;
    MRESULT res = MOK;
    res = ASFOnlineActivation(APPID,SDKKEY);
	MInt32 mask =  ASF_FACERECOGNITION;
	res = ASFInitEngine(ASF_DETECT_MODE_IMAGE, ASF_OP_0_ONLY, NSCALE, FACENUM, mask, &faceHandle);
    return 0;
}
extern "C" void face_comparison_deinit(UDF_INIT *inited)
{
        printf("face_comparison_init_init");
}

int test()
{
    printf("hello worlod");
    return 3;
}

drop FUNCTION face_comparison;
CREATE FUNCTION face_comparison RETURNS REAL SONAME 'libudf_face_comparison.so';
SELECT  face_comparison('base64', feature_data) from face.face  

这样就可以将模型比较放在sql 语句本身的执行里。

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