派生自 ruleprocess
ruleserver/readyDataForRule.go
@@ -3,12 +3,11 @@ import ( "basic.com/dbapi.git" "basic.com/pubsub/protomsg.git" "basic.com/valib/logger.git" "encoding/json" "errors" "fmt" "basic.com/valib/logger.git" "github.com/golang/protobuf/proto" uuid "github.com/satori/go.uuid" "math" "nanomsg.org/go-mangos" "nanomsg.org/go-mangos/protocol/req" @@ -93,35 +92,6 @@ //logger.Info("初步保留两位成str::::",value2) return value2 } // 取出某个时间规则的第几天的规则段集合 func GetTimeById(id string, index int) []structure.TimeRange { _, cameraTimeRule := cache.GetTimeRuleById(id) var timeRangeList []structure.Day err := json.Unmarshal([]byte(cameraTimeRule.TimeRule), &timeRangeList) if err != nil { logger.Error("取时间规则时反序列化错误！") } for _, timerange := range timeRangeList { if timerange.Day == index { //logger.Println("取到的时间规则：", timerange.TimeRange) return timerange.TimeRange } } return nil } // 根据传入的字符串得到其在一周内的索引 周一到周日分别对应1到7 func getIndexOfWeek(weekday string) int { var weekdays = [7]string{"Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"} for k, value := range weekdays { if value == weekday { return k + 1 // 因为数据库中存的是1-7代表的周一到周日 } } return 0 } // 将字符串格式的坐标序列化为Point格式 func Json2points(areaPoints string) []structure.Point { @@ -186,8 +156,8 @@ if err != nil || len(table) == 0 { logger.Error("根据id查询底库信息出错！", err, "--返回值长度为：", len(table)) } logger.Debug("看看这个base的对比值是多少：", Decimal(m[baseinfo.Id].CompareScore)) base := structure.BaseInfo{TableId: baseinfo.TableId, TableName: table[0].TableName, BwType: table[0].BwType, CompareScore: Decimal(m[baseinfo.Id].CompareScore), PersonId: baseinfo.Id, PersonName: baseinfo.PersonName, PersonPicUrl: baseinfo.PersonPicUrl, PhoneNum: baseinfo.PhoneNum, Sex: baseinfo.Sex, IdCard: baseinfo.IdCard, MonitorLevel: baseinfo.MonitorLevel, Content: baseinfo.Reserved} //logger.Debug("看看这个base的对比值是多少：", Decimal(m[baseinfo.Id].CompareScore)) base := structure.BaseInfo{TableId: baseinfo.TableId, TableName: table[0].TableName, BwType: table[0].BwType, CompareScore: Decimal(m[baseinfo.Id].CompareScore), TargetId: baseinfo.Id, TargetName: baseinfo.PersonName, TargetPicUrl: baseinfo.PersonPicUrl, MonitorLevel: baseinfo.MonitorLevel, Content: baseinfo.Reserved,DbLabel: baseinfo.PhoneNum+"/"+baseinfo.Sex+"/"+baseinfo.IdCard,} //os.Exit(1) arg.Liker = append(arg.Liker, &base) } @@ -213,7 +183,7 @@ if groupRule.Rules[j].SdkArgAlias == "cmpThreshold" { v2, err := strconv.ParseFloat(groupRule.Rules[j].SdkArgValue, 32) if err != nil { logger.Error("string转float32失败！") //logger.Error("string转float32失败！") } threshold = float32(v2) } @@ -222,15 +192,15 @@ // 为了测试作下弊，直接让其比对全部底库 //compareFlag = 1 if compareFlag == 0 { logger.Info("没有配置对比底库参数") //logger.Info("没有配置对比底库参数") return } logger.Debug("=====配置的阈值为：", threshold) //logger.Debug("=====配置的阈值为：", threshold) for j := 0; j < len(groupRule.Rules); j++ { if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { for _, sdkData := range args.Sdkdata { if sdkData.IpcId == "A8B73405-373D-4F23-CED2-A617EBD7EC55" { // 搜索到人脸检测的sdkdata 现在关于人脸的只有他一个sdk，全找他 logger.Info("============================================进行人脸对比") //logger.Info("============================================进行人脸对比") for _, areaMap := range sdkData.AreaMapList { // 拿区域中每个人脸特征值去对比，填充其liker if groupRule.Rules[j].PolygonId == areaMap.AreaId { @@ -258,48 +228,48 @@ } // 计算区域内的目标数量以及将相似度、占比、尺寸等打包 func CountAreaObjs(a *structure.AreaMap,arg *structure.SdkData) { a.TargetNum = 0 threshold := 80.0 // 相似度 intersectionper := 0.2 // 占比 size := 0.0 // 尺寸 areaPoints := Json2points(a.AreaJson) logger.Info("看看图片的width和height:",arg.ImageWidth,arg.ImageHeight) widthScale := float64(arg.ImageWidth) / 960 heigthScale := float64(arg.ImageHeight) / 540 for _, obj := range arg.Photo { //logger.Info("------------------看看sdkData:", arg.SdkName, "的Photo数据----------------", obj, "----顺便看看占比-----：", PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale)) if obj.Score >= threshold && float64(obj.Rects.Width*obj.Rects.Height) >= size && PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale) >= intersectionper { // 这步要备齐表达式里所需要的所有参数 a.TargetNum++ uuid := uuid.NewV4().String() arg1 := structure.Arg{obj.Id,uuid,obj.Score, PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale), float64(obj.Rects.Width * obj.Rects.Height), a.AreaJson,obj.IsYolo, obj.Rects, obj.Feature, obj.ThftRes, []*structure.BaseInfo{},nil} //logger.Println("放进去的arg：-------", arg1) a.Args = append(a.Args, &arg1) a.FilterData = append(a.FilterData, &arg1) } } logger.Info("区域是：",areaPoints,"区域内目标数量为：",a.TargetNum,"---",len(a.FilterData)) a.Time = time.Unix(time.Now().Unix(), 0).String()[11:16] //logger.Println("--------------------看看区域数据：",*a) } // 把sdk从数据帧上提取的按照区域分类归置 func SdkDataFormat(cameraId string, arg *structure.SdkData, cameraPolygons []protomsg.CameraPolygon) { logger.Info("==================================本sdkData中解出来的目标数据=======================================") for _, photo := range arg.Photo { logger.Info("--------解析出来的数据---", cameraId, arg.IpcId, photo.Rects, photo.Score) } for _, polygon := range cameraPolygons { //logger.Println("++++++在这儿看一下区域啊:", polygon.Polygon) areaMap := structure.AreaMap{CameraId: cameraId, AreaId: polygon.Id, AreaJson: polygon.Polygon, TriggerLine: polygon.TriggerLine, DirectionLine: polygon.DirectionLine} // 为每个摄像机区域填充数据 CountAreaObjs(&areaMap,arg) arg.AreaMapList = append(arg.AreaMapList, &areaMap) } } //func CountAreaObjs(a *structure.AreaMap,arg *structure.SdkData) { // // a.TargetNum = 0 // threshold := 80.0 // 相似度 // intersectionper := 20.0 // 占比 // size := 0.0 // 尺寸 // // areaPoints := Json2points(a.AreaJson) // logger.Info("看看图片的width和height:",arg.ImageWidth,arg.ImageHeight) // widthScale := float64(arg.ImageWidth) / 960 // heigthScale := float64(arg.ImageHeight) / 540 // for _, obj := range arg.Photo { // //logger.Info("------------------看看sdkData:", arg.SdkName, "的Photo数据----------------", obj, "----顺便看看占比-----：", PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale)) // if obj.Score >= threshold && float64(obj.Rects.Width*obj.Rects.Height) >= size && PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale) >= intersectionper { // // 这步要备齐表达式里所需要的所有参数 // a.TargetNum++ // uuid := uuid.NewV4().String() // arg1 := structure.Arg{obj.Id,uuid,obj.Score, PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale), float64(obj.Rects.Width * obj.Rects.Height), a.AreaJson,obj.Type, obj.Rects, obj.Car,obj.Feature, obj.ThftRes, []*structure.BaseInfo{},"",structure.ResultMsg{}} // //logger.Println("放进去的arg：-------", arg1) // a.Args = append(a.Args, &arg1) // a.FilterData = append(a.FilterData, &arg1) // } // } // //logger.Info("区域是：",areaPoints,"区域内目标数量为：",a.TargetNum,"---",len(a.FilterData)) // a.Time = time.Unix(time.Now().Unix(), 0).String()[11:16] // //logger.Println("--------------------看看区域数据：",*a) //} // //// 把sdk从数据帧上提取的按照区域分类归置 //func SdkDataFormat(cameraId string, arg *structure.SdkData, cameraPolygons []protomsg.CameraPolygon) { // logger.Info("==================================本sdkData中解出来的目标数据=======================================") // for _, photo := range arg.Photo { // logger.Info("--------解析出来的数据---", cameraId, arg.IpcId, photo.Rects, photo.Score) // } // for _, polygon := range cameraPolygons { // //logger.Println("++++++在这儿看一下区域啊:", polygon.Polygon) // areaMap := structure.AreaMap{CameraId: cameraId, AreaId: polygon.Id, AreaJson: polygon.Polygon, TriggerLine: polygon.TriggerLine, DirectionLine: polygon.DirectionLine} // // 为每个摄像机区域填充数据 // CountAreaObjs(&areaMap,arg) // arg.AreaMapList = append(arg.AreaMapList, &areaMap) // } //} func Push(data *protomsg.CompareArgs,sock mangos.Socket) []byte{ //var sock mangos.Socket @@ -373,19 +343,16 @@ logger.Info("序列化失败：",err1) } logger.Debug("推送数据") //bytes := []byte("ndfasojdfaidsos") if err = sock.Send(bytes); err != nil { logger.Error("推送socket发送数据失败: %s", err.Error()) //os.Exit(1) } if msg, err = sock.Recv(); err != nil { logger.Error("接收响应失败: %s", err.Error()) //os.Exit(1) } logger.Debug("数据推送成功！收到响应,数据长度为：",len(msg)) receiver <- msg default: time.Sleep(time.Millisecond * 10) } } }
