派生自 ruleprocess
ruleserver/ruleToformula.go
@@ -2,7 +2,6 @@ import ( "encoding/json" "fmt" "ruleprocess/cache" "ruleprocess/logger" "sort" @@ -11,12 +10,15 @@ "time" bigCache "basic.com/pubsub/cache.git" "basic.com/pubsub/cache.git/esutil" "basic.com/pubsub/protomsg.git" "github.com/knetic/govaluate" ) func init () { func init() { bigCache.Init() } // 任务 type Task struct { camID string //摄像机ID @@ -65,7 +67,6 @@ Size float64 // 区域内的目标的尺寸 IsYolo bool // 是否是yolo数据 Location Rect // 记下每个目标的位置参数，最后给结果装配人脸数据的时候用的到 SdkName string Feature []byte ThftRes protomsg.ThftResult Liker []*protomsg.Baseinfo @@ -100,7 +101,6 @@ Rects Rect // 矩形区域参数 Score float64 // 相似度得分（有多大程度像一个目标。人脸，人体或车等等） IsYolo bool // 是否是yolo数据 SdkName string ThftRes protomsg.ThftResult Feature []byte } @@ -108,8 +108,7 @@ // 每个算法对于当前帧画面自己提取的数据 type SdkData struct { TaskId string SdkId string SdkName string IpcId string IsYolo bool Photo []PhotoMap // yolo算法结构，也可以存人脸的数据，毕竟人脸中能用规则来测的还是那些参数 KeepRight bool // 是否靠右行 算法判断的与上一帧图像的比较结果 @@ -185,6 +184,7 @@ // 把sdk从数据帧上提取的按照区域分类归置 func SdkDataFormat(cameraId string, arg *SdkData, cameraPolygons []protomsg.CameraPolygon) { logger.Info("--------看看解析出来的数据---", *arg) for _, polygon := range cameraPolygons { //logger.Println("++++++在这儿看一下区域啊:", polygon.Polygon) areaMap := AreaMap{cameraId: cameraId, areaId: polygon.Id, areaJson: polygon.Polygon, triggerLine: polygon.TriggerLine, directionLine: polygon.DirectionLine} @@ -233,37 +233,69 @@ } } func Compare(args *SdkDatas, groupRule *protomsg.GroupRule) { compareFlag := false compareFlag := 0 tableIds := "" // 看看是否有只配人脸比对算法但没有配对比库的规则，如果有，则比对对象为全部底库 for j := 0; j < len(groupRule.Rules); j++ { if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { if groupRule.Rules[j].SdkArgAlias == "compareBase" { compareFlag = true if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { // 配了人脸比对 if groupRule.Rules[j].SdkArgAlias == "compareBase" && groupRule.Rules[j].SdkArgValue != "" { // 配了比对底库的参数但没有配全部底库 compareFlag = 2 tableIds = groupRule.Rules[j].SdkArgValue + "," // 最后会多一个tableId，切出来的数组取len-1就可以 } if groupRule.Rules[j].SdkArgAlias == "compareBase" && groupRule.Rules[j].SdkArgValue == "" { // 配的参数是比对全部底库 compareFlag = 1 } } } if compareFlag { logger.Info("配置了对比底库参数") } else { // 作弊，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") return } for j := 0; j < len(groupRule.Rules); j++ { // 只有是人脸对比并且配置的参数是对比底库才走（若配的对比阈值则不走） if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972" && groupRule.Rules[j].SdkArgAlias == "compareBase" { if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972"{ for _, sdkData := range args.Sdkdata { if sdkData.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" { // 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 if sdkData.IpcId == "812b674b-2375-4589-919a-5c1c3278a97e" { // 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 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 { for _, arg := range areaMap.args { bytes := bigCache.Getdbpersonmsg("", arg.Feature, true) var m map[string]float32 json.Unmarshal(bytes, &m) for key, val := range m { fmt.Println(key) baseinfo := protomsg.Baseinfo{} baseinfo.CompareScore = val arg.Liker = append(arg.Liker, &baseinfo) if compareFlag == 1 { bytes := bigCache.Getdbpersonmsg("", arg.Feature, true) var m map[string]float32 err1 := json.Unmarshal(bytes, &m) if err1 != nil { logger.Error("getBaseInfo解压错误", err1) } for key, val := range m { baseinfo,err1 := esutil.Dbpersoninfosbyid(key) if err1 != nil { logger.Error("查询底库人员信息出错",err1) } baseinfo.CompareScore = val arg.Liker = append(arg.Liker, &baseinfo) } } if compareFlag == 2 { array := strings.Split(tableIds, ",") for i := 0; i < len(array)-1; i++ { bytes := bigCache.Getdbpersonmsg(array[i], arg.Feature, true) var m map[string]float32 err1 := json.Unmarshal(bytes, &m) if err1 != nil { logger.Error("getBaseInfo解压错误", err1) } for key, val := range m { baseinfo, err1 := esutil.Dbpersoninfosbyid(key) if err1 != nil { logger.Error("查询底库人员信息出错",err1) } baseinfo.CompareScore = val arg.Liker = append(arg.Liker, &baseinfo) } } } logger.Info("-------------------成功给liker赋值：", arg.Liker) } @@ -283,14 +315,30 @@ logger.Info("+++++++++++规则开始运行+++++++++++++++++当前规则--：", *groupRule) Compare(args, groupRule) resultSplice := []*LittleRuleResult{} sdkNames := "" // 先过完条件规则 for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { ruleResult := filterRule(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("条件规则结果：", ruleResult.Result) resultSplice = append(resultSplice, &ruleResult) // 根据规则的sdkId查出其对应的ipcId，用ipcId去找该比对的数据 sdk, err := cache.GetSdkById(groupRule.Rules[j].SdkId) if err != nil { logger.Error("没查到sdk的信息---", err) } ipcId := sdk.IpcId sdkName := sdk.SdkName if ipcId == sdkData.IpcId { logger.Info("当前走的规则的算法是--：", sdkName, "---") for _, areaMap := range sdkData.AreaMapList { ruleResult := filterRule(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("条件规则结果：", ruleResult.Result) // 如果此结果为真且当前过的是yolo算法，应记下此规则所对应的sdkName,另外，还要去重 if ruleResult.Result == "true" && ipcId == "02D54B61-0F16-C604-8567-FC4BE493C523" && !strings.Contains(sdkNames, sdkName) { sdkNames = sdkName + "," } resultSplice = append(resultSplice, &ruleResult) } } } } @@ -299,11 +347,23 @@ // 再过其他数据 这步直接得到结果（真或假） 过目标数量 for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { ruleResult := transferParameters(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("数量规则结果：", ruleResult.Result) resultSplice = append(resultSplice, &ruleResult) // 根据规则的sdkId查出其对应的ipcId，用ipcId去找该比对的数据 sdk, err := cache.GetSdkById(groupRule.Rules[j].SdkId) if err != nil { logger.Error("没查到sdk的信息---", err) } ipcId := sdk.IpcId sdkName := sdk.SdkName if ipcId == sdkData.IpcId { for _, areaMap := range sdkData.AreaMapList { ruleResult := transferParameters(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("数量规则结果：", ruleResult.Result) if ruleResult.Result == "true" && ipcId == "02D54B61-0F16-C604-8567-FC4BE493C523" && !strings.Contains(sdkNames, sdkName) { sdkNames = sdkName + "," } resultSplice = append(resultSplice, &ruleResult) } } } } @@ -311,11 +371,22 @@ // 这步过的是时间规则（时间段等） for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { ruleResult := timeRuleResult(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("时间规则结果：", ruleResult.Result) resultSplice = append(resultSplice, &ruleResult) sdk, err := cache.GetSdkById(groupRule.Rules[j].SdkId) if err != nil { logger.Error("没查到sdk的信息---", err) } ipcId := sdk.IpcId sdkName := sdk.SdkName if ipcId == sdkData.IpcId { for _, areaMap := range sdkData.AreaMapList { ruleResult := timeRuleResult(groupRule.Rules[j], &areaMap) if ruleResult.Result != "" { logger.Info("时间规则结果：", ruleResult.Result) if ruleResult.Result == "true" && ipcId == "02D54B61-0F16-C604-8567-FC4BE493C523" && !strings.Contains(sdkNames, sdkName) { sdkNames = sdkName + "," } resultSplice = append(resultSplice, &ruleResult) } } } } @@ -323,8 +394,15 @@ // 最后过持续时间等时间维度的条件 for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { duration(groupRule.Rules[j], &areaMap) sdk, err := cache.GetSdkById(groupRule.Rules[j].SdkId) if err != nil { logger.Error("没查到sdk的信息---", err) } ipcId := sdk.IpcId if ipcId == sdkData.IpcId { for _, areaMap := range sdkData.AreaMapList { duration(groupRule.Rules[j], &areaMap) } } } } @@ -397,36 +475,27 @@ } if flag { logger.Warn("___________________________________________________________________________终于走完万里长征") // 如果成功了我应该找到规则中涉及到的sdk，记录下他们的sdkname sdkName := "" for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { if groupRule.Rules[j].SdkId == sdkData.SdkId && sdkData.IsYolo && !strings.Contains(sdkName, sdkData.SdkName) { // 只记录yolo符合规则的sdk 同时要避免重复拼接 sdkName = sdkData.SdkName + " " // 把他们的位置数据也传下去 locations := []Rect{} for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { for j := 0; j < len(groupRule.Rules); j++ { locations = append(locations, putYolosToResult(groupRule.Rules[j], &areaMap)...) } } } if sdkName != "" { // 把他们的位置数据也传下去 locations := []Rect{} for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { for j := 0; j < len(groupRule.Rules); j++ { locations = append(locations, putYolosToResult(groupRule.Rules[j], &areaMap)...) } } } //// 配了人脸的算法才把人脸的数据甩出来打标签 //flag11 := false //for j := 0; j < len(groupRule.Rules); j++ { // if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a971" { // flag11 = true // } //} //if flag11 { // args.RuleResult["face"] = faces //} args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText, locations}) //// 配了人脸的算法才把人脸的数据甩出来打标签 //flag11 := false //for j := 0; j < len(groupRule.Rules); j++ { // if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a971" { // flag11 = true // } //} //if flag11 { // args.RuleResult["face"] = faces //} if sdkNames != "" { args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkNames, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText, locations}) logger.Info("-------------------yolo结果标签", args.RuleResult["yolo"].([]Result)) } if args.RuleResult["face"] != nil { @@ -444,7 +513,7 @@ func putFaceToResult(rule *protomsg.Rule, am *AreaMap) []Arg { faces := []Arg{} if rule.SdkId == am.sdkId && rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { if len(am.filterData) > 0 { for _, data := range am.filterData { faces = append(faces, data) @@ -457,7 +526,7 @@ func putYolosToResult(rule *protomsg.Rule, am *AreaMap) []Rect { locations := []Rect{} if rule.SdkId == am.sdkId && rule.SdkId != "812b674b-2375-4589-919a-5c1c3278a97e" && rule.SdkId != "812b674b-2375-4589-919a-5c1c3278a972" { if rule.SdkId != "812b674b-2375-4589-919a-5c1c3278a97e" && rule.SdkId != "812b674b-2375-4589-919a-5c1c3278a972" { if len(am.filterData) > 0 { for _, data := range am.filterData { locations = append(locations, data.Location) @@ -486,18 +555,16 @@ // } 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)) //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 threshold <= obj.Score && size <= float64(obj.Rects.Width*obj.Rects.Height) && intersectionper <= PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale) { // 这步要备齐表达式里所需要的所有参数 a.targetNum++ arg1 := Arg{obj.Score, PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale), float64(obj.Rects.Width * obj.Rects.Height), obj.IsYolo, obj.Rects, obj.SdkName, obj.Feature, obj.ThftRes, []*protomsg.Baseinfo{}} arg1 := Arg{obj.Score, PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale), float64(obj.Rects.Width * obj.Rects.Height), obj.IsYolo, obj.Rects, obj.Feature, obj.ThftRes, []*protomsg.Baseinfo{}} //logger.Println("放进去的arg：-------", arg1) a.args = append(a.args, arg1) a.filterData = append(a.filterData, arg1) } } a.sdkId = arg.SdkId a.sdkName = arg.SdkName a.time = time.Unix(time.Now().Unix(), 0).String()[11:16] a.keepRight = arg.KeepRight a.isStatic = arg.IsStatic @@ -603,18 +670,8 @@ result, _ := expression.Evaluate(nil) // 得到数学公式的结果 if result.(bool) { logger.Info("___________________________________________________________________联动任务报警") sdkName := "" for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { if groupRule.Rules[j].SdkId == sdkData.SdkId && sdkData.IsYolo && !strings.Contains(sdkName, sdkData.SdkName) { // 只记录yolo符合规则的sdk 同时要避免重复拼接 sdkName = sdkData.SdkName + " " } } } if sdkName != "" { args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText, []Rect{}}) logger.Info("-------------------yolo结果标签", args.RuleResult["yolo"].([]Result)) } args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, "", groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText, []Rect{}}) logger.Info("-------------------yolo结果标签", args.RuleResult["yolo"].([]Result)) if args.RuleResult["face"] != nil { logger.Info("-------------------face结果标签", args.RuleResult["face"].([]Arg)) } @@ -640,8 +697,8 @@ func filterRule(rule *protomsg.Rule, am *AreaMap) LittleRuleResult { if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { // 处理的是人脸算法 如果这条规则配置的是人脸算法，过滤完条件之后直接得出结果，因为肯定没有数量条件，自己拼接 logger.Error("规则的算法id和区域的算法id：", rule.SdkId, "===", am.sdkId) if rule.SdkId == am.sdkId && rule.PolygonId == am.areaId { // 算法和区域都得对的上 //logger.Info("规则的算法id和区域的算法id：", rule.SdkId, "===", am.sdkId) if rule.PolygonId == am.areaId { // 算法和区域都得对的上 if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a972" && rule.SdkArgAlias != "time_rule" { // 只需要过滤阈值，过滤完后数组长度大于0即为报警，但要考虑如何对每一张都报警呢 @@ -728,7 +785,7 @@ } } else { // 处理的都是yolo数据 if rule.SdkId == am.sdkId && rule.PolygonId == am.areaId { // 首先这条规则得是这个算法的规则，其次规则所对应的区域id要跟区域数据的id对的上 if rule.PolygonId == am.areaId { // 首先这条规则得是这个算法的规则，其次规则所对应的区域id要跟区域数据的id对的上 if rule.SdkArgAlias == "score" || rule.SdkArgAlias == "proportion" || rule.SdkArgAlias == "size" { // 判断的是相似值，占比，尺寸等过滤条件，如果再有，还可以再加 logger.Info("----------当前条件规则：---------", rule) var args []Arg @@ -776,7 +833,7 @@ // 都过滤完条件之后看看是否要创建一个定时器元素 创建定时器的条件：是否有靠右行，个体静止等自带定时器含义的算法以及是否有持续时间 func duration(rule *protomsg.Rule, am *AreaMap) { if rule.SdkId == am.sdkId && rule.PolygonId == am.areaId { // 首先规则所对应的区域id要跟区域数据的id对的上 配置的算法要对的上 if rule.PolygonId == am.areaId { // 首先规则所对应的区域id要跟区域数据的id对的上 配置的算法要对的上 if rule.SdkArgAlias == "duration" { // // 先看看定时器元素队列中是否有这个摄像机这个区域的定时器,如果有就不能再次创建了 var flag bool = true @@ -815,7 +872,7 @@ // 给数据库的规则表达式代参 args: 一条子规则，区域数据 func transferParameters(rule *protomsg.Rule, am *AreaMap) LittleRuleResult { if rule.SdkId == am.sdkId && rule.PolygonId == am.areaId { // 首先规则所对应的区域id要跟区域数据的id对的上 if rule.PolygonId == am.areaId { // 首先规则所对应的区域id要跟区域数据的id对的上 if rule.SdkArgAlias == "targetNum" { // 如果参数是要区域内目标数量 即yolo 人脸不会有数量 //logger.Info("得出结果阶段", "比较的规则是：", rule) if rule.Operator == "" { @@ -850,7 +907,7 @@ return LittleRuleResult{} } func timeRuleResult(rule *protomsg.Rule, am *AreaMap) LittleRuleResult { if rule.PolygonId == am.areaId && rule.SdkId == am.sdkId { // 首先规则所对应的区域id要跟区域数据的id对的上 if rule.PolygonId == am.areaId { // 首先规则所对应的区域id要跟区域数据的id对的上 if rule.SdkArgAlias == "time_rule" { // 判断是否符合时间规则 logger.Info("----------当前时间规则：---------", rule) // 根据放值字段里存的时间规则的id去另一个表里查需要比对的时间段（比如当前时间是周三，应根据区域id查出其周三的几个布防时间段，数组） @@ -938,7 +995,10 @@ //} _, cameraTimeRule := cache.GetTimeRuleById(id) var timeRangeList []day json.Unmarshal([]byte(cameraTimeRule.TimeRule), &timeRangeList) 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)
