派生自 ruleprocess
ruleserver/ruleToformula.go
@@ -2,6 +2,7 @@ import ( "encoding/json" "fmt" "ruleprocess/cache" "ruleprocess/logger" "sort" @@ -9,10 +10,13 @@ "strings" "time" bigCache "basic.com/pubsub/cache.git" "basic.com/pubsub/protomsg.git" "github.com/knetic/govaluate" ) func init () { bigCache.Init() } // 任务 type Task struct { camID string //摄像机ID @@ -62,6 +66,7 @@ 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 } @@ -97,7 +102,7 @@ IsYolo bool // 是否是yolo数据 SdkName string ThftRes protomsg.ThftResult Liker []*protomsg.Baseinfo // 如果是人脸的话尤其是比对，应存下他跟底库的人员的相似情况 yolo的话给nil就行 Feature []byte } // 每个算法对于当前帧画面自己提取的数据 @@ -180,6 +185,7 @@ // 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} @@ -227,6 +233,48 @@ } } } func Compare(args *SdkDatas, groupRule *protomsg.GroupRule) { compareFlag := false // 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 compareFlag { logger.Info("配置了对比底库参数") } else { logger.Info("没有配置对比底库参数") } 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" { 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 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) } logger.Info("-------------------成功给liker赋值：", arg.Liker) } } } } } } } } func RunRule(args *SdkDatas, groupRule *protomsg.GroupRule, taskId string) bool { defer func() { if err := recover(); err != nil { @@ -234,6 +282,7 @@ } }() logger.Info("+++++++++++规则开始运行+++++++++++++++++当前规则--：", *groupRule) Compare(args, groupRule) resultSplice := []*LittleRuleResult{} // 先过完条件规则 for j := 0; j < len(groupRule.Rules); j++ { @@ -290,12 +339,12 @@ if strings.HasPrefix(completeFormula, "&&") || strings.HasPrefix(completeFormula, "||") || strings.HasPrefix(completeFormula, ">=") || strings.HasPrefix(completeFormula, "<=") || strings.HasPrefix(completeFormula, "==") || strings.HasPrefix(completeFormula, "!=") || strings.HasPrefix(completeFormula, ">") || strings.HasPrefix(completeFormula, "<") { // 以这些开头的基本是联动任务 if strings.HasPrefix(completeFormula, "&&") || strings.HasPrefix(completeFormula, "||") || strings.HasPrefix(completeFormula, ">=") || strings.HasPrefix(completeFormula, "<=") || strings.HasPrefix(completeFormula, "==") || strings.HasPrefix(completeFormula, "!=") { completeFormula = completeFormula[2 :] completeFormula = completeFormula[2:] } if strings.HasPrefix(completeFormula, ">") || strings.HasPrefix(completeFormula, "<") { completeFormula = completeFormula[1 :] completeFormula = completeFormula[1:] } logger.Info("-------------------看看拔毛后的表达式：",completeFormula) logger.Info("-------------------看看拔毛后的表达式：", completeFormula) expression, _ := govaluate.NewEvaluableExpression(completeFormula) result, _ := expression.Evaluate(nil) // 得到数学公式的结果 return result.(bool) @@ -330,7 +379,7 @@ // 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" { if groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || groupRule.Rules[j].SdkId == "812b674b-2375-4589-919a-5c1c3278a972" { flag11 = true } } @@ -378,7 +427,7 @@ //if flag11 { // args.RuleResult["face"] = faces //} args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText,locations}) args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText, locations}) logger.Info("-------------------yolo结果标签", args.RuleResult["yolo"].([]Result)) } if args.RuleResult["face"] != nil { @@ -396,7 +445,7 @@ 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-5c1c3278a971" { if rule.SdkId == am.sdkId && 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) @@ -409,7 +458,7 @@ 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-5c1c3278a971" { if rule.SdkId == am.sdkId && 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) @@ -438,11 +487,11 @@ // } 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.ThftRes, obj.Liker} 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{}} //logger.Println("放进去的arg：-------", arg1) a.args = append(a.args, arg1) a.filterData = append(a.filterData, arg1) @@ -564,7 +613,7 @@ } } if sdkName != "" { args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText,[]Rect{}}) 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)) } if args.RuleResult["face"] != nil { @@ -592,22 +641,22 @@ 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.Info("规则的算法id和区域的算法id：",rule.SdkId,"===",am.sdkId) logger.Info("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 if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a972" && rule.SdkArgAlias != "time_rule"{ 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 argValue, err := strconv.ParseFloat(rule.SdkArgValue, 64) if err != nil { logger.Info("规则配置的阈值非法") logger.Error("规则配置的阈值非法") return LittleRuleResult{am.sdkName, rule.RuleWithPre + "" + "false", rule.Sort} } flag := "false" for _, obj := range am.filterData { for index := 0; index < len(obj.Liker); { // 将达不到阈值的相似者从相似者数组中删除 logger.Warn("=======================相似值：",float64(obj.Liker[index].CompareScore * 100)) if float64(obj.Liker[index].CompareScore * 100) < argValue { logger.Warn("=======================相似值：", float64(obj.Liker[index].CompareScore*100)) if float64(obj.Liker[index].CompareScore*100) < argValue { // Go 语言中切片删除元素的本质是：以被删除元素为分界点，将前后两个部分的内存重新连接起来。不用怀疑，数组删除元素就这么坑爹 obj.Liker = append(obj.Liker[:index], obj.Liker[index+1:]...) } else {
