派生自 ruleprocess
ruleserver/ruleToformula.go
@@ -4,6 +4,7 @@ "encoding/json" "fmt" "log" "os" "ruleprocess/cache" "sort" "strconv" @@ -139,7 +140,7 @@ RuleText string // 文字版规则组 } type LittleRuleResult struct { SdkName string //记录下此结果是哪个sdk的结果 SdkName string // 记录下此结果是哪个sdk的结果 Result string // 已包含了前置连接符 Sort int32 } @@ -181,7 +182,7 @@ // 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) { for _, polygon := range cameraPolygons { //log.Println("++++++在这儿看一下区域啊", polygon) //log.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} // 为每个摄像机区域填充数据 areaMap.CountAreaObjs(arg) @@ -209,6 +210,7 @@ for _, taskRule := range taskRuleList { ruleList := taskRule.GroupRules // 获取的是task下面的任务组 taskId := taskRule.TaskId //log.Println("------------本组任务下的规则组的数量：",len(ruleList)) for i := 0; i < len(ruleList); i++ { temp := ruleList[i].Rules // temp为一组完整规则 在此需要判断规则是否是联动规则 if len(temp) > 0 { @@ -232,7 +234,7 @@ } }() log.Println("++++++++++++++++++++++++++++规则开始运行+++++++++++++++++++++++++") log.Println("+++++++++++规则开始运行+++++++++++++++++当前规则--：",*groupRule) resultSplice := []*LittleRuleResult{} // 先过完条件规则 for j := 0; j < len(groupRule.Rules); j++ { @@ -251,11 +253,10 @@ for _, sdkData := range args.Sdkdata { for _, areaMap := range sdkData.AreaMapList { for j := 0; j < len(groupRule.Rules); j++ { putFaceToResult(groupRule.Rules[j], &areaMap, faces) args.RuleResult["face"] = putFaceToResult(groupRule.Rules[j], &areaMap, faces) } } } args.RuleResult["face"] = faces // 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 { @@ -328,14 +329,19 @@ sdkName := "" for j := 0; j < len(groupRule.Rules); j++ { for _, sdkData := range args.Sdkdata { if groupRule.Rules[j].SdkId == sdkData.SdkId && sdkData.IsYolo { // 只记录yolo符合规则的sdk sdkName = sdkName + "," + sdkData.SdkName 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 + " " } } } // 过完规则后打个标签，告诉调用者本帧数据针对哪个任务哪组规则报警了 后加：可能还不够，还需要区分触发报警的对象，后面往es数据库插数据时要用 args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText}) log.Println("-------------------结果标签",args.RuleResult["yolo"].([]Result)) if sdkName != "" { args.RuleResult["yolo"] = append(args.RuleResult["yolo"].([]Result), Result{taskId, sdkName, groupRule.GroupId, groupRule.AlarmLevel, groupRule.GroupText}) log.Println("-------------------yolo结果标签",args.RuleResult["yolo"].([]Result)) } if args.RuleResult["face"] != nil { log.Println("-------------------face结果标签",args.RuleResult["face"].([]Arg)) os.Exit(1) } return true } else { return false @@ -346,14 +352,16 @@ } } func putFaceToResult(rule *protomsg.Rule, am *AreaMap, faces []Arg) { func putFaceToResult(rule *protomsg.Rule, am *AreaMap, faces []Arg) []Arg { if rule.SdkId == am.sdkId { if len(am.filterData) > 0 { for _, data := range am.filterData { log.Println("---------------------------------------------------------------------有这个data",data) faces = append(faces, data) } } } return faces } // 计算区域内的目标数量以及将相似度、占比、尺寸等打包 @@ -374,7 +382,7 @@ // } for _, obj := range arg.Photo { log.Println("------------------看看sdkData的Photo数据----------------", obj, "----顺便看看占比-----：", PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale)) log.Println("------------------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++ @@ -389,6 +397,7 @@ a.time = time.Unix(time.Now().Unix(), 0).String()[11:16] a.keepRight = arg.KeepRight a.isStatic = arg.IsStatic //log.Println("--------------------看看区域数据：",*a) } // 将字符串格式的坐标序列化为Point格式 @@ -514,11 +523,12 @@ // 过滤规则先筛选出符合条件的目标数量 func filterRule(rule *protomsg.Rule, am *AreaMap) LittleRuleResult { if rule.SdkId == "FaceDetect" || rule.SdkId == "FaceCompare" { if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" || rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a971" { // 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 if rule.SdkId == am.sdkId && rule.PolygonId == am.areaId { // 算法和区域都得对的上 if rule.SdkId == "FaceCompare" { if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a971" { // 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 { @@ -552,7 +562,8 @@ } return LittleRuleResult{am.sdkName, rule.RuleWithPre + "" + flag, rule.Sort} } if rule.SdkId == "FaceDetect" { // 人脸检测 if rule.SdkId == "812b674b-2375-4589-919a-5c1c3278a97e" { // 人脸检测 log.Println("------------------------------------------------------------------------------------------------------------------------------------终于等到你") if rule.Operator == "==" || rule.Operator == ">=" || rule.Operator == "<=" || rule.Operator == "<" || rule.Operator == ">" || rule.Operator == "!=" { // 如果是不规矩的连接符统统返回false 规则也只能判断人脸的相似度，所以不存在别的连接符 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 @@ -582,6 +593,7 @@ am.targetNum = len(am.filterData) // 把符合条件的目标数量更新到targetNum字段 } if am.targetNum > 0 { log.Println("！！！！！！！！！人脸检测成功") return LittleRuleResult{am.sdkName, rule.RuleWithPre + "" + "true", rule.Sort} } else { return LittleRuleResult{am.sdkName, rule.RuleWithPre + "" + "false", rule.Sort}
