派生自 ruleprocess
algorithm/middleware/readyData.go
@@ -2,7 +2,7 @@ import ( "basic.com/pubsub/protomsg.git" "basic.com/valib/logger.git" logger "github.com/alecthomas/log4go" "github.com/golang/protobuf/proto" uuid "github.com/satori/go.uuid" "ruleprocess/ruleserver" @@ -35,7 +35,7 @@ // 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, ruleserver.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{}} arg1 := structure.Arg{structure.SourceArg{obj.Id,uuid,obj.Score, ruleserver.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{}},structure.SourceArg{}} //logger.Println("放进去的arg：-------", arg1) a.Args = append(a.Args, &arg1) a.FilterData = append(a.FilterData, &arg1) @@ -74,9 +74,6 @@ return rect } // 将外部传进来的sdk数据包解成 SdkDatas func ParamFormat(msg []byte, args *structure.SdkDatas) protomsg.SdkMessage { defer func() { @@ -106,91 +103,166 @@ logger.Info("接到数据，摄像机为：", m.Cid, "图片的id为：", i.Id) //logger.Info("----------------看看有几个算法：",len(m.Tasklab.Sdkinfos)) for _, sdkinfo := range m.Tasklab.Sdkinfos { // yolo算法 if sdkinfo.Sdktype == "Yolo" { arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = true arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) logger.Info("-----追踪之后sdkinfo.Sdkdata的长度为：----", len(sdkinfo.Sdkdata)) if len(sdkinfo.Sdkdata) > 1 { // 大于1才有数据 yoloParam := protomsg.ParamYoloObj{} err = proto.Unmarshal(sdkinfo.Sdkdata, &yoloParam) if err != nil { logger.Info("解析YOLO sdk数据时出现错误", err) continue } var yoloNum int = 0 for _, info := range yoloParam.Infos { if info.Typ == 0 { //logger.Debug("-------------yolo的坐标有几个",info.RcObj) photoMap := structure.PhotoMap{Rects: rectFormat(info.RcObj), Score: float64(info.Prob) * 100, Type: "yolo",Id:strconv.Itoa(int(info.ObjID))} arg.Photo = append(arg.Photo, photoMap) yoloNum++ } } logger.Info("--------------追踪之后yolo的个数：", yoloNum) args.Sdkdata = append(args.Sdkdata, &arg) } else { continue } } if sdkinfo.Sdktype == "FaceDetect" { // 人脸检测 arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) if len(sdkinfo.Sdkdata) > 1 { faceParam := protomsg.ParamFacePos{} err = proto.Unmarshal(sdkinfo.Sdkdata, &faceParam) if err != nil { logger.Info("解析FACE sdk数据时出现错误", err) continue } logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces)) for _, info := range faceParam.Faces { //logger.Info("_______________________________________________第一次看相似值：",info.Pos.FAngle.Confidence*100) photoMap := structure.PhotoMap{Id: strconv.Itoa(int(info.Pos.FaceID)) , Rects: rectFormat(info.Pos.RcFace), Score: float64(info.Pos.FAngle.Confidence * 100), Type: "face", ThftRes: *(info.Result), Feature: info.Feats} arg.Photo = append(arg.Photo, photoMap) } args.Sdkdata = append(args.Sdkdata, &arg) } else { continue } } if sdkinfo.Sdktype == "Plate" { // 车牌识别 arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid logger.Info("车牌的ipcid：",sdkinfo.Ipcid) arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) if len(sdkinfo.Sdkdata) > 1 { plateIDResult := protomsg.PlateIDResult {} err = proto.Unmarshal(sdkinfo.Sdkdata, &plateIDResult ) if err != nil { logger.Info("解析车牌数据时出现错误", err) continue } for _, info := range plateIDResult.Result { logger.Info("接收车牌数据：",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation) if info.NConfidence > 70 { logger.Info("车牌也符合的数据",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation,info.NConfidence,) photoMap := structure.PhotoMap{Id: info.License,Score: float64(info.FvdConf)*100,Rects: rectFormat(info.RcCarLocation), Type: "plate", Car:info} arg.Photo = append(arg.Photo, photoMap) } } args.Sdkdata = append(args.Sdkdata, &arg) } else { continue } switch sdkinfo.Sdktype { case "Yolo": extractYolo(args,m,sdkinfo,i) case "FaceDetect": extractFace(args,m,sdkinfo,i) case "Plate": extractCar(args,m,sdkinfo,i) case "HumanTrack": extractTrack(args,m,sdkinfo,i) } } return m } // 提取face func extractFace(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) { arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) if len(sdkinfo.Sdkdata) > 1 { faceParam := protomsg.ParamFacePos{} err := proto.Unmarshal(sdkinfo.Sdkdata, &faceParam) if err != nil { logger.Info("解析FACE sdk数据时出现错误", err) return } logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces)) for _, info := range faceParam.Faces { //logger.Info("_______________________________________________第一次看相似值：",info.Pos.FAngle.Confidence*100) photoMap := structure.PhotoMap{structure.SourcePhoto{Id: strconv.Itoa(int(info.Pos.FaceID)) , Rects: rectFormat(info.Pos.RcFace), Score: float64(info.Pos.FAngle.Confidence * 100), Type: "face", ThftRes: *(info.Result), Feature: info.Feats},structure.SourcePhoto{}} arg.Photo = append(arg.Photo, photoMap) } args.Sdkdata = append(args.Sdkdata, &arg) } } // 提取yolo func extractYolo(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) { arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = true arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) logger.Info("-----追踪之后sdkinfo.Sdkdata的长度为：----", len(sdkinfo.Sdkdata)) if len(sdkinfo.Sdkdata) > 1 { // 大于1才有数据 yoloParam := protomsg.ParamYoloObj{} err := proto.Unmarshal(sdkinfo.Sdkdata, &yoloParam) if err != nil { logger.Info("解析YOLO sdk数据时出现错误", err) return } var yoloNum int = 0 for _, info := range yoloParam.Infos { if info.Typ == 0 { //logger.Debug("-------------yolo的坐标有几个",info.RcObj) photoMap := structure.PhotoMap{structure.SourcePhoto{Rects: rectFormat(info.RcObj), Score: float64(info.Prob) * 100, Type: "yolo",Id:strconv.Itoa(int(info.ObjID))},structure.SourcePhoto{}} arg.Photo = append(arg.Photo, photoMap) yoloNum++ } } logger.Info("--------------追踪之后yolo的个数：", yoloNum) args.Sdkdata = append(args.Sdkdata, &arg) } else { return } } // 提取car func extractCar(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) { arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) if len(sdkinfo.Sdkdata) > 1 { plateIDResult := protomsg.PlateIDResult {} err := proto.Unmarshal(sdkinfo.Sdkdata, &plateIDResult ) if err != nil { logger.Info("解析车牌数据时出现错误", err) return } for _, info := range plateIDResult.Result { logger.Info("接收车牌数据：",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation) if info.NConfidence > 70 { logger.Info("车牌也符合的数据",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation,info.NConfidence,) photoMap := structure.PhotoMap{structure.SourcePhoto{Id: info.License,Score: float64(info.FvdConf)*100,Rects: rectFormat(info.RcCarLocation), Type: "plate", Car:info},structure.SourcePhoto{}} arg.Photo = append(arg.Photo, photoMap) } } args.Sdkdata = append(args.Sdkdata, &arg) } else { return } } // 提取跟踪 func extractTrack(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) { arg := structure.SdkData{} arg.TaskId = m.Tasklab.Taskid arg.IpcId = sdkinfo.Ipcid arg.IsYolo = false arg.ImageWidth = int(i.Width) arg.ImageHeight = int(i.Height) if len(sdkinfo.Sdkdata) > 1 { Track := protomsg.HumanTrackResult {} err := proto.Unmarshal(sdkinfo.Sdkdata, &Track) if err != nil { logger.Info("解析跟踪目标数据时出现错误", err) return } for _, info := range Track.Result { logger.Info("接收跟踪数据：",info.Id,info.Confidence) photoMap := structure.PhotoMap{structure.SourcePhoto{Id: strconv.Itoa(int(info.Id)),Score: float64(info.Confidence)*100,Rects: rectFormat(info.RcHuman), Type: "track"},structure.SourcePhoto{}} FacePush2Body(&photoMap,m.Tasklab.Sdkinfos) logger.Info("组装后的跟踪数据：",photoMap) arg.Photo = append(arg.Photo, photoMap) } args.Sdkdata = append(args.Sdkdata, &arg) } else { return } } // 把人脸放进对应的人体 func FacePush2Body (photomap *structure.PhotoMap,sdkInfos []*protomsg.SdkmsgWithTask) { for _,sdkinfo := range sdkInfos { if sdkinfo.Sdktype == "FaceDetect" { faceParam := protomsg.ParamFacePos{} err := proto.Unmarshal(sdkinfo.Sdkdata, &faceParam) if err != nil { logger.Info("解析FACE sdk数据时出现错误", err) return } logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces)) for _, info := range faceParam.Faces { percent := ruleserver.PgsInterPercent(Rect2Point(photomap.Rects),rectFormat(info.Pos.RcFace), 1, 1) if percent > 99 { photomap.AttachObj = structure.SourcePhoto{Id:strconv.Itoa(int(info.Pos.FaceID)),Rects: rectFormat(info.Pos.RcFace),Score: float64(info.Pos.FAngle.Confidence * 100), Type: "face", ThftRes: *(info.Result), Feature: info.Feats} } } } } } func Rect2Point(rect structure.Rect) []structure.Point{ // 按逆时针转化 points := []structure.Point{} leftTop := structure.Point{rect.X,rect.Y} points = append(points,leftTop) leftBottom := structure.Point{rect.X,rect.Y+rect.Height} points = append(points,leftBottom) rightBottom := structure.Point{rect.X+rect.Width,rect.Y+rect.Height} points = append(points,rightBottom) rightTop := structure.Point{rect.X+rect.Width,rect.Y} points = append(points,rightTop) return points }
