package main
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import (
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"basic.com/pubsub/protomsg.git"
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"basic.com/valib/logger.git"
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"encoding/base64"
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"encoding/json"
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"github.com/golang/protobuf/proto"
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uuid "github.com/satori/go.uuid"
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"ruleprocess/ruleserver"
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"ruleprocess/structure"
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"ruleprocess/util"
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"strconv"
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"time"
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)
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func ReadData(args *structure.SdkDatas,cameraPolygons []protomsg.CameraPolygon) {
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for _, arg := range args.Sdkdata {
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SdkDataFormat(args.CameraId, arg, cameraPolygons)
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}
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}
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// 计算区域内的目标数量以及将相似度、占比、尺寸等打包
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func CountAreaObjs(a *structure.AreaMap,arg *structure.SdkData) {
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a.TargetNum = 0
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threshold := 0.0 // 相似度
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intersectionper := 20.0 // 占比
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size := 0.0 // 尺寸
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areaPoints := ruleserver.Json2points(a.AreaJson)
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logger.Info("看看图片的width和height:",arg.ImageWidth,arg.ImageHeight)
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widthScale := float64(arg.ImageWidth) / 960
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heigthScale := float64(arg.ImageHeight) / 540
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for _, obj := range arg.Photo {
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//logger.Info("------------------看看sdkData:", arg.SdkName, "的Photo数据----------------", obj, "----顺便看看占比-----：", PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale))
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if obj.Score >= threshold && float64(obj.Rects.Width*obj.Rects.Height) >= size && ruleserver.PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale) >= intersectionper {
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// 这步要备齐表达式里所需要的所有参数
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a.TargetNum++
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uuid := uuid.NewV4().String()
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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{}}
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//logger.Println("放进去的arg：-------", arg1)
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a.Args = append(a.Args, &arg1)
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a.FilterData = append(a.FilterData, &arg1)
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}
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}
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logger.Info("区域是：",areaPoints,"区域内目标数量为：",a.TargetNum,"---",len(a.FilterData))
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a.Time = time.Unix(time.Now().Unix(), 0).String()[11:16]
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//logger.Println("--------------------看看区域数据：",*a)
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}
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// 把sdk从数据帧上提取的按照区域分类归置
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func SdkDataFormat(cameraId string, arg *structure.SdkData, cameraPolygons []protomsg.CameraPolygon) {
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logger.Info("==================================本sdkData中解出来的目标数据=======================================")
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for _, photo := range arg.Photo {
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logger.Info("--------解析出来的数据---", cameraId, arg.IpcId, photo.Rects, photo.Score)
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}
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for _, polygon := range cameraPolygons {
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//logger.Println("++++++在这儿看一下区域啊:", polygon.Polygon)
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areaMap := structure.AreaMap{CameraId: cameraId, AreaId: polygon.Id,AreaJson: polygon.Polygon, TriggerLine: polygon.TriggerLine, DirectionLine: polygon.DirectionLine}
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// 为每个摄像机区域填充数据
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CountAreaObjs(&areaMap,arg)
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arg.AreaMapList = append(arg.AreaMapList, &areaMap)
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}
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}
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// 将外部传进来的rect（top,bottom,left,right）转化为自己内部的rect(left top width height)
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func rectFormat(rcobj *protomsg.Rect) structure.Rect {
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//logger.Info("++++++++++++++++++++++++++++++收到的yolo的区域坐标：",rcobj)
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rect := structure.Rect{}
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rect.X = float64(rcobj.Left)
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rect.Y = float64(rcobj.Top)
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rect.Width = float64(rcobj.Right - rcobj.Left)
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rect.Height = float64(rcobj.Bottom - rcobj.Top)
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return rect
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}
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// 将外部传进来的sdk数据包解成 SdkDatas
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func ParamFormat(msg []byte, args *structure.SdkDatas) protomsg.SdkMessage {
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defer func() {
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if err := recover(); err != nil {
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logger.Info("解包过程的异常捕获", err.(string))
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}
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}()
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// 反序列化数据得到sdk入参
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m := protomsg.SdkMessage{}
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err := proto.Unmarshal(msg, &m)
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if err != nil {
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panic("解析msg时出现错误")
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}
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// 先进行一下追踪
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ruleserver.FaceIsSame(&m)
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args.CameraId = m.Cid
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args.TaskId = m.Tasklab.Taskid
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// 把图片的二进制解压缩进行画框在压缩回去
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bdata, err := util.UnCompress(m.Data)
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if err != nil {
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panic("解压缩图片时出现错误")
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}
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i := protomsg.Image{}
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err = proto.Unmarshal(bdata, &i)
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logger.Info("接到数据，摄像机为：", m.Cid, "图片的id为：", i.Id)
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//logger.Info("----------------看看有几个算法：",len(m.Tasklab.Sdkinfos))
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for _, sdkinfo := range m.Tasklab.Sdkinfos { // yolo算法
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switch sdkinfo.Sdktype {
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case "Yolo":
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extractYolo(args,m,sdkinfo,i)
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case "FaceDetect":
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extractFace(args,m,sdkinfo,i)
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case "Plate":
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extractCar(args,m,sdkinfo,i)
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case "HumanTrack":
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extractTrack(args,m,sdkinfo,i)
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}
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}
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return m
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}
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// 提取face
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func extractFace(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) {
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arg := structure.SdkData{}
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arg.TaskId = m.Tasklab.Taskid
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arg.IpcId = sdkinfo.Ipcid
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arg.IsYolo = false
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arg.ImageWidth = int(i.Width)
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arg.ImageHeight = int(i.Height)
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if len(sdkinfo.Sdkdata) > 1 {
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faceParam := protomsg.ParamFacePos{}
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err := proto.Unmarshal(sdkinfo.Sdkdata, &faceParam)
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if err != nil {
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logger.Info("解析FACE sdk数据时出现错误", err)
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return
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}
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logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces))
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for _, info := range faceParam.Faces {
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//logger.Info("_______________________________________________第一次看相似值：",info.Pos.FAngle.Confidence*100)
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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: base64.StdEncoding.EncodeToString(info.Feats)},structure.SourcePhoto{}}
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arg.Photo = append(arg.Photo, photoMap)
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}
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args.Sdkdata = append(args.Sdkdata, &arg)
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}
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}
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// 提取yolo
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func extractYolo(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) {
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arg := structure.SdkData{}
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arg.TaskId = m.Tasklab.Taskid
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arg.IpcId = sdkinfo.Ipcid
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arg.IsYolo = true
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arg.ImageWidth = int(i.Width)
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arg.ImageHeight = int(i.Height)
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logger.Info("-----追踪之后sdkinfo.Sdkdata的长度为：----", len(sdkinfo.Sdkdata))
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if len(sdkinfo.Sdkdata) > 1 {
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// 大于1才有数据
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yoloParam := protomsg.ParamYoloObj{}
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err := proto.Unmarshal(sdkinfo.Sdkdata, &yoloParam)
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if err != nil {
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logger.Info("解析YOLO sdk数据时出现错误", err)
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return
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}
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var yoloNum int = 0
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for _, info := range yoloParam.Infos {
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if info.Typ == 0 {
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//logger.Debug("-------------yolo的坐标有几个",info.RcObj)
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photoMap := structure.PhotoMap{structure.SourcePhoto{Rects: rectFormat(info.RcObj), Score: float64(info.Prob) * 100, Type: "yolo",Id:strconv.Itoa(int(info.ObjID))},structure.SourcePhoto{}}
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arg.Photo = append(arg.Photo, photoMap)
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yoloNum++
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}
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}
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logger.Info("--------------追踪之后yolo的个数：", yoloNum)
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args.Sdkdata = append(args.Sdkdata, &arg)
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} else {
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return
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}
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}
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// 提取car
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func extractCar(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) {
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arg := structure.SdkData{}
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arg.TaskId = m.Tasklab.Taskid
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arg.IpcId = sdkinfo.Ipcid
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arg.IsYolo = false
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arg.ImageWidth = int(i.Width)
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arg.ImageHeight = int(i.Height)
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if len(sdkinfo.Sdkdata) > 1 {
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plateIDResult := protomsg.PlateIDResult {}
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err := proto.Unmarshal(sdkinfo.Sdkdata, &plateIDResult )
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if err != nil {
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logger.Info("解析车牌数据时出现错误", err)
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return
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}
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for _, info := range plateIDResult.Result {
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logger.Info("接收车牌数据：",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation)
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if info.NConfidence > 70 {
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logger.Info("车牌也符合的数据",info.FvdConf,info.NVehicleColor1,info.NPlateFlag,info.RcCarLocation,info.NConfidence,)
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photoMap := structure.PhotoMap{structure.SourcePhoto{Id: info.License,Score: float64(info.FvdConf)*100,Rects: rectFormat(info.RcCarLocation), Type: "plate", Car:info},structure.SourcePhoto{}}
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arg.Photo = append(arg.Photo, photoMap)
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}
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}
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args.Sdkdata = append(args.Sdkdata, &arg)
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} else {
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return
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}
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}
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// 提取跟踪
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func extractTrack(args *structure.SdkDatas,m protomsg.SdkMessage,sdkinfo *protomsg.SdkmsgWithTask,i protomsg.Image) {
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arg := structure.SdkData{}
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arg.TaskId = m.Tasklab.Taskid
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arg.IpcId = sdkinfo.Ipcid
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arg.IsYolo = false
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arg.ImageWidth = int(i.Width)
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arg.ImageHeight = int(i.Height)
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if len(sdkinfo.Sdkdata) > 1 {
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Track := protomsg.HumanTrackResult {}
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err := proto.Unmarshal(sdkinfo.Sdkdata, &Track)
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if err != nil {
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logger.Info("解析跟踪目标数据时出现错误", err)
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return
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}
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for _, info := range Track.Result {
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logger.Info("接收跟踪数据：",info.Id,info.Confidence)
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b,_ := json.Marshal(info.Feature)
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photoMap := structure.PhotoMap{structure.SourcePhoto{Id: strconv.Itoa(int(info.Id)),Score: float64(info.Confidence)*100,Rects: rectFormat(info.RcHuman), Type: "track",Feature: base64.StdEncoding.EncodeToString(b)},structure.SourcePhoto{}}
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arg.Photo = append(arg.Photo, photoMap)
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}
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args.Sdkdata = append(args.Sdkdata, &arg)
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} else {
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return
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}
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}
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// 把人脸放进对应的人体
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func FacePush2Body (photomap *structure.PhotoMap,sdkInfos []*protomsg.SdkmsgWithTask) {
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for _,sdkinfo := range sdkInfos {
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if sdkinfo.Sdktype == "FaceDetect" {
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faceParam := protomsg.ParamFacePos{}
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err := proto.Unmarshal(sdkinfo.Sdkdata, &faceParam)
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if err != nil {
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logger.Info("解析FACE sdk数据时出现错误", err)
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return
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}
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logger.Info("--------------追踪之后人脸的个数：", len(faceParam.Faces))
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for _, info := range faceParam.Faces {
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percent := ruleserver.PgsInterPercent(Rect2Point(photomap.Rects),rectFormat(info.Pos.RcFace), 1, 1)
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if percent > 99 {
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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: base64.StdEncoding.EncodeToString(info.Feats)}
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}
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}
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}
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}
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}
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func Rect2Point(rect structure.Rect) []structure.Point{
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// 按逆时针转化
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points := []structure.Point{}
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leftTop := structure.Point{rect.X,rect.Y}
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points = append(points,leftTop)
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leftBottom := structure.Point{rect.X,rect.Y+rect.Height}
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points = append(points,leftBottom)
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rightBottom := structure.Point{rect.X+rect.Width,rect.Y+rect.Height}
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points = append(points,rightBottom)
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rightTop := structure.Point{rect.X+rect.Width,rect.Y}
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points = append(points,rightTop)
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return points
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}
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