package main

import (
	"basic.com/pubsub/protomsg.git"
	logger "github.com/alecthomas/log4go"
	"github.com/golang/protobuf/proto"
	uuid "github.com/satori/go.uuid"
	"ruleprocess/ruleserver"
	"ruleprocess/structure"
	"ruleprocess/util"
	"strconv"
	"time"
)
func ReadData(args *structure.SdkDatas,cameraPolygons []protomsg.CameraPolygon) {
	for _, arg := range args.Sdkdata {
		SdkDataFormat(args.CameraId, arg, cameraPolygons)
	}
}

// 计算区域内的目标数量以及将相似度、占比、尺寸等打包
func CountAreaObjs(a *structure.AreaMap,arg *structure.SdkData) {

	a.TargetNum = 0
	threshold := 70.0       // 相似度
	intersectionper := 20.0 // 占比
	size := 0.0            // 尺寸

	areaPoints := ruleserver.Json2points(a.AreaJson)
	logger.Info("看看图片的width和height:",arg.ImageWidth,arg.ImageHeight)
	widthScale := float64(arg.ImageWidth) / 960
	heigthScale := float64(arg.ImageHeight) / 540
	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))
		if  obj.Score >= threshold && float64(obj.Rects.Width*obj.Rects.Height) >= size && ruleserver.PgsInterPercent(areaPoints, obj.Rects, widthScale, heigthScale) >= intersectionper {
			// 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{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)
		}
	}
	logger.Info("区域是：",areaPoints,"区域内目标数量为：",a.TargetNum,"---",len(a.FilterData))
	a.Time = time.Unix(time.Now().Unix(), 0).String()[11:16]
	//logger.Println("--------------------看看区域数据：",*a)
}

// 把sdk从数据帧上提取的按照区域分类归置
func SdkDataFormat(cameraId string, arg *structure.SdkData, cameraPolygons []protomsg.CameraPolygon) {
	logger.Info("==================================本sdkData中解出来的目标数据=======================================")
	for _, photo := range arg.Photo {
		logger.Info("--------解析出来的数据---", cameraId, arg.IpcId, photo.Rects, photo.Score)
	}
	for _, polygon := range cameraPolygons {
		//logger.Println("++++++在这儿看一下区域啊:", polygon.Polygon)
		areaMap := structure.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
		CountAreaObjs(&areaMap,arg)
		arg.AreaMapList = append(arg.AreaMapList, &areaMap)
	}
}



// 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)
func rectFormat(rcobj *protomsg.Rect) structure.Rect {
	//logger.Info("++++++++++++++++++++++++++++++收到的yolo的区域坐标：",rcobj)
	rect := structure.Rect{}
	rect.X = float64(rcobj.Left)
	rect.Y = float64(rcobj.Top)
	rect.Width = float64(rcobj.Right - rcobj.Left)
	rect.Height = float64(rcobj.Bottom - rcobj.Top)
	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() {
		if err := recover(); err != nil {
			logger.Info("解包过程的异常捕获", err.(string))
		}

	}()
	// 反序列化数据得到sdk入参
	m := protomsg.SdkMessage{}
	err := proto.Unmarshal(msg, &m)
	if err != nil {
		panic("解析msg时出现错误")
	}

	// 先进行一下追踪
	ruleserver.FaceIsSame(&m)
	args.CameraId = m.Cid
	args.TaskId = m.Tasklab.Taskid
	// 把图片的二进制解压缩进行画框在压缩回去
	bdata, err := util.UnCompress(m.Data)
	if err != nil {
		panic("解压缩图片时出现错误")
	}
	i := protomsg.Image{}
	err = proto.Unmarshal(bdata, &i)
	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
		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
}