优化文件
This commit is contained in:
BBIT-Kai
@@ -9,7 +9,6 @@ import ink.snowflake.server.route.ImageAnalytics
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import ink.snowflake.server.route.RemoteDebug
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import ink.snowflake.server.route.VideoAnalytics
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import ink.snowflake.server.route.VideoAnalyticsJetson
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import ink.snowflake.server.route.mainFunc
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import ink.snowflake.server.utils.AppConfig
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import io.ktor.server.application.*
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import io.ktor.server.tomcat.jakarta.*
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@@ -54,8 +53,6 @@ fun Application.module() {
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// 设置-WebSocket
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configureSockets()
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// 业务-首页导航
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mainFunc()
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// 业务-用户信息相关操作
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User(appConfig)
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// 业务-聊天
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@@ -32,7 +32,6 @@ object ImageDao {
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}
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}
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fun getImageList(name: String): List<ImageAnalyticsRequest> {
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return transaction {
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ImageTable.selectAll()
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@@ -8,6 +8,7 @@ import io.ktor.server.auth.*
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import io.ktor.server.routing.*
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import io.ktor.server.request.*
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import io.ktor.server.response.*
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import kotlin.text.isNullOrEmpty
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fun Application.ImageAnalytics() {
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routing {
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@@ -18,16 +19,6 @@ fun Application.ImageAnalytics() {
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call.respond(BaseResponse(data = ImageDao.insertImageAnalyticsData(request)))
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}
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authenticate {
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// 拍照保存为图片 并且调用Python程序进行分析
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get("/takePhoto") {
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val camera = call.request.queryParameters["cameraId"]
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if (camera.isNullOrEmpty()) {
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call.respond(BaseResponse(status = false, message = "摄像头名称不能为空", data = null))
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return@get
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}
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stopHLSStream(camera)
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call.respond(BaseResponse(message = "摄像头流已停止", data = null))
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}
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// 获取已分析图片列表
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get("/getImageList") {
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val name = call.parameters["name"]
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@@ -1,30 +0,0 @@
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package ink.snowflake.server.route
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import com.google.gson.Gson
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import ink.snowflake.server.model.response.BaseResponse
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import ink.snowflake.server.model.response.DeviceItem
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import ink.snowflake.server.utils.runCommand
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import io.ktor.client.*
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import io.ktor.client.engine.cio.*
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import io.ktor.http.*
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import io.ktor.server.application.*
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import io.ktor.server.response.*
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import io.ktor.server.routing.*
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import java.io.BufferedReader
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import java.io.InputStreamReader
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import io.ktor.client.plugins.auth.*
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import io.ktor.client.plugins.auth.providers.*
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import io.ktor.client.request.*
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import io.ktor.client.statement.*
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import io.ktor.server.auth.*
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import io.ktor.server.http.content.*
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import java.io.File
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fun Application.mainFunc() {
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routing {
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get("/") {
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// call.respondFile(File("src/main/resources/page/html/login.html"))
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// call.respondRedirect("html/login.html")
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}
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}
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}
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@@ -34,244 +34,211 @@ import java.time.format.DateTimeFormatter
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import java.util.*
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val clients = Collections.synchronizedList<WebSocketServerSession>(ArrayList()) // 线程安全的客户端列表
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var aiState = "等待分析任务中"
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fun Application.VideoAnalytics() {
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routing {
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// 实时发送AI状态
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webSocket("/handleState") { // WebSocket 路由
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clients.add(this) // 添加当前连接的客户端
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send(aiState) // 向客户端发送连接成功消息
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try {
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incoming.consumeEach { frame -> // 持续接收消息
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when (frame) {
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is Frame.Text -> {
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aiState = frame.readText() // 更新状态
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broadcastMessage(aiState) // 使用封装的方法广播消息
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}
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is Frame.Close -> {
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println("Closed")
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clients.remove(this)
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close() // 确保关闭 WebSocket 连接
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return@consumeEach
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}
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// 其他消息类型的处理
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is Frame.Binary -> TODO() // 处理二进制消息
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is Frame.Ping -> TODO() // 处理 Ping 消息
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is Frame.Pong -> TODO() // 处理 Pong 消息
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}
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}
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} catch (e: Exception) {
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// 处理接收消息时的异常
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close(CloseReason(CloseReason.Codes.NORMAL, "Client disconnected"))
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e.printStackTrace()
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} finally {
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clients.remove(this) // 确保在连接关闭时移除客户端
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}
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}
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route("/api/iva") {
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// 上传分析结果
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post("/saveVideoAnalyticsData") {
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val request = call.receive<VideoAnalyticsRequest>()
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// todo 上传这里未做测试
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call.respond(BaseResponse(data = VideoDao.insertVideoAnalyticsData(request)))
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}
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authenticate {
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post("/createVideoTask") {
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val multipart = call.receiveMultipart() //1G
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// 确保 uploads 目录存在
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val uploadDir = File(VIDEO_INPUT_PATH)
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if (!uploadDir.exists()) {
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if (!uploadDir.mkdirs()) {
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println("无法创建目录")
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throw IOException("Failed to create upload directory.")
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}
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// 上传分析结果
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post("/saveVideoAnalyticsData") {
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val request = call.receive<VideoAnalyticsRequest>()
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// todo 上传这里未做测试
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call.respond(BaseResponse(data = VideoDao.insertVideoAnalyticsData(request)))
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}
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authenticate {
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post("/createVideoTask") {
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val multipart = call.receiveMultipart() //1G
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// 确保 uploads 目录存在
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val uploadDir = File(VIDEO_INPUT_PATH)
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if (!uploadDir.exists()) {
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if (!uploadDir.mkdirs()) {
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println("无法创建目录")
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throw IOException("Failed to create upload directory.")
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}
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var fileName = ""
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var name = ""
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var datetime = ""
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broadcastMessage("正在上传数据")
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}
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var fileName = ""
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var name = ""
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var datetime = ""
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broadcastMessage("正在上传数据")
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withContext(Dispatchers.IO) {
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multipart.forEachPart { part ->
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when (part) {
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is PartData.FileItem -> {
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fileName = part.originalFileName ?: "unknown"
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val file = File("$VIDEO_INPUT_PATH$fileName") // 保存路径
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//ktor3
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withContext(Dispatchers.IO) {
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multipart.forEachPart { part ->
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when (part) {
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is PartData.FileItem -> {
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fileName = part.originalFileName ?: "unknown"
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val file = File("$VIDEO_INPUT_PATH$fileName") // 保存路径
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//ktor3
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// file.outputStream().use { outputStream ->
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// val writableChannel = Channels.newChannel(outputStream)
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// part.provider().copyTo(writableChannel) // 复制到 WritableByteChannel
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// }
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//ktor2
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part.streamProvider().use { inputStream ->
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file.outputStream().buffered().use { outputStream ->
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inputStream.copyTo(outputStream)
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}
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//ktor2
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part.streamProvider().use { inputStream ->
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file.outputStream().buffered().use { outputStream ->
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inputStream.copyTo(outputStream)
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}
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}
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is PartData.FormItem -> {
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when (part.name) {
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"projectName" -> name = part.value
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"projectDatetime" -> datetime = part.value
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}
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}
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else -> part.dispose()
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}
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is PartData.FormItem -> {
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when (part.name) {
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"projectName" -> name = part.value
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"projectDatetime" -> datetime = part.value
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}
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}
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else -> part.dispose()
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}
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}
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call.respond(BaseResponse(message = "上传成功", data = null))
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broadcastMessage("上传完成，开始启动AI引擎")
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val command = listOf(
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"/usr/bin/python3",
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"/home/xhcp/mine/IntelligentVideoAnalytics/AI_Project/DeepStream_Action_Recognition/core/final.py",
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"$VIDEO_INPUT_PATH$fileName",
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datetime,
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name
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}
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call.respond(BaseResponse(message = "上传成功", data = null))
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broadcastMessage("上传完成，开始启动AI引擎")
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val command = listOf(
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"/usr/bin/python3",
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"/home/xhcp/mine/IntelligentVideoAnalytics/AI_Project/DeepStream_Action_Recognition/core/final.py",
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"$VIDEO_INPUT_PATH$fileName",
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datetime,
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name
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)
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println("-----------------" + command.joinToString(" "))
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runCommand(command) {
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println(it)
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}
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}
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// 获取已分析视频列表
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get("/getVideoList") {
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val name = call.parameters["name"]
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val res = VideoDao.getVideoList(name)
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call.respond(BaseResponse(data = res))
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}
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// 获取某视频分析详情
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get("/getAnalyticsDetailByVideoId") {
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// 获取 vId 参数
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val vIdParam = call.parameters["vId"]
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val vId = vIdParam?.toIntOrNull() // 将 vId 转换为 Int，确保安全
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if (vId == null) {
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call.respond(BaseResponse(status = true, message = "Invalid vId", data = null))
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return@get
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}
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// 查询视频信息
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val video = VideoDao.getAnalyticsDetailByVideoId(vId)
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if (video == null) {
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call.respond(BaseResponse(status = false, message = "不存在该视频", data = null))
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} else {
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// 查询相关的分析详情
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val details = VideoDao.selectVideoDetailByVid(vId)
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// 用于返回的数据
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val yTotalData = mutableListOf<Pair<String, Int>>() // (时间， 总人数)
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val yMaskedData = mutableListOf<Pair<String, Int>>() // (时间， 佩戴口罩人数)
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val areaData = mutableListOf<List<Area>>()
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val detailList = mutableListOf<DetailItem>()
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// 颜色映射
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val colors = mapOf(
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"feed" to "rgba(0, 255, 0, 0.4)", // 淡绿色
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"disinfection" to "rgba(0, 0, 255, 0.4)", // 淡蓝色
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"other" to "rgba(255, 0, 0, 0.4)" // 淡红色
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)
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println("-----------------" + command.joinToString(" "))
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runCommand(command) {
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println(it)
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}
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}
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// 获取已分析视频列表
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get("/getVideoList") {
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val name = call.parameters["name"]
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val res = VideoDao.getVideoList(name)
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call.respond(BaseResponse(data = res))
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}
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// 获取某视频分析详情
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get("/getAnalyticsDetailByVideoId") {
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// 获取 vId 参数
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val vIdParam = call.parameters["vId"]
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val vId = vIdParam?.toIntOrNull() // 将 vId 转换为 Int，确保安全
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if (vId == null) {
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call.respond(BaseResponse(status = true, message = "Invalid vId", data = null))
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return@get
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}
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// 查询视频信息
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val video = VideoDao.getAnalyticsDetailByVideoId(vId)
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if (video == null) {
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call.respond(BaseResponse(status = false, message = "不存在该视频", data = null))
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} else {
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// 查询相关的分析详情
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val details = VideoDao.selectVideoDetailByVid(vId)
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// 生成 yTotalData 和 yMaskedData，同时计算 areaData
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var lastAction: String? = null
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var areaStartTime: String? = null
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var currentColor: String? = null
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// 用于返回的数据
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val yTotalData = mutableListOf<Pair<String, Int>>() // (时间， 总人数)
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val yMaskedData = mutableListOf<Pair<String, Int>>() // (时间， 佩戴口罩人数)
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val areaData = mutableListOf<List<Area>>()
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val detailList = mutableListOf<DetailItem>()
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// 颜色映射
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val colors = mapOf(
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"feed" to "rgba(0, 255, 0, 0.4)", // 淡绿色
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"disinfection" to "rgba(0, 0, 255, 0.4)", // 淡蓝色
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"other" to "rgba(255, 0, 0, 0.4)" // 淡红色
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)
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// 生成 yTotalData 和 yMaskedData，同时计算 areaData
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var lastAction: String? = null
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var areaStartTime: String? = null
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var currentColor: String? = null
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for (detail in details) {
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// 获取视频开始时间
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val vStartDatetime: LocalDateTime = video[vStartDateTime]!!
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val timeStr = vStartDatetime.toJavaLocalDateTime()
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.plusSeconds(detail.a_time_stamp.toLong())
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.format(DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"))
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for (detail in details) {
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// 获取视频开始时间
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val vStartDatetime: LocalDateTime = video[vStartDateTime]!!
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val timeStr = vStartDatetime.toJavaLocalDateTime()
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.plusSeconds(detail.a_time_stamp.toLong())
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.format(DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"))
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// 添加总人数和口罩佩戴人数
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yTotalData.add(timeStr to detail.a_total_people)
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yMaskedData.add(timeStr to detail.a_total_people_masked)
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// 添加总人数和口罩佩戴人数
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yTotalData.add(timeStr to detail.a_total_people)
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yMaskedData.add(timeStr to detail.a_total_people_masked)
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// 处理 areaData，根据 a_action 判断是否需要创建新的区域
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if (detail.a_action != "--") { // 只处理非 "--" 动作
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if (lastAction == null || lastAction != detail.a_action) {
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// 如果上一个动作和当前动作不同，并且 areaStartTime 已经存在，创建新的区域
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if (areaStartTime != null) {
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areaData.add(
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listOf(
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Area(areaStartTime, ItemStyle(currentColor ?: "#FF0000")),
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Area(timeStr, ItemStyle(currentColor ?: "#FF0000"))
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)
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)
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}
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// 添加到 detailList，记录动作开始的时刻
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detailList.add(
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DetailItem(getFriendlyActionName(detail.a_action), time = timeStr)
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)
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// 更新为新的动作
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lastAction = detail.a_action
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areaStartTime = timeStr
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currentColor = colors[detail.a_action] ?: "#FF0000" // 默认红色
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}
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} else {
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// 如果当前动作为 "--"，则结束当前区域，并重置状态
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// 处理 areaData，根据 a_action 判断是否需要创建新的区域
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if (detail.a_action != "--") { // 只处理非 "--" 动作
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if (lastAction == null || lastAction != detail.a_action) {
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// 如果上一个动作和当前动作不同，并且 areaStartTime 已经存在，创建新的区域
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if (areaStartTime != null) {
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// 添加到 detailList，记录动作开始的时刻
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detailList.add(
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DetailItem(getFriendlyActionName(detail.a_action), timeStr)
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)
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// 结束当前区域
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areaData.add(
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listOf(
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Area(areaStartTime, ItemStyle(currentColor ?: "#FF0000")),
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Area(timeStr, ItemStyle(currentColor ?: "#FF0000"))
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)
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)
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// 重置状态
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lastAction = null
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areaStartTime = null
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currentColor = null
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}
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// 添加到 detailList，记录动作开始的时刻
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detailList.add(
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DetailItem(getFriendlyActionName(detail.a_action), time = timeStr)
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)
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// 更新为新的动作
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lastAction = detail.a_action
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areaStartTime = timeStr
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currentColor = colors[detail.a_action] ?: "#FF0000" // 默认红色
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}
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} else {
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// 如果当前动作为 "--"，则结束当前区域，并重置状态
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if (areaStartTime != null) {
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// 添加到 detailList，记录动作开始的时刻
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detailList.add(
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DetailItem(getFriendlyActionName(detail.a_action), timeStr)
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)
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// 结束当前区域
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areaData.add(
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listOf(
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Area(areaStartTime, ItemStyle(currentColor ?: "#FF0000")),
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Area(timeStr, ItemStyle(currentColor ?: "#FF0000"))
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)
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)
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// 重置状态
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lastAction = null
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areaStartTime = null
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currentColor = null
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}
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}
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// 处理最后一个区域的结束时间
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if (areaStartTime != null && lastAction != null) {
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areaData.add(
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listOf(
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Area(areaStartTime, ItemStyle(currentColor ?: "#FF0000")),
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Area(yTotalData.last().first, ItemStyle(currentColor ?: "#FF0000"))
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)
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)
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}
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val analyticsData = VideoAnalyticsData(
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||||
yTotalData = yTotalData,
|
||||
yMaskedData = yMaskedData,
|
||||
areaData = areaData
|
||||
)
|
||||
// 返回数据
|
||||
call.respond(
|
||||
BaseResponse(
|
||||
data = VideoAnalyticsDetail(
|
||||
v_id = vId,
|
||||
v_name = video[VideoTable.vName],
|
||||
v_video_play_path = "http://${SERVER_PATH_OSS}:9000/video/" + video[VideoTable.vObjectName],
|
||||
v_file_name = video[VideoTable.vFileName],
|
||||
v_duration = video[VideoTable.vDuration],
|
||||
v_size = video[VideoTable.vSize],
|
||||
v_start_datetime = video[vStartDateTime]?.toString() ?: "",
|
||||
v_video_codec = video[VideoTable.vVideoCodec],
|
||||
v_audio_codec = video[VideoTable.vAudioCodec],
|
||||
v_overall_bit_rate = video[VideoTable.vOverallBitRate],
|
||||
v_resolution = video[VideoTable.vResolution],
|
||||
v_a_time = video[VideoTable.vATime].toString(),
|
||||
v_a_total_people = video[vATotalPeople], // 总人数
|
||||
v_a_count_people = video[vACountPeople], // 佩戴口罩人数
|
||||
v_a_max_stay_time = video[vAMaxStayTime], // 最大停留时间
|
||||
v_a_max_action = getFriendlyActionName(video[vAMaxAction]), // 最大动作
|
||||
v_a_average_masked_ratio = video[vAAverageMaskedRatio], // 平均佩戴口罩比例
|
||||
v_a_details = analyticsData, // 这里是计算得来的 VideoAnalyticsData
|
||||
v_details_list = detailList
|
||||
)
|
||||
}
|
||||
// 处理最后一个区域的结束时间
|
||||
if (areaStartTime != null && lastAction != null) {
|
||||
areaData.add(
|
||||
listOf(
|
||||
Area(areaStartTime, ItemStyle(currentColor ?: "#FF0000")),
|
||||
Area(yTotalData.last().first, ItemStyle(currentColor ?: "#FF0000"))
|
||||
)
|
||||
)
|
||||
}
|
||||
val analyticsData = VideoAnalyticsData(
|
||||
yTotalData = yTotalData,
|
||||
yMaskedData = yMaskedData,
|
||||
areaData = areaData
|
||||
)
|
||||
// 返回数据
|
||||
call.respond(
|
||||
BaseResponse(
|
||||
data = VideoAnalyticsDetail(
|
||||
v_id = vId,
|
||||
v_name = video[VideoTable.vName],
|
||||
v_video_play_path = "http://${SERVER_PATH_OSS}:9000/video/" + video[VideoTable.vObjectName],
|
||||
v_file_name = video[VideoTable.vFileName],
|
||||
v_duration = video[VideoTable.vDuration],
|
||||
v_size = video[VideoTable.vSize],
|
||||
v_start_datetime = video[vStartDateTime]?.toString() ?: "",
|
||||
v_video_codec = video[VideoTable.vVideoCodec],
|
||||
v_audio_codec = video[VideoTable.vAudioCodec],
|
||||
v_overall_bit_rate = video[VideoTable.vOverallBitRate],
|
||||
v_resolution = video[VideoTable.vResolution],
|
||||
v_a_time = video[VideoTable.vATime].toString(),
|
||||
v_a_total_people = video[vATotalPeople], // 总人数
|
||||
v_a_count_people = video[vACountPeople], // 佩戴口罩人数
|
||||
v_a_max_stay_time = video[vAMaxStayTime], // 最大停留时间
|
||||
v_a_max_action = getFriendlyActionName(video[vAMaxAction]), // 最大动作
|
||||
v_a_average_masked_ratio = video[vAAverageMaskedRatio], // 平均佩戴口罩比例
|
||||
v_a_details = analyticsData, // 这里是计算得来的 VideoAnalyticsData
|
||||
v_details_list = detailList
|
||||
)
|
||||
)
|
||||
)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,46 @@
|
||||
|
||||
var aiState = "等待分析任务中"
|
||||
// 实时发送AI状态
|
||||
webSocket("/handleState") { // WebSocket 路由
|
||||
clients.add(this) // 添加当前连接的客户端
|
||||
send(aiState) // 向客户端发送连接成功消息
|
||||
try {
|
||||
incoming.consumeEach { frame -> // 持续接收消息
|
||||
when (frame) {
|
||||
is Frame.Text -> {
|
||||
aiState = frame.readText() // 更新状态
|
||||
broadcastMessage(aiState) // 使用封装的方法广播消息
|
||||
}
|
||||
|
||||
is Frame.Close -> {
|
||||
println("Closed")
|
||||
clients.remove(this)
|
||||
close() // 确保关闭 WebSocket 连接
|
||||
return@consumeEach
|
||||
}
|
||||
// 其他消息类型的处理
|
||||
is Frame.Binary -> TODO() // 处理二进制消息
|
||||
is Frame.Ping -> TODO() // 处理 Ping 消息
|
||||
is Frame.Pong -> TODO() // 处理 Pong 消息
|
||||
}
|
||||
}
|
||||
} catch (e: Exception) {
|
||||
// 处理接收消息时的异常
|
||||
close(CloseReason(CloseReason.Codes.NORMAL, "Client disconnected"))
|
||||
e.printStackTrace()
|
||||
} finally {
|
||||
clients.remove(this) // 确保在连接关闭时移除客户端
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// 拍照保存为图片 并且调用Python程序进行分析
|
||||
//get("/takePhoto") {
|
||||
// val camera = call.request.queryParameters["cameraId"]
|
||||
// if (camera.isNullOrEmpty()) {
|
||||
// call.respond(BaseResponse(status = false, message = "摄像头名称不能为空", data = null))
|
||||
// return@get
|
||||
// }
|
||||
// stopHLSStream(camera)
|
||||
// call.respond(BaseResponse(message = "摄像头流已停止", data = null))
|
||||
//}
|
||||
Reference in New Issue
Block a user