优化视频对讲
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@ -17,9 +17,6 @@ class LockDetailState {
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StreamSubscription? DetailLockInfo;
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StreamSubscription? SuccessfulDistributionNetworkEvent;
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// 添加网络质量状态变量
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final RxInt networkQualityScore = 1.obs; // 1-5分，5为最佳
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final RxString networkQualityMessage = ''.obs; // 网络质量提示信息
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String lockNetToken = '0';
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int differentialTime = 0; // 服务器时间与本地时间差值
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bool isHaveNetwork = true;
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@ -408,6 +408,9 @@ class LockMonitoringLogic extends BaseGetXController {
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_getUDPStatusRefreshUIAction();
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initRecorder();
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// 页面加载时自动发起接听请求
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initiateUdpAnswerAction();
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}
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@override
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@ -47,7 +47,7 @@ class LockMonitoringState {
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// 定时器如果发送了接听的命令 而没收到回复就每秒重复发送10次
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late Timer answerTimer = Timer(const Duration(seconds: 1), () {}); //接听命令定时器
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RxInt answerSeconds = 0.obs;
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RxBool isClickAnswer = false.obs; //是否点击了接听按钮
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RxBool isClickAnswer = true.obs; //是否点击了接听按钮
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late Timer hangUpTimer = Timer(const Duration(seconds: 1), () {}); //挂断命令定时器
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RxInt hangUpSeconds = 0.obs;
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@ -1,5 +1,6 @@
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import 'dart:async';
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import 'dart:io';
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import 'dart:math';
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import 'dart:ui' as ui;
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import 'package:flutter/foundation.dart';
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@ -37,9 +38,9 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
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final LockDetailState lockDetailState = Get.put(LockDetailLogic()).state;
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int bufferSize = 25; // 初始化为默认大小
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int bufferSize = 2; // 初始化为默认大小，减小缓冲区以降低延迟
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int audioBufferSize = 20; // 音频默认缓冲2帧
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int audioBufferSize = 3; // 音频默认缓冲3帧，减少音频延迟
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// 回绕阈值，动态调整，frameSeq较小时阈值也小
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int _getFrameSeqRolloverThreshold(int lastSeq) {
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@ -88,6 +89,44 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
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bool _waitingForIFrame = false;
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int? lastDecodedIFrameSeq;
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// 新增：缓冲区满载处理相关变量
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int _consecutiveFullBufferCount = 0; // 连续缓冲区满载次数
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int _maxConsecutiveFullBufferCount = 3; // 最大连续满载次数，超过此值将采取措施，降低为3以更快响应
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bool _isAdjustingForBufferFull = false; // 是否正在为缓冲区满载调整
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// 新增：记录最近一次视频画面开始渲染的时间
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DateTime? _lastVideoRenderTime;
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// 新增：自适应缓冲区大小相关变量
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int _currentBufferSize = 3; // 当前缓冲区大小
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int _lastBufferSizeAdjustmentTime = 0; // 上次缓冲区大小调整时间
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int _bufferSizeAdjustmentCooldown = 2000; // 缓冲区大小调整冷却时间(毫秒)
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// 新增：网络状况评估相关变量
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int _lastNetworkQualityCheckTime = 0; // 上次网络质量检查时间
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int _framesProcessedSinceLastCheck = 0; // 自上次检查以来处理的帧数
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int _framesDroppedSinceLastCheck = 0; // 自上次检查以来丢弃的帧数
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double _currentNetworkQualityScore = 1.0; // 当前网络质量评分(0.0-1.0, 1.0为最佳)
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// 网络质量评估相关变量
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List<int> _frameReceiveTimes = []; // 存储帧接收时间戳
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List<int> _frameSeqList = []; // 存储帧序列号用于计算丢包
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int _totalFramesReceived = 0; // 总接收帧数
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int _lostFrames = 0; // 丢失帧数
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int _lastFrameSeqNum = -1; // 上一帧序列号
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DateTime? _testStartTime; // 测试开始时间
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Timer? _networkQualityTestTimer; // 网络质量评估定时器
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// 包、帧和关键帧统计变量
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int _totalPacketsReceived = 0; // 总接收包数
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int _totalFramesReceivedCount = 0; // 总接收帧数
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int _iFramesReceived = 0; // 接收到的关键帧数（I帧）
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int _pFramesReceived = 0; // 接收到的预测帧数（P帧）
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int _processedFrames = 0; // 已处理的帧数
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int _droppedFrames = 0; // 丢弃的帧数
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int _framesInBuffer = 0; // 进入缓冲区的帧数
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int _bufferSize = 0; // 缓冲区大小
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// 初始化视频解码器
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Future<void> _initVideoDecoder() async {
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@ -128,16 +167,20 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
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height: height,
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codecType: 'h264',
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);
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AppLog.log('解码器配置的宽高为：${config.width}x${config.height}');
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// 初始化解码器并获取textureId
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final textureId = await VideoDecodePlugin.initDecoder(config);
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if (textureId != null) {
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Future.microtask(() => state.textureId.value = textureId);
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AppLog.log('视频解码器初始化成功：textureId=$textureId');
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VideoDecodePlugin.setOnFrameRenderedListener((textureId) {
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AppLog.log('已经开始渲染=======');
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// 记录视频开始渲染时间
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_lastVideoRenderTime = DateTime.now();
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// 只有真正渲染出首帧时才关闭loading
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Future.microtask(() => state.isLoading.value = false);
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if (state.isLoading.value) {
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Future.microtask(() => state.isLoading.value = false);
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} else {
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AppLog.log('视频已在渲染状态，保持当前状态');
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}
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});
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} else {
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AppLog.log('视频解码器初始化失败');
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@ -243,6 +286,110 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
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}
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_lastFrameSeq = frameSeq;
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}
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// 记录帧接收
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recordFrameReceived(frameSeq, frameType);
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// 优化：对于低延迟场景，仅保留最新的帧以减少延迟
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bool isVideoRendering = state.textureId.value != null &&
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(state.isLoading.isFalse || _lastVideoRenderTime != null);
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if (isVideoRendering) {
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// 如果视频已经开始渲染，优先保留最新的I帧和其关联的P帧
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if (frameType == TalkDataH264Frame_FrameTypeE.I) {
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// 对于新的I帧，移除旧的I帧和其关联的P帧
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_removeOldFramesForIFrame(frameSeq);
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// 当接收到新I帧时，动态调整缓冲区大小以适应当前网络状况
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_adjustBufferSizeForNetworkCondition();
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} else {
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// 对于P帧，确保它关联到有效的I帧
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_cleanOldPFrameForCurrentIFrame(frameSeq, frameSeqI);
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}
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} else {
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// 视频未渲染时，按原有逻辑处理
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if (state.h264FrameBuffer.length >= state.maxFrameBufferSize) {
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// 检查是否已经有视频开始渲染
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bool isVideoRendering = state.textureId.value != null &&
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(state.isLoading.isFalse || _lastVideoRenderTime != null);
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// 如果视频已经在渲染，我们采用更智能的缓冲区清理策略
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if (isVideoRendering) {
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_consecutiveFullBufferCount++;
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// 当连续多次缓冲区满载时，采取特殊处理策略
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if (_consecutiveFullBufferCount >= _maxConsecutiveFullBufferCount) {
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// 计算当前网络质量并调整缓冲区大小
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_evaluateCurrentNetworkQuality();
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// 查找所有非关键帧（非I帧）进行清理
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final framesToRemove = <int>[];
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for (int i = 0; i < state.h264FrameBuffer.length; i++) {
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if (state.h264FrameBuffer[i]['frameType'] != TalkDataH264Frame_FrameTypeE.I) {
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framesToRemove.add(i);
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}
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}
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// 从后往前删除，避免索引变化问题
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framesToRemove.reversed.forEach((index) {
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state.h264FrameBuffer.removeAt(index);
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recordDroppedFrame();
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});
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// 如果仍有过多帧，保留最新的I帧及相关的P帧
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if (state.h264FrameBuffer.length > _currentBufferSize ~/ 2) {
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// 找到最后一个I帧的位置
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int lastIFrameIndex = -1;
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for (int i = state.h264FrameBuffer.length - 1; i >= 0; i--) {
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if (state.h264FrameBuffer[i]['frameType'] == TalkDataH264Frame_FrameTypeE.I) {
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lastIFrameIndex = i;
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break;
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}
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}
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// 如果找到I帧，只保留I帧及其后续的P帧，删除前面的帧
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if (lastIFrameIndex > 0) {
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for (int i = 0; i < lastIFrameIndex; i++) {
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state.h264FrameBuffer.removeAt(0);
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recordDroppedFrame();
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}
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} else {
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// 如果没有I帧，只保留最新的半数帧
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while (state.h264FrameBuffer.length > _currentBufferSize ~/ 2) {
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state.h264FrameBuffer.removeAt(0);
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recordDroppedFrame();
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}
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}
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}
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_consecutiveFullBufferCount = 0; // 重置计数
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_isAdjustingForBufferFull = false;
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} else {
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// 非连续满载情况下，采用保守清理策略
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int pbIndex = state.h264FrameBuffer.indexWhere((f) => f['frameType'] == TalkDataH264Frame_FrameTypeE.P);
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if (pbIndex != -1) {
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state.h264FrameBuffer.removeAt(pbIndex);
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recordDroppedFrame(); // 记录丢弃的帧
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} else {
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state.h264FrameBuffer.removeAt(0);
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recordDroppedFrame(); // 记录丢弃的帧
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}
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}
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} else {
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// 视频尚未渲染时，使用原始策略
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int pbIndex = state.h264FrameBuffer.indexWhere((f) => f['frameType'] == TalkDataH264Frame_FrameTypeE.P);
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if (pbIndex != -1) {
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state.h264FrameBuffer.removeAt(pbIndex);
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recordDroppedFrame(); // 记录丢弃的帧
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} else {
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state.h264FrameBuffer.removeAt(0);
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recordDroppedFrame(); // 记录丢弃的帧
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}
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}
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}
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}
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// 创建包含帧数据和类型的Map
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final Map<String, dynamic> frameMap = {
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'frameData': frameData,
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@ -253,18 +400,169 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
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'scpMessage': scpMessage,
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};
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// 如果缓冲区超出最大大小，优先丢弃P/B帧
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while (state.h264FrameBuffer.length >= state.maxFrameBufferSize) {
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int pbIndex = state.h264FrameBuffer.indexWhere((f) => f['frameType'] == TalkDataH264Frame_FrameTypeE.P);
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if (pbIndex != -1) {
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state.h264FrameBuffer.removeAt(pbIndex);
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} else {
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state.h264FrameBuffer.removeAt(0);
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}
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}
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// 将帧添加到缓冲区
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state.h264FrameBuffer.add(frameMap);
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recordFrameInBuffer(); // 记录进入缓冲区的帧
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// 重置连续满载计数（只有在缓冲区未满时）
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if (state.h264FrameBuffer.length < state.maxFrameBufferSize) {
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_consecutiveFullBufferCount = 0;
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}
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}
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// 辅助方法：移除旧的I帧和其关联的P帧
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void _removeOldFramesForIFrame(int newIFrameSeq) {
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// 保留最新的I帧和相关的P帧，移除旧的I帧和其关联的P帧
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final List<Map<String, dynamic>> framesToKeep = [];
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// 分别收集I帧和P帧
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final List<Map<String, dynamic>> iFrames = [];
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final List<Map<String, dynamic>> pFrames = [];
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for (var frame in state.h264FrameBuffer) {
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if (frame['frameType'] == TalkDataH264Frame_FrameTypeE.I) {
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iFrames.add(frame);
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} else {
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pFrames.add(frame);
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}
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}
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// 按frameSeq排序I帧
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iFrames.sort((a, b) => (a['frameSeq'] as int).compareTo(b['frameSeq'] as int));
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// 保留最新的I帧（即当前正在添加的新I帧）
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final int maxIFramesToKeep = 2; // 保留最多2个I帧以确保平滑过渡
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final int startIdx = max(0, iFrames.length - maxIFramesToKeep);
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for (int i = startIdx; i < iFrames.length; i++) {
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framesToKeep.add(iFrames[i]);
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}
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// 对于P帧，只保留与保留的I帧关联的P帧
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for (var pFrame in pFrames) {
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int refIFrameSeq = pFrame['frameSeqI'];
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bool shouldKeep = false;
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// 检查该P帧引用的I帧是否被保留
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for (var keptIFrame in framesToKeep) {
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if (keptIFrame['frameType'] == TalkDataH264Frame_FrameTypeE.I &&
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keptIFrame['frameSeq'] == refIFrameSeq) {
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shouldKeep = true;
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break;
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}
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}
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if (shouldKeep) {
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framesToKeep.add(pFrame);
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} else {
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recordDroppedFrame(); // 记录丢弃的帧
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}
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}
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// 用筛选后的帧替换原缓冲区
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state.h264FrameBuffer.clear();
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state.h264FrameBuffer.addAll(framesToKeep);
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}
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// 辅助方法：清理当前I帧的旧P帧
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void _cleanOldPFrameForCurrentIFrame(int frameSeq, int frameSeqI) {
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// 为当前I帧保留最新的P帧，移除过旧的P帧
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final List<Map<String, dynamic>> framesToKeep = [];
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final List<Map<String, dynamic>> framesToRemove = [];
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// 首先添加所有非当前I帧引用的帧
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for (var frame in state.h264FrameBuffer) {
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if (frame['frameSeqI'] != frameSeqI || frame['frameType'] == TalkDataH264Frame_FrameTypeE.I) {
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framesToKeep.add(frame);
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}
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}
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// 收集当前I帧引用的P帧
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final List<Map<String, dynamic>> currentIFramePFrames = [];
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for (var frame in state.h264FrameBuffer) {
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if (frame['frameSeqI'] == frameSeqI && frame['frameType'] == TalkDataH264Frame_FrameTypeE.P) {
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currentIFramePFrames.add(frame);
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}
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}
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// 按frameSeq排序P帧
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currentIFramePFrames.sort((a, b) => (a['frameSeq'] as int).compareTo(b['frameSeq'] as int));
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// 保留最新的P帧（例如保留最近的5个）
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final int maxPFramesToKeep = 5;
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final int startIdx = max(0, currentIFramePFrames.length - maxPFramesToKeep);
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for (int i = startIdx; i < currentIFramePFrames.length; i++) {
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framesToKeep.add(currentIFramePFrames[i]);
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}
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// 记录被丢弃的P帧
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for (int i = 0; i < startIdx; i++) {
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recordDroppedFrame();
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}
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// 用筛选后的帧替换原缓冲区
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state.h264FrameBuffer.clear();
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state.h264FrameBuffer.addAll(framesToKeep);
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}
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/// 根据网络状况动态调整缓冲区大小
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void _adjustBufferSizeForNetworkCondition() {
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// 获取当前时间
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int currentTime = DateTime.now().millisecondsSinceEpoch;
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// 检查是否在冷却期内
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if (currentTime - _lastBufferSizeAdjustmentTime < _bufferSizeAdjustmentCooldown) {
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return;
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}
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// 更新最后调整时间
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_lastBufferSizeAdjustmentTime = currentTime;
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// 根据当前网络质量评分调整缓冲区大小
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if (_currentNetworkQualityScore > 0.7) {
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// 网络状况良好，使用较小缓冲区以降低延迟
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_currentBufferSize = state.adaptiveBufferSizeMin;
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} else if (_currentNetworkQualityScore > 0.4) {
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// 网络状况一般，使用中等缓冲区以平衡延迟和稳定性
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_currentBufferSize = (state.adaptiveBufferSizeMin + state.adaptiveBufferSizeMax) ~/ 2;
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} else {
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// 网络状况较差，使用较大缓冲区以减少卡顿
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_currentBufferSize = state.adaptiveBufferSizeMax;
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}
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AppLog.log('根据网络状况调整缓冲区大小: ${_currentBufferSize} (当前网络质量评分: ${_currentNetworkQualityScore.toStringAsFixed(2)})');
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}
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/// 评估当前网络质量
|
||||
void _evaluateCurrentNetworkQuality() {
|
||||
int currentTime = DateTime.now().millisecondsSinceEpoch;
|
||||
|
||||
// 检查是否到了网络质量检查间隔
|
||||
if (currentTime - _lastNetworkQualityCheckTime < state.networkQualityCheckIntervalMs) {
|
||||
return;
|
||||
}
|
||||
|
||||
_lastNetworkQualityCheckTime = currentTime;
|
||||
|
||||
// 计算丢帧率
|
||||
double dropRate = 0.0;
|
||||
int totalProcessed = _framesProcessedSinceLastCheck + _framesDroppedSinceLastCheck;
|
||||
if (totalProcessed > 0) {
|
||||
dropRate = _framesDroppedSinceLastCheck / totalProcessed;
|
||||
}
|
||||
|
||||
// 更新网络质量评分 (基于丢帧率，评分越高网络越好)
|
||||
_currentNetworkQualityScore = 1.0 - dropRate;
|
||||
if (_currentNetworkQualityScore < 0) {
|
||||
_currentNetworkQualityScore = 0.0;
|
||||
}
|
||||
|
||||
AppLog.log('网络质量评估: 丢帧率=${dropRate.toStringAsFixed(2)}, 网络质量评分=${_currentNetworkQualityScore.toStringAsFixed(2)}');
|
||||
|
||||
// 重置计数器
|
||||
_framesProcessedSinceLastCheck = 0;
|
||||
_framesDroppedSinceLastCheck = 0;
|
||||
}
|
||||
|
||||
/// 启动帧处理定时器
|
||||
@ -272,8 +570,8 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
|
||||
// 取消已有定时器
|
||||
state.frameProcessTimer?.cancel();
|
||||
|
||||
// 计算定时器间隔，确保以目标帧率处理帧
|
||||
final int intervalMs = (1000 / state.targetFps).round();
|
||||
// 使用配置的间隔时间
|
||||
final int intervalMs = state.frameProcessIntervalMs;
|
||||
|
||||
// 创建新定时器
|
||||
state.frameProcessTimer = Timer.periodic(Duration(milliseconds: intervalMs), (timer) {
|
||||
@ -984,4 +1282,215 @@ class TalkViewNativeDecodeLogic extends BaseGetXController {
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
/// 记录帧接收
|
||||
void recordFrameReceived(int frameSeq, TalkDataH264Frame_FrameTypeE frameType) {
|
||||
_totalFramesReceivedCount++;
|
||||
|
||||
// 根据帧类型更新计数
|
||||
if (frameType == TalkDataH264Frame_FrameTypeE.I) {
|
||||
_iFramesReceived++;
|
||||
} else if (frameType == TalkDataH264Frame_FrameTypeE.P) {
|
||||
_pFramesReceived++;
|
||||
}
|
||||
|
||||
// 计算丢包 - 修复：添加合理的帧序号差异限制，避免异常高的丢包计算
|
||||
if (_lastFrameSeqNum != -1) {
|
||||
if (frameSeq > _lastFrameSeqNum + 1) {
|
||||
// 计算中间缺失的帧数，但限制最大丢失数量以防止异常值
|
||||
int gap = frameSeq - _lastFrameSeqNum - 1;
|
||||
// 设置最大允许的帧间隙，防止因为帧序列号回绕或异常导致的错误计算
|
||||
int maxAllowedGap = 50; // 可根据实际情况调整
|
||||
if (gap > maxAllowedGap) {
|
||||
// 如果间隙过大，可能是帧序列号回绕或其他异常，不计入丢失帧
|
||||
AppLog.log('检测到帧序列号异常跳跃: gap=$gap, 当前frameSeq=$frameSeq, 上一个frameSeq=$_lastFrameSeqNum');
|
||||
} else {
|
||||
_lostFrames += gap;
|
||||
}
|
||||
} else if (frameSeq <= _lastFrameSeqNum && frameSeq < 100 && _lastFrameSeqNum > 1000) {
|
||||
// 检测到帧序列号回绕（从大数值回到小数值），重置参考值
|
||||
// 这种情况通常发生在新的视频流开始或流重启
|
||||
AppLog.log('检测到帧序列号回绕: 从 $_lastFrameSeqNum 回到 $frameSeq');
|
||||
_lastFrameSeqNum = frameSeq;
|
||||
}
|
||||
}
|
||||
_lastFrameSeqNum = frameSeq;
|
||||
|
||||
// 记录接收时间
|
||||
_frameReceiveTimes.add(DateTime.now().millisecondsSinceEpoch);
|
||||
_frameSeqList.add(frameSeq);
|
||||
|
||||
// 只保留最近的100个帧记录
|
||||
if (_frameReceiveTimes.length > 100) {
|
||||
_frameReceiveTimes.removeAt(0);
|
||||
_frameSeqList.removeAt(0);
|
||||
}
|
||||
}
|
||||
|
||||
/// 记录包接收
|
||||
void recordPacketReceived() {
|
||||
_totalPacketsReceived++;
|
||||
}
|
||||
|
||||
/// 记录已处理的帧
|
||||
void recordProcessedFrame() {
|
||||
_processedFrames++;
|
||||
_framesProcessedSinceLastCheck++; // 用于网络质量评估
|
||||
}
|
||||
|
||||
/// 记录丢弃的帧
|
||||
void recordDroppedFrame() {
|
||||
_droppedFrames++;
|
||||
_framesDroppedSinceLastCheck++; // 用于网络质量评估
|
||||
}
|
||||
|
||||
/// 记录进入缓冲区的帧
|
||||
void recordFrameInBuffer() {
|
||||
_framesInBuffer++;
|
||||
}
|
||||
|
||||
/// 开始网络质量评估
|
||||
void startNetworkQualityAssessment() {
|
||||
resetNetworkQualityAssessmentVariables();
|
||||
_testStartTime = DateTime.now();
|
||||
|
||||
// 初始化统计计数器
|
||||
_bufferSize = state.maxFrameBufferSize; // 记录缓冲区大小
|
||||
|
||||
// 启动定时器每秒评估一次网络质量
|
||||
_networkQualityTestTimer = Timer.periodic(const Duration(seconds: 1), (timer) {
|
||||
_evaluateNetworkQuality();
|
||||
});
|
||||
}
|
||||
|
||||
/// 停止网络质量评估
|
||||
void stopNetworkQualityAssessment() {
|
||||
_networkQualityTestTimer?.cancel();
|
||||
_networkQualityTestTimer = null;
|
||||
}
|
||||
|
||||
/// 重置网络质量评估变量
|
||||
void resetNetworkQualityAssessmentVariables() {
|
||||
_totalFramesReceived = 0;
|
||||
_lostFrames = 0;
|
||||
_lastFrameSeqNum = -1;
|
||||
_frameReceiveTimes.clear();
|
||||
_frameSeqList.clear();
|
||||
_testStartTime = null;
|
||||
|
||||
// 重置统计计数器
|
||||
_totalPacketsReceived = 0;
|
||||
_totalFramesReceivedCount = 0;
|
||||
_iFramesReceived = 0;
|
||||
_pFramesReceived = 0;
|
||||
_processedFrames = 0;
|
||||
_droppedFrames = 0;
|
||||
_framesInBuffer = 0;
|
||||
}
|
||||
|
||||
/// 评估网络质量
|
||||
void _evaluateNetworkQuality() {
|
||||
if (_testStartTime == null) return;
|
||||
|
||||
final elapsed = DateTime.now().difference(_testStartTime!).inSeconds;
|
||||
if (elapsed == 0) return;
|
||||
|
||||
// 计算丢包率 - 确保丢包率不会超过100%
|
||||
double lossRate = 0.0;
|
||||
if (_totalFramesReceivedCount > 0) {
|
||||
lossRate = (_lostFrames / _totalFramesReceivedCount) * 100;
|
||||
// 限制丢包率不超过100%
|
||||
if (lossRate > 100.0) {
|
||||
lossRate = 100.0;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
// 计算抖动 (基于相邻帧的时间间隔变化)
|
||||
if (_frameReceiveTimes.length >= 2) {
|
||||
List<int> intervals = [];
|
||||
for (int i = 1; i < _frameReceiveTimes.length; i++) {
|
||||
intervals.add(_frameReceiveTimes[i] - _frameReceiveTimes[i-1]);
|
||||
}
|
||||
}
|
||||
|
||||
// 根据网络质量动态调整缓冲区大小
|
||||
_adjustBufferSizeBasedOnNetworkQuality();
|
||||
}
|
||||
|
||||
/// 根据丢包率、帧率和抖动确定网络质量等级
|
||||
String _getNetworkQualityLevel(double lossRate, double frameRate, double jitter) {
|
||||
if (lossRate < 1.0 && frameRate > 15.0 && jitter < 50.0) {
|
||||
return "优秀";
|
||||
} else if (lossRate < 3.0 && frameRate > 10.0 && jitter < 100.0) {
|
||||
return "良好";
|
||||
} else if (lossRate < 5.0 && frameRate > 5.0 && jitter < 200.0) {
|
||||
return "一般";
|
||||
} else {
|
||||
return "较差";
|
||||
}
|
||||
}
|
||||
|
||||
/// 预测视频卡顿概率
|
||||
String _predictStutterProbability(double lossRate, double frameRate, double jitter) {
|
||||
if (lossRate < 2.0 && frameRate > 10.0 && jitter < 100.0) {
|
||||
return "低风险 - 视频流畅";
|
||||
} else if (lossRate <= 5.0 && frameRate >= 5.0 && jitter <= 200.0) {
|
||||
return "中风险 - 可能轻微卡顿";
|
||||
} else {
|
||||
return "高风险 - 可能严重卡顿";
|
||||
}
|
||||
}
|
||||
|
||||
/// 根据网络质量动态调整缓冲区大小
|
||||
void _adjustBufferSizeBasedOnNetworkQuality() {
|
||||
if (_testStartTime == null) return;
|
||||
|
||||
final elapsed = DateTime.now().difference(_testStartTime!).inSeconds;
|
||||
if (elapsed == 0) return;
|
||||
|
||||
// 计算丢包率
|
||||
double lossRate = 0.0;
|
||||
if (_totalFramesReceivedCount > 0) {
|
||||
lossRate = (_lostFrames / _totalFramesReceivedCount) * 100;
|
||||
if (lossRate > 100.0) lossRate = 100.0;
|
||||
}
|
||||
|
||||
// 计算平均接收帧率
|
||||
final avgFrameRate = _totalFramesReceivedCount / elapsed;
|
||||
|
||||
// 计算抖动
|
||||
double jitter = 0.0;
|
||||
if (_frameReceiveTimes.length >= 2) {
|
||||
List<int> intervals = [];
|
||||
for (int i = 1; i < _frameReceiveTimes.length; i++) {
|
||||
intervals.add(_frameReceiveTimes[i] - _frameReceiveTimes[i-1]);
|
||||
}
|
||||
|
||||
if (intervals.length > 1) {
|
||||
double mean = intervals.reduce((a, b) => a + b) / intervals.length;
|
||||
double variance = 0.0;
|
||||
for (int interval in intervals) {
|
||||
variance += pow(interval - mean, 2).toDouble();
|
||||
}
|
||||
variance /= intervals.length;
|
||||
jitter = sqrt(variance);
|
||||
}
|
||||
}
|
||||
|
||||
// 根据网络质量调整缓冲区大小
|
||||
if (lossRate < 2.0 && avgFrameRate > 15.0 && jitter < 50.0) {
|
||||
// 网络质量优秀 - 使用最小缓冲区以降低延迟
|
||||
_currentBufferSize = state.adaptiveBufferSizeMin;
|
||||
} else if (lossRate < 5.0 && avgFrameRate > 10.0 && jitter < 100.0) {
|
||||
// 网络质量良好 - 使用中等偏小缓冲区
|
||||
_currentBufferSize = (state.adaptiveBufferSizeMin + state.adaptiveBufferSizeMax) ~/ 3;
|
||||
} else if (lossRate < 10.0 && avgFrameRate > 5.0 && jitter < 200.0) {
|
||||
// 网络质量一般 - 使用中等偏大缓冲区
|
||||
_currentBufferSize = ((state.adaptiveBufferSizeMin + state.adaptiveBufferSizeMax) ~/ 2 + state.adaptiveBufferSizeMax) ~/ 2;
|
||||
} else {
|
||||
// 网络质量差 - 使用最大缓冲区以减少卡顿
|
||||
_currentBufferSize = state.adaptiveBufferSizeMax;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -109,8 +109,12 @@ class TalkViewNativeDecodeState {
|
||||
|
||||
// H264帧缓冲区相关
|
||||
final List<Map<String, dynamic>> h264FrameBuffer = <Map<String, dynamic>>[]; // H264帧缓冲区，存储帧数据和类型
|
||||
int maxFrameBufferSize = 25; // 最大缓冲区大小
|
||||
int maxFrameBufferSize = 3; // 最大缓冲区大小，减小以降低延迟
|
||||
final int targetFps = 25; // 目标解码帧率,只是为了快速填充native的缓冲区
|
||||
final int adaptiveBufferSizeMin = 2; // 自适应缓冲区最小大小
|
||||
final int adaptiveBufferSizeMax = 6; // 自适应缓冲区最大大小
|
||||
final int networkQualityCheckIntervalMs = 2000; // 网络质量检查间隔(毫秒)
|
||||
final int frameProcessIntervalMs = 10; // 帧处理间隔(毫秒)，提高响应速度
|
||||
Timer? frameProcessTimer; // 帧处理定时器
|
||||
bool isProcessingFrame = false; // 是否正在处理帧
|
||||
int lastProcessedTimestamp = 0; // 上次处理帧的时间戳
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user