diff --git a/AlgorithmModule/src/QX_Merge_Analysis.cpp b/AlgorithmModule/src/QX_Merge_Analysis.cpp index 8c68557..fa80a18 100644 --- a/AlgorithmModule/src/QX_Merge_Analysis.cpp +++ b/AlgorithmModule/src/QX_Merge_Analysis.cpp @@ -402,6 +402,17 @@ int QX_Merge_Analysis::StartAnalysis() int QX_Merge_Analysis::Analysis_single_Config(QXAnalysis_Config *pconfig, QX_channel_List *pqxList, int qx_type, std::shared_ptr pchannelLog) { + // AD 单通道参数判定受 merge_analysy_region_sf 通道过滤约束 + if (qx_type == QX_ANALYSIS_AD && m_pbaseCheckFunction) + { + std::vector merge_analysy_region_sf = m_pbaseCheckFunction->ad_check.analysis_sf.region_sf; + if (std::find(merge_analysy_region_sf.begin(), merge_analysy_region_sf.end(), pqxList->channel_name) == merge_analysy_region_sf.end()) + { + pchannelLog->AddCheckstr(PrintLevel_1, 3, "Analysis_single_Config", "merge_analysy_region_sf not found %s --> skip", pqxList->channel_name.c_str()); + return 0; + } + } + pchannelLog->AddCheckstr(PrintLevel_2, 3, "param", " okparam = %d area %f max_area %f hj %d num %d dis %f len %f md %f", pconfig->bok, pconfig->area, pconfig->sum_area, pconfig->hj, pconfig->num, pconfig->dis, pconfig->len, pconfig->density); diff --git a/example/deal.cpp b/example/deal.cpp index 3bdb8b9..692428e 100644 --- a/example/deal.cpp +++ b/example/deal.cpp @@ -1327,9 +1327,9 @@ int deal::DetImg() return 0; } -/// @brief 监控模式：每 10 秒执行一次模型推理，并把当前设备资源消耗（CPU 内存 / GPU 显存） -/// 写入 monitor.log；out 图重复覆盖保存到输入图同名 out 文件（*_in.png -> *_out.png）， -/// 当某次推理输出 out 图至少一个像素不为全黑时退出监控。 +/// @brief 监控模式：4 线程并发循环执行模型推理（压 GPU），并把当前设备资源消耗 +/// （CPU 内存 / GPU 显存）写入 monitor.log；正常（out 全黑）不写图，检测到残点 +/// （out 图至少一个像素不为全黑）时才保存对应 *_out.png 并退出监控。 /// @return 0 表示成功，非 0 表示初始化失败 int deal::MonitorRun() { @@ -1474,26 +1474,96 @@ int deal::MonitorRun() return 1; } - // 同时输出到终端和 log 文件 - auto logLine = [&logFile](const std::string &line) + // 日志互斥锁（worker 线程与主线程都会写日志） + std::mutex logMutex; + auto logLine = [&logFile, &logMutex](const std::string &line) { + std::lock_guard lock(logMutex); printf("%s\n", line.c_str()); + fflush(stdout); // 强制刷新控制台，避免 stdout 块缓冲导致显示延迟 logFile << line << std::endl; - logFile.flush(); }; - const int nIntervalSec = 1; // 1 秒 - long nRound = 0; - logLine("===== monitor start (every 10s, exit on first non-black out) ====="); + const int nThreadNum = 4; // 并发线程数（与模型 Stream_num 一致时并行度最高） + long nImageNum = (long)inImgs.size(); + + // 共享状态 + std::atomic nNextIdx{0}; // 原子分配任务索引，轮询所有图 + std::atomic nInferCount{0}; // 成功推理次数 + std::atomic nFailCount{0}; // 推理失败次数 + std::atomic bHit{false}; // 是否命中非全黑 out + std::atomic nHitIdx{-1}; // 命中的图索引 + std::atomic nHitNonZero{0}; // 命中的非零像素数 + + std::mutex saveMutex; // 保护 out 文件写入 + + logLine("===== monitor start (4 threads loop, exit on first non-black out) ====="); + + // 启动 worker 线程：循环推理压 GPU + std::vector workers; + workers.reserve(nThreadNum); + for (int t = 0; t < nThreadNum; t++) + { + workers.emplace_back([&, t]() + { + while (!bHit.load(std::memory_order_relaxed)) + { + long idx = nNextIdx.fetch_add(1, std::memory_order_relaxed) % nImageNum; + + cv::Mat outImg; + int re = pAI_Model->AIDet(inImgs[(size_t)idx], outImg); + if (re != 0 || outImg.empty()) + { + nFailCount.fetch_add(1, std::memory_order_relaxed); + continue; + } + + nInferCount.fetch_add(1, std::memory_order_relaxed); - // 初始化 CPU 采样基准（用于计算 CPU 使用率） + int nNonZero = cv::countNonZero(outImg); + if (nNonZero > 0) + { + // 有残点才写图，然后退出 + bool expected = false; + if (bHit.compare_exchange_strong(expected, true)) + { + { + std::lock_guard lock(saveMutex); + fs::path outParent = fs::path(outList[(size_t)idx]).parent_path(); + if (!outParent.empty()) + { + std::error_code ec; + fs::create_directories(outParent, ec); + } + cv::imwrite(outList[(size_t)idx], outImg); + } + nHitIdx.store(idx, std::memory_order_relaxed); + nHitNonZero.store(nNonZero, std::memory_order_relaxed); + logLine("[hit] thread " + std::to_string(t) + " out image " + + okInList[(size_t)idx] + " non-zero pixels: " + + std::to_string(nNonZero) + " -> " + outList[(size_t)idx]); + } + break; + } + } + }); + } + + // 主线程：资源监控（持续循环采样），直到命中退出 struct rusage usagePrev; getrusage(RUSAGE_SELF, &usagePrev); CPUStat cpuStatPrev; getSystemCPUStat(cpuStatPrev); auto wallPrev = std::chrono::steady_clock::now(); - while (true) + long nRound = 0; + + // GPU 显存采样很慢（内部执行 nvidia-smi），降低采样频率避免阻塞主循环 + long gpuUsedMB = -1; + long gpuTotalMB = -1; + const int nGPUSampleInterval = 10; // 每 10 轮（约 10 秒）才调用一次 nvidia-smi + + while (!bHit.load(std::memory_order_relaxed)) { nRound++; @@ -1510,9 +1580,10 @@ int deal::MonitorRun() CPUStat cpuStat; getSystemCPUStat(cpuStat); - long gpuUsedMB = -1; - long gpuTotalMB = -1; - getGPUMemInfo(gpuUsedMB, gpuTotalMB); + if ((nRound % nGPUSampleInterval) == 1) + { + getGPUMemInfo(gpuUsedMB, gpuTotalMB); + } auto wallNow = std::chrono::steady_clock::now(); @@ -1546,63 +1617,33 @@ int deal::MonitorRun() char buf[512]; snprintf(buf, sizeof(buf), - "[round %ld] %s | VmRSS: %ld MB | maxRSS: %ld MB | ProcCPU: %.1f%% | SysCPU: %.1f%% | Mem total %ld / free %ld / avail %ld MB | GPU: %ld/%ld MB", - nRound, ts, rssKB / 1024, usage.ru_maxrss / 1024, + "[round %ld] %s | infer=%ld fail=%ld | VmRSS: %ld MB | maxRSS: %ld MB | ProcCPU: %.1f%% | SysCPU: %.1f%% | Mem total %ld / free %ld / avail %ld MB | GPU: %ld/%ld MB", + nRound, ts, nInferCount.load(), nFailCount.load(), + rssKB / 1024, usage.ru_maxrss / 1024, procCpuUsage, sysCpuUsage, memTotalKB / 1024, memFreeKB / 1024, memAvailKB / 1024, gpuUsedMB, gpuTotalMB); - logLine(buf); - - // 2. 逐图推理，out 图重复覆盖保存；遇到非全黑则退出 - bool bHit = false; - for (size_t i = 0; i < inImgs.size(); i++) + // 打印降频：每 10 轮打印一次，减少日志 IO/系统调用对 CPU 的争抢 + if ((nRound % 10) == 1) { - cv::Mat outImg; - int re = pAI_Model->AIDet(inImgs[i], outImg); - if (re != 0 || outImg.empty()) - { - snprintf(buf, sizeof(buf), - "[round %ld] infer fail(%d) on image %zu: %s", - nRound, re, i, okInList[i].c_str()); - logLine(buf); - continue; - } - - // 输出图重复覆盖保存到 *_out.png - bool bSaved = false; - { - fs::path outParent = fs::path(outList[i]).parent_path(); - if (!outParent.empty()) - { - std::error_code ec; - fs::create_directories(outParent, ec); - } - bSaved = cv::imwrite(outList[i], outImg); - } - - int nNonZero = cv::countNonZero(outImg); - if (nNonZero > 0) - { - snprintf(buf, sizeof(buf), - "[round %ld] hit! out image %zu non-zero pixels: %d -> %s (saved=%d), exit monitor", - nRound, i, nNonZero, outList[i].c_str(), bSaved ? 1 : 0); - logLine(buf); - bHit = true; - break; - } + logLine(buf); } + } - if (bHit) + // 等待所有 worker 线程退出 + for (auto &th : workers) + { + if (th.joinable()) { - break; + th.join(); } - - snprintf(buf, sizeof(buf), "[round %ld] all out black, sleep %d s ...", nRound, nIntervalSec); - logLine(buf); - - std::this_thread::sleep_for(std::chrono::seconds(nIntervalSec)); } + long hitIdx = nHitIdx.load(); + logLine("===== monitor exit (hit image " + + (hitIdx >= 0 ? okInList[(size_t)hitIdx] : std::string("?")) + + ", non-zero pixels " + std::to_string(nHitNonZero.load()) + ") ====="); + logFile.close(); return 0; }