feat 添加定时小图测试

example/MemMonitor.h

@@ -5,6 +5,7 @@
 #include <stdlib.h>
 #include <string.h>
 #include <unistd.h>
+#include <sys/time.h>
 #include <sys/resource.h>
 
 // 获取当前进程 RSS (物理内存) 使用量，单位 MB
@@ -47,4 +48,130 @@ static inline void printMemUsage(const char *tag, const char *extra)
         printf("[MEM] %-30s | VmRSS: %6ld MB | " fmt "\n", tag, _rss / 1024, ##__VA_ARGS__); \
     } while(0)
 
+// 获取 GPU 显存使用情况（通过 nvidia-smi），返回所有 GPU 累加的已用/总量，单位 MB
+// 成功返回 0，失败返回 -1（此时 usedMB/totalMB 置为 -1）
+static inline int getGPUMemInfo(long &usedMB, long &totalMB)
+{
+    usedMB = -1;
+    totalMB = -1;
+    FILE *fp = popen("nvidia-smi --query-gpu=memory.used,memory.total --format=csv,noheader,nounits 2>/dev/null", "r");
+    if (!fp)
+    {
+        return -1;
+    }
+    char line[256];
+    long used = 0;
+    long total = 0;
+    int n = 0;
+    while (fgets(line, sizeof(line), fp))
+    {
+        long u = 0;
+        long t = 0;
+        if (sscanf(line, "%ld, %ld", &u, &t) == 2)
+        {
+            used += u;
+            total += t;
+            n++;
+        }
+    }
+    pclose(fp);
+    if (n == 0)
+    {
+        return -1;
+    }
+    usedMB = used;
+    totalMB = total;
+    return 0;
+}
+
+// 获取系统内存信息（/proc/meminfo），单位 KB
+// 成功返回 0，失败返回 -1（此时各值置为 -1）
+static inline int getSystemMemInfo(long &totalKB, long &freeKB, long &availableKB)
+{
+    totalKB = -1;
+    freeKB = -1;
+    availableKB = -1;
+    FILE *fp = fopen("/proc/meminfo", "r");
+    if (!fp)
+    {
+        return -1;
+    }
+    char line[256];
+    while (fgets(line, sizeof(line), fp))
+    {
+        long val = -1;
+        if (sscanf(line, "MemTotal: %ld kB", &val) == 1)
+        {
+            totalKB = val;
+        }
+        else if (sscanf(line, "MemFree: %ld kB", &val) == 1)
+        {
+            freeKB = val;
+        }
+        else if (sscanf(line, "MemAvailable: %ld kB", &val) == 1)
+        {
+            availableKB = val;
+        }
+    }
+    fclose(fp);
+    return 0;
+}
+
+// 系统 CPU 时间快照（/proc/stat 第一行 cpu 累计值），用于两次采样计算 CPU 使用率
+struct CPUStat
+{
+    unsigned long long user;
+    unsigned long long nice;
+    unsigned long long system;
+    unsigned long long idle;
+    unsigned long long iowait;
+    unsigned long long irq;
+    unsigned long long softirq;
+    unsigned long long steal;
+
+    CPUStat()
+    {
+        user = nice = system = idle = iowait = irq = softirq = steal = 0;
+    }
+    unsigned long long total() const
+    {
+        return user + nice + system + idle + iowait + irq + softirq + steal;
+    }
+    unsigned long long idleTotal() const
+    {
+        return idle + iowait;
+    }
+};
+
+// 读取系统 CPU 时间快照，成功返回 0，失败返回 -1
+static inline int getSystemCPUStat(CPUStat &stat)
+{
+    FILE *fp = fopen("/proc/stat", "r");
+    if (!fp)
+    {
+        return -1;
+    }
+    char line[256];
+    int ret = -1;
+    if (fgets(line, sizeof(line), fp))
+    {
+        // 格式: cpu  user nice system idle iowait irq softirq steal guest guest_nice
+        if (sscanf(line, "cpu %llu %llu %llu %llu %llu %llu %llu %llu",
+                   &stat.user, &stat.nice, &stat.system, &stat.idle,
+                   &stat.iowait, &stat.irq, &stat.softirq, &stat.steal) >= 4)
+        {
+            ret = 0;
+        }
+    }
+    fclose(fp);
+    return ret;
+}
+
+// 进程累计消耗的 CPU 时间（用户态 + 内核态），单位秒
+static inline double cpuTimeSec(const struct rusage &usage)
+{
+    return (double)usage.ru_utime.tv_sec + (double)usage.ru_utime.tv_usec / 1e6 +
+           (double)usage.ru_stime.tv_sec + (double)usage.ru_stime.tv_usec / 1e6;
+}
+
 #endif // _MEM_MONITOR_H_

example/deal.cpp

@@ -3,6 +3,7 @@
 #include <sys/time.h>
 #include <sys/types.h>
 #include <sys/stat.h>
+#include <ctime>
 #include "MemMonitor.h"
 #include <unistd.h>
 #include <string>
@@ -1326,13 +1327,320 @@ int deal::DetImg()
     return 0;
 }
 
+/// @brief 监控模式：每 5 分钟执行一次模型推理，并把当前设备资源消耗（CPU 内存 / GPU 显存）
+///        写入 monitor.log；当某次推理输出 out 图至少一个像素不为全黑时，保存该 out 图并退出监控。
+/// @return 0 表示成功，非 0 表示初始化失败
+int deal::MonitorRun()
+{
+    // 输入目录：优先使用命令行指定路径，否则使用默认路径
+    std::string strSrcRoot = runConfig.filePath;
+    if (strSrcRoot.empty())
+    {
+        strSrcRoot = "/home/aidlux/BOE/FOG/AI_Detect/";
+    }
+    else if (strSrcRoot.back() != '/')
+    {
+        strSrcRoot += "/";
+    }
+
+    std::shared_ptr<AIFactory> pAIFactory = AIFactory::GetInstance();
+    std::shared_ptr<AIModel_Base> pAI_Model = pAIFactory->AI_defect_NF;
+    if (!pAI_Model || !pAI_Model->m_bInitSuccess)
+    {
+        printf("MonitorRun: AI model (AI_defect_NF) not ready!\n");
+        return 1;
+    }
+
+    const int nModelInCh = pAI_Model->input_0.channel;
+    const int nModelInW = pAI_Model->input_0.width;
+    const int nModelInH = pAI_Model->input_0.height;
+
+    printf("MonitorRun: model input [c=%d w=%d h=%d] output [c=%d w=%d h=%d]\n",
+           nModelInCh, nModelInW, nModelInH,
+           pAI_Model->output_0.channel, pAI_Model->output_0.width, pAI_Model->output_0.height);
+
+    // 收集所有 *_in.png 文件
+    std::vector<std::string> inList;
+    try
+    {
+        if (!fs::exists(strSrcRoot))
+        {
+            printf("MonitorRun: src dir not exist: %s\n", strSrcRoot.c_str());
+            return 1;
+        }
+        for (const auto &entry : fs::recursive_directory_iterator(strSrcRoot))
+        {
+            if (!entry.is_regular_file())
+            {
+                continue;
+            }
+            std::string name = entry.path().filename().string();
+            const std::string suffix = "_in.png";
+            if (name.size() >= suffix.size() &&
+                name.compare(name.size() - suffix.size(), suffix.size(), suffix) == 0)
+            {
+                inList.push_back(entry.path().string());
+            }
+        }
+    }
+    catch (const std::exception &e)
+    {
+        printf("MonitorRun: traverse error %s\n", e.what());
+        return 1;
+    }
+
+    std::sort(inList.begin(), inList.end());
+    printf("MonitorRun: total %zu in images\n", inList.size());
+    if (inList.empty())
+    {
+        printf("MonitorRun: no *_in.png found\n");
+        return 1;
+    }
+
+    // 预处理成模型输入（只读一次，每轮复用）
+    std::vector<cv::Mat> inImgs;
+    inImgs.reserve(inList.size());
+    for (size_t i = 0; i < inList.size(); i++)
+    {
+        cv::Mat inImg = cv::imread(inList[i], cv::IMREAD_UNCHANGED);
+        if (inImg.empty())
+        {
+            printf("MonitorRun: read fail: %s\n", inList[i].c_str());
+            continue;
+        }
+        if (inImg.channels() != nModelInCh)
+        {
+            cv::Mat tmp;
+            if (inImg.channels() >= 3)
+            {
+                cv::cvtColor(inImg, tmp, cv::COLOR_BGR2GRAY);
+            }
+            else
+            {
+                tmp = inImg.clone();
+            }
+            inImg = tmp;
+        }
+        if (inImg.type() != CV_8U)
+        {
+            inImg.convertTo(inImg, CV_8U);
+        }
+        if (inImg.cols != nModelInW || inImg.rows != nModelInH)
+        {
+            cv::resize(inImg, inImg, cv::Size(nModelInW, nModelInH));
+        }
+        inImgs.push_back(inImg);
+    }
+    if (inImgs.empty())
+    {
+        printf("MonitorRun: no valid in image\n");
+        return 1;
+    }
+
+    // 输出目录：输入目录去掉末尾 '/' 后追加 "_TEST/"（与 TestAIDet 保持一致）
+    std::string strDstRoot = strSrcRoot;
+    while (strDstRoot.size() > 1 && strDstRoot.back() == '/')
+    {
+        strDstRoot.pop_back();
+    }
+    strDstRoot += "_TEST/";
+
+    // 本次监控的时间戳输出目录（存图和 log 都放这里）
+    time_t startT = time(NULL);
+    struct tm stmv;
+    localtime_r(&startT, &stmv);
+    char dirTs[64] = {0};
+    strftime(dirTs, sizeof(dirTs), "monitor_%Y%m%d_%H%M%S", &stmv);
+    std::string strOutDir = strDstRoot + dirTs + "/";
+    {
+        std::error_code ec;
+        fs::create_directories(strOutDir, ec);
+    }
+
+    // 打开监控日志（追加写）
+    std::string strLogPath = strOutDir + "monitor.log";
+    std::ofstream logFile(strLogPath, std::ios::app);
+    if (!logFile)
+    {
+        printf("MonitorRun: open log fail: %s\n", strLogPath.c_str());
+        return 1;
+    }
+
+    // 同时输出到终端和 log 文件
+    auto logLine = [&logFile](const std::string &line)
+    {
+        printf("%s\n", line.c_str());
+        logFile << line << std::endl;
+        logFile.flush();
+    };
+
+    const int nIntervalSec = 5 * 60; // 5 分钟
+    const int nMaxRunSec = 30 * 60;  // 30 分钟
+    long nRound = 0;
+    auto monitorStart = std::chrono::steady_clock::now();
+    logLine("===== monitor start (run max 30 min) =====");
+
+    // 初始化 CPU 采样基准（用于计算 CPU 使用率）
+    struct rusage usagePrev;
+    getrusage(RUSAGE_SELF, &usagePrev);
+    CPUStat cpuStatPrev;
+    getSystemCPUStat(cpuStatPrev);
+    auto wallPrev = std::chrono::steady_clock::now();
+
+    while (true)
+    {
+        // 0. 运行 30 分钟后停止
+        double elapsedSec = std::chrono::duration<double>(
+                                std::chrono::steady_clock::now() - monitorStart)
+                                .count();
+        if (elapsedSec >= nMaxRunSec)
+        {
+            logLine("===== monitor exit (timeout 30 min) =====");
+            break;
+        }
+
+        nRound++;
+
+        // 1. 采集设备资源消耗
+        long rssKB = getRSS_KB();
+        struct rusage usage;
+        getrusage(RUSAGE_SELF, &usage);
+
+        long memTotalKB = -1;
+        long memFreeKB = -1;
+        long memAvailKB = -1;
+        getSystemMemInfo(memTotalKB, memFreeKB, memAvailKB);
+
+        CPUStat cpuStat;
+        getSystemCPUStat(cpuStat);
+
+        long gpuUsedMB = -1;
+        long gpuTotalMB = -1;
+        getGPUMemInfo(gpuUsedMB, gpuTotalMB);
+
+        auto wallNow = std::chrono::steady_clock::now();
+
+        // 系统 CPU 使用率（两次采样之间）
+        double sysCpuUsage = -1.0;
+        unsigned long long totalDelta = cpuStat.total() - cpuStatPrev.total();
+        unsigned long long idleDelta = cpuStat.idleTotal() - cpuStatPrev.idleTotal();
+        if (totalDelta > 0)
+        {
+            sysCpuUsage = 100.0 * (1.0 - (double)idleDelta / (double)totalDelta);
+        }
+
+        // 进程 CPU 使用率（getrusage 的 CPU 时间 / 墙钟时间，多核下可能超过 100%）
+        double procCpuUsage = -1.0;
+        double wallSec = std::chrono::duration<double>(wallNow - wallPrev).count();
+        if (wallSec > 0)
+        {
+            procCpuUsage = 100.0 * (cpuTimeSec(usage) - cpuTimeSec(usagePrev)) / wallSec;
+        }
+
+        // 更新采样基准
+        usagePrev = usage;
+        cpuStatPrev = cpuStat;
+        wallPrev = wallNow;
+
+        time_t now = time(NULL);
+        struct tm tmv;
+        localtime_r(&now, &tmv);
+        char ts[64] = {0};
+        strftime(ts, sizeof(ts), "%Y-%m-%d %H:%M:%S", &tmv);
+
+        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,
+                 procCpuUsage, sysCpuUsage,
+                 memTotalKB / 1024, memFreeKB / 1024, memAvailKB / 1024,
+                 gpuUsedMB, gpuTotalMB);
+        logLine(buf);
+
+        // 2. 逐图推理，遇到 out 非全黑则保存对应的输入图和输出图
+        int nHit = 0;
+        for (size_t i = 0; i < inImgs.size(); i++)
+        {
+            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, inList[i].c_str());
+                logLine(buf);
+                continue;
+            }
+
+            int nNonZero = cv::countNonZero(outImg);
+            if (nNonZero > 0)
+            {
+                // 输出图不全黑 -> 保存对应的输入图和输出图
+                std::string saveInPath = strOutDir + "monitor_hit_round" +
+                                         std::to_string(nRound) + "_img" +
+                                         std::to_string(i) + "_in.png";
+                std::string saveOutPath = strOutDir + "monitor_hit_round" +
+                                          std::to_string(nRound) + "_img" +
+                                          std::to_string(i) + "_out.png";
+                cv::imwrite(saveInPath, inImgs[i]);
+                cv::imwrite(saveOutPath, outImg);
+
+                snprintf(buf, sizeof(buf),
+                         "[round %ld] hit! out image %zu non-zero pixels: %d -> save %s / %s",
+                         nRound, i, nNonZero, saveInPath.c_str(), saveOutPath.c_str());
+                logLine(buf);
+                nHit++;
+            }
+        }
+
+        snprintf(buf, sizeof(buf), "[round %ld] %d non-black out saved, sleep %d s ...",
+                 nRound, nHit, nIntervalSec);
+        logLine(buf);
+
+        // 3. 休眠（不超过剩余运行时间）
+        double remainSec = nMaxRunSec - elapsedSec;
+        int sleepSec = (int)(remainSec < nIntervalSec ? remainSec : nIntervalSec);
+        if (sleepSec > 0)
+        {
+            std::this_thread::sleep_for(std::chrono::seconds(sleepSec));
+        }
+    }
+
+    logFile.close();
+    return 0;
+}
+
 /// @brief AI 检测独立测试：遍历 /home/aidlux/BOE/FOG/AI_Detect/ 下所有 *_in.png，
 ///        送入 AI_defect_NF 模型推理，将输出 *_out.png 保存到 /home/aidlux/BOE/FOG/AI_Detect_TEST/
 /// @return 0 表示成功
 int deal::TestAIDet()
 {
-    std::string strSrcRoot = "/home/aidlux/BOE/FOG/AI_Detect/";
+    // 输入目录：优先使用命令行指定路径，否则使用默认路径
-    std::string strDstRoot = "/home/aidlux/BOE/FOG/AI_Detect_TEST/";
+    std::string strSrcRoot = runConfig.filePath;
+    if (strSrcRoot.empty())
+    {
+        strSrcRoot = "/home/aidlux/BOE/FOG/AI_Detect/";
+    }
+    else if (strSrcRoot.back() != '/')
+    {
+        strSrcRoot += "/";
+    }
+
+    // 输出目录：输入目录去掉末尾 '/' 后追加 "_TEST/"
+    // 默认输入 /home/aidlux/BOE/FOG/AI_Detect/ -> 输出 /home/aidlux/BOE/FOG/AI_Detect_TEST/
+    std::string strDstRoot = strSrcRoot;
+    while (strDstRoot.size() > 1 && strDstRoot.back() == '/')
+    {
+        strDstRoot.pop_back();
+    }
+    strDstRoot += "_TEST/";
+
+    if(runConfig.bmonitor)
+    {
+        // 监控模式：每 5 分钟执行一次模型推理，记录设备资源消耗到 log；
+        // 当某次推理输出 out 图至少一个像素不为全黑时退出监控。
+        return MonitorRun();
+    }
 
     std::shared_ptr<AIFactory> pAIFactory = AIFactory::GetInstance();
     std::shared_ptr<AIModel_Base> pAI_Model = pAIFactory->AI_defect_NF;

example/deal.h

@@ -548,6 +548,7 @@ struct DealRunConfig
 	std::string filePath = "";						// 处理文件路径 如果为空 处理当前的单张图片
 	bool det_Tag = false;							// 是否检测标签
 	bool bDebugSaveImg = false;						// 是否中间图片图片
+	bool bmonitor = false;							// 是否监控
 	int m_nTestNum = 999999;
 	void print(std::string str)
 	{
@@ -635,6 +636,7 @@ private:
 	int ReJson_ALL();
 	int DetImg();																					 // 套图复测
 	int TestAIDet(); // AI 检测独立测试：读取 in 图送入模型，保存 out 图
+	int MonitorRun();																 // 监控模式：每 5 分钟推理一次，记录资源消耗，遇非全黑 out 退出
 	int ReJson_product(std::vector<Json_Det_Path> &jsonList, std::string strProductName);			 // 套图复测
 	int CheckFileImg();																				 ///< 检查文件图片（新增）
 	int CheckProduct(const LoadProductImages &product);												 ///< 检查单个产品（新增）

example/test_example.cpp

@@ -191,6 +191,10 @@ int main(int argc, char *argv[])
 			else if (string(argv[i]) == "-testAIDet")
 			{
 				test.runConfig.det_Type = RUNTYPE_RUN_File_AI_DetTest;
+				if (argc == 3)
+				{
+					test.runConfig.filePath = string(argv[i + 1]);
+				}
 			}
 			else if (string(argv[i]) == "-feqx" && i + 1 < argc)
 			{
@@ -242,6 +246,10 @@ int main(int argc, char *argv[])
 			{
 				test.runConfig.bDebugSaveImg = true;
 			}
+			if (string(argv[i]) == "-m")
+			{
+				test.runConfig.bmonitor = true;
+			}
 			if (string(argv[i]) == "-n" && i + 1 < argc)
 			{
 				std::string strnum = string(argv[i + 1]);