GrabBag/App/HolePitPosition/HolePitPositionApp/Presenter/Src/HolePitPositionPresenter.cpp

#include "HolePitPositionPresenter.h"
#include "VrError.h"
#include "VrLog.h"
#include <QtCore/QCoreApplication>
#include <QtCore/QFileInfo>
#include <QtCore/QDir>
#include <QtCore/QString>
#include <QtCore/QStandardPaths>
#include <QtCore/QFile>
#include <QtCore/QDateTime>
#include <cmath>
#include <algorithm>
#include <cstdio>
#include <QImage>
#include <QThread>
#include <atomic>

#include "Version.h"
#include "VrTimeUtils.h"
#include "VrDateUtils.h"
#include "VrConvert.h"
#include "TCPServerProtocol.h"
#include "DetectPresenter.h"
#include "PathManager.h"

// 配置变化监听器代理实现
void ConfigChangeListenerProxy::OnSystemConfigChanged(const SystemConfig& config)
{
    if (m_presenter) {
        LOG_INFO("ConfigChangeListenerProxy: config changed, reloading algorithm parameters\n");
        m_presenter->InitAlgoParams();
    }
}

HolePitPositionPresenter::HolePitPositionPresenter(QObject *parent)
    : BasePresenter(parent)
    , m_pConfigManager(nullptr)
    , m_pDetectPresenter(nullptr)
    , m_pTCPServer(nullptr)
    , m_bTCPConnected(false)
{
    // 基类已经创建了相机重连定时器和检测数据缓存
}

HolePitPositionPresenter::~HolePitPositionPresenter()
{
    // 基类会自动处理：相机重连定时器、算法检测线程、检测数据缓存、相机设备资源

    // 释放ConfigManager
    if (m_pConfigManager) {
        m_pConfigManager->Shutdown();
        delete m_pConfigManager;
        m_pConfigManager = nullptr;
    }

    // 释放TCP服务器
    if (m_pTCPServer) {
        m_pTCPServer->Deinitialize();
        delete m_pTCPServer;
        m_pTCPServer = nullptr;
    }

    // 释放检测处理器
    if (m_pDetectPresenter) {
        delete m_pDetectPresenter;
        m_pDetectPresenter = nullptr;
    }
}

int HolePitPositionPresenter::InitApp()
{
    LOG_DEBUG("Start APP Version: %s\n", HOLEPITPOSITION_FULL_VERSION_STRING);
    fprintf(stderr, "[DIAG] InitApp started, version: %s\n", HOLEPITPOSITION_FULL_VERSION_STRING);
    fflush(stderr);

    // 初始化连接状态
    SetWorkStatus(WorkStatus::InitIng);

    fprintf(stderr, "[DIAG] Creating DetectPresenter...\n"); fflush(stderr);
    m_pDetectPresenter = new DetectPresenter();
    fprintf(stderr, "[DIAG] DetectPresenter created OK\n"); fflush(stderr);

    int nRet = SUCCESS;

    // 创建 ConfigManager 实例
    fprintf(stderr, "[DIAG] Creating ConfigManager...\n"); fflush(stderr);
    m_pConfigManager = new ConfigManager();
    if (!m_pConfigManager) {
        LOG_ERROR("Failed to create ConfigManager instance\n");
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("配置管理器创建失败");
        return ERR_CODE(DEV_CONFIG_ERR);
    }
    fprintf(stderr, "[DIAG] ConfigManager created OK\n"); fflush(stderr);

    // 初始化 ConfigManager
    fprintf(stderr, "[DIAG] Initializing ConfigManager...\n"); fflush(stderr);
    if (!m_pConfigManager->Initialize()) {
        LOG_ERROR("Failed to initialize ConfigManager\n");
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("配置管理器初始化失败");
        return ERR_CODE(DEV_CONFIG_ERR);
    }
    fprintf(stderr, "[DIAG] ConfigManager initialized OK\n"); fflush(stderr);

    // 注册配置变化监听器
    m_pConfigListener = std::make_shared<ConfigChangeListenerProxy>(this);
    m_pConfigManager->AddConfigChangeListener(m_pConfigListener);

    LOG_INFO("Configuration loaded successfully\n");
    fprintf(stderr, "[DIAG] Configuration loaded OK\n"); fflush(stderr);

    // 获取配置结果
    ConfigResult configResult = m_pConfigManager->GetConfigResult();
    fprintf(stderr, "[DIAG] Camera count from config: %zu\n", configResult.cameraList.size()); fflush(stderr);

    // 调用基类InitCamera进行相机初始化（bRGB=false, bSwing=true）
    fprintf(stderr, "[DIAG] Calling InitCamera...\n"); fflush(stderr);
    InitCamera(configResult.cameraList, false, true);
    fprintf(stderr, "[DIAG] InitCamera completed OK\n"); fflush(stderr);

    LOG_INFO("Camera initialization completed. Connected cameras: %zu, default camera index: %d\n",
             m_vrEyeDeviceList.size(), m_currentCameraIndex);

    // 初始化TCP服务器
    fprintf(stderr, "[DIAG] Initializing TCP server...\n"); fflush(stderr);
    nRet = InitTCPServer();
    if (nRet != 0) {
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化失败");
        m_bTCPConnected = false;
    } else {
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化成功");
    }
    fprintf(stderr, "[DIAG] TCP server init result: %d\n", nRet); fflush(stderr);

    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("设备初始化完成");

    CheckAndUpdateWorkStatus();

    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate("配置初始化成功");

    fprintf(stderr, "[DIAG] InitApp completed successfully\n"); fflush(stderr);
    return SUCCESS;
}

// 初始化算法参数（实现BasePresenter纯虚函数）
int HolePitPositionPresenter::InitAlgoParams()
{
    fprintf(stderr, "[DIAG] InitAlgoParams started\n"); fflush(stderr);
    LOG_DEBUG("initializing algorithm parameters\n");
    QString exePath = QCoreApplication::applicationFilePath();

    // 清空现有的手眼标定矩阵列表
    m_clibMatrixList.clear();

    // 从 ConfigManager 获取配置结果（包含多相机手眼标定矩阵列表）
    ConfigResult configResult = m_pConfigManager->GetConfigResult();

    // 从 config.xml 加载所有相机的手眼标定矩阵
    for (size_t i = 0; i < configResult.handEyeCalibMatrixList.size(); i++) {
        CalibMatrix calibMatrix;
        memcpy(calibMatrix.clibMatrix, configResult.handEyeCalibMatrixList[i].matrix, sizeof(double) * 16);
        m_clibMatrixList.push_back(calibMatrix);

        LOG_INFO("Loaded hand-eye calibration matrix for camera %zu from config.xml:\n", i + 1);
        QString clibMatrixStr;
        for (int r = 0; r < 4; ++r) {
            clibMatrixStr.clear();
            for (int c = 0; c < 4; ++c) {
                clibMatrixStr += QString::asprintf("%8.4f ", calibMatrix.clibMatrix[r * 4 + c]);
            }
            LOG_INFO("  %s\n", clibMatrixStr.toStdString().c_str());
        }
    }

    // 如果没有配置任何矩阵，添加一个默认单位矩阵
    if (m_clibMatrixList.empty()) {
        CalibMatrix defaultMatrix;
        double initClibMatrix[16] = {
            1.0, 0.0, 0.0, 0.0,
            0.0, 1.0, 0.0, 0.0,
            0.0, 0.0, 1.0, 0.0,
            0.0, 0.0, 0.0, 1.0
        };
        memcpy(defaultMatrix.clibMatrix, initClibMatrix, sizeof(initClibMatrix));
        m_clibMatrixList.push_back(defaultMatrix);
        LOG_WARNING("No hand-eye calibration matrices found, using identity matrix\n");
    }

    LOG_INFO("Total loaded %zu hand-eye calibration matrices\n", m_clibMatrixList.size());

    const VrAlgorithmParams& xmlParams = configResult.algorithmParams;

    // 打印线段参数
    LOG_INFO("Loaded XML params - LineSeg: distScale=%.1f, segGapTh_y=%.1f, segGapTh_z=%.1f\n",
             xmlParams.lineSegParam.distScale,
             xmlParams.lineSegParam.segGapTh_y,
             xmlParams.lineSegParam.segGapTh_z);

    // 打印角点参数
    LOG_INFO("Loaded XML params - Corner: cornerTh=%.1f, scale=%.1f, minEndingGap=%.1f, minEndingGap_z=%.1f, jumpCornerTh_1=%.1f, jumpCornerTh_2=%.1f\n",
             xmlParams.cornerParam.cornerTh,
             xmlParams.cornerParam.scale,
             xmlParams.cornerParam.minEndingGap,
             xmlParams.cornerParam.minEndingGap_z,
             xmlParams.cornerParam.jumpCornerTh_1,
             xmlParams.cornerParam.jumpCornerTh_2);

    // 打印噪声滤除参数
    LOG_INFO("Loaded XML params - OutlierFilter: continuityTh=%.1f, outlierTh=%.1f\n",
             xmlParams.outlierFilterParam.continuityTh,
             xmlParams.outlierFilterParam.outlierTh);

    // 打印树生长参数
    LOG_INFO("Loaded XML params - TreeGrow: maxLineSkipNum=%d, yDeviation_max=%.1f, maxSkipDistance=%.1f, zDeviation_max=%.1f, minLTypeTreeLen=%.1f, minVTypeTreeLen=%.1f\n",
             xmlParams.treeGrowParam.maxLineSkipNum,
             xmlParams.treeGrowParam.yDeviation_max,
             xmlParams.treeGrowParam.maxSkipDistance,
             xmlParams.treeGrowParam.zDeviation_max,
             xmlParams.treeGrowParam.minLTypeTreeLen,
             xmlParams.treeGrowParam.minVTypeTreeLen);

    LOG_INFO("Algorithm parameters initialized successfully\n");

    fprintf(stderr, "[DIAG] InitAlgoParams completed OK\n"); fflush(stderr);
    return SUCCESS;
}

// 手眼标定矩阵管理方法实现
CalibMatrix HolePitPositionPresenter::GetClibMatrix(int index) const
{
    CalibMatrix clibMatrix;

    double initClibMatrix[16] = {
        1.0, 0.0, 0.0, 0.0,
        0.0, 1.0, 0.0, 0.0,
        0.0, 0.0, 1.0, 0.0,
        0.0, 0.0, 0.0, 1.0
    };
    memcpy(clibMatrix.clibMatrix, initClibMatrix, sizeof(initClibMatrix));

    if (index >= 0 && index < static_cast<int>(m_clibMatrixList.size())) {
        clibMatrix = m_clibMatrixList[index];
        memcpy(clibMatrix.clibMatrix, m_clibMatrixList[index].clibMatrix, sizeof(initClibMatrix));
    } else {
        LOG_WARNING("Invalid hand-eye calibration matrix\n");
    }

    return clibMatrix;
}

std::string HolePitPositionPresenter::GetAlgoVersion() const
{
    if (m_pDetectPresenter) {
        return m_pDetectPresenter->GetAlgoVersion();
    }
    return "unknown";
}


void HolePitPositionPresenter::CheckAndUpdateWorkStatus()
{
    if (m_bCameraConnected) {
        SetWorkStatus(WorkStatus::Ready);
    } else {
        SetWorkStatus(WorkStatus::Error);
    }
}

// 实现BasePresenter纯虚函数：执行算法检测
int HolePitPositionPresenter::ProcessAlgoDetection(std::vector<std::pair<EVzResultDataType, SVzLaserLineData>>& detectionDataCache)
{
    LOG_INFO("[Algo Thread] Start real detection task using algorithm\n");

    // 1. 获取缓存的点云数据（已由基类验证非空）
    unsigned int lineNum = detectionDataCache.size();
    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
        pStatus->OnStatusUpdate("扫描线数:" + std::to_string(lineNum) + "，正在算法检测...");
    }

    // 检查检测处理器是否已初始化
    if (!m_pDetectPresenter) {
        LOG_ERROR("DetectPresenter is null, cannot proceed with detection\n");
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
            pStatus->OnStatusUpdate("检测处理器未初始化");
        }
        return ERR_CODE(DEV_NOT_FIND);
    }

    CVrTimeUtils oTimeUtils;

    // 获取当前使用的手眼标定矩阵
    const CalibMatrix currentClibMatrix = GetClibMatrix(m_currentCameraIndex - 1);

    // 打印手眼标定矩阵
    LOG_INFO("[Algo Thread] Hand-Eye Calibration Matrix (Camera %d):\n", m_currentCameraIndex);
    LOG_INFO("  [%.4f, %.4f, %.4f, %.4f]\n", currentClibMatrix.clibMatrix[0], currentClibMatrix.clibMatrix[1], currentClibMatrix.clibMatrix[2], currentClibMatrix.clibMatrix[3]);
    LOG_INFO("  [%.4f, %.4f, %.4f, %.4f]\n", currentClibMatrix.clibMatrix[4], currentClibMatrix.clibMatrix[5], currentClibMatrix.clibMatrix[6], currentClibMatrix.clibMatrix[7]);
    LOG_INFO("  [%.4f, %.4f, %.4f, %.4f]\n", currentClibMatrix.clibMatrix[8], currentClibMatrix.clibMatrix[9], currentClibMatrix.clibMatrix[10], currentClibMatrix.clibMatrix[11]);
    LOG_INFO("  [%.4f, %.4f, %.4f, %.4f]\n", currentClibMatrix.clibMatrix[12], currentClibMatrix.clibMatrix[13], currentClibMatrix.clibMatrix[14], currentClibMatrix.clibMatrix[15]);

    // 从 ConfigManager 获取算法参数和调试参数
    VrAlgorithmParams algorithmParams = m_pConfigManager->GetAlgorithmParams();
    ConfigResult configResult = m_pConfigManager->GetConfigResult();
    VrDebugParam debugParam = configResult.debugParam;

    // 获取旋转顺序配置（从对应相机的标定矩阵中获取）
    int eulerOrder = 11;  // 默认外旋ZYX
    int calibIdx = m_currentCameraIndex - 1;
    if (calibIdx >= 0 && calibIdx < static_cast<int>(configResult.handEyeCalibMatrixList.size())) {
        eulerOrder = configResult.handEyeCalibMatrixList[calibIdx].eulerOrder;
    }
    LOG_INFO("[Algo Thread] Using euler order: %d (camera %d)\n", eulerOrder, m_currentCameraIndex);

    // 获取方向向量反向配置
    int dirVectorInvert = configResult.plcRobotServerConfig.dirVectorInvert;
    LOG_INFO("[Algo Thread] Using dir vector invert: %d\n", dirVectorInvert);

    HoleDetectionResult detectionResult;

    int nRet = m_pDetectPresenter->DetectHoles(m_currentCameraIndex, detectionDataCache,
                                algorithmParams, debugParam, m_dataLoader,
                                currentClibMatrix.clibMatrix, eulerOrder, dirVectorInvert,
                                m_currentRobotPose, detectionResult);

    // 根据项目类型选择处理方式
    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
        QString err = QString("错误:%1").arg(nRet);
        pStatus->OnStatusUpdate(QString("检测%1").arg(SUCCESS == nRet ? "成功": err).toStdString());
    }

    LOG_INFO("[Algo Thread] DetectHoles detected %zu holes (candidates=%d, filtered=%d) time : %.2f ms\n",
        detectionResult.positions.size(), detectionResult.totalCandidates, detectionResult.filteredCount,
        oTimeUtils.GetElapsedTimeInMilliSec());
    ERR_CODE_RETURN(nRet);

    // 8. 通知UI检测结果
    detectionResult.cameraIndex = m_currentCameraIndex;
    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
        pStatus->OnDetectionResult(detectionResult);
    }

    // 更新状态
    QString statusMsg = QString("检测完成，发现%1个孔").arg(detectionResult.positions.size());
    if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate(statusMsg.toStdString());

    // 发送检测结果给TCP客户端
    _SendDetectionResultToTCP(detectionResult, m_currentCameraIndex);

    // 9. 检测完成后，将工作状态更新为"完成"
    SetWorkStatus(WorkStatus::Completed);

    // 恢复到就绪状态
    SetWorkStatus(WorkStatus::Ready);

    return SUCCESS;
}


// 实现配置改变通知接口
void HolePitPositionPresenter::OnConfigChanged(const ConfigResult& configResult)
{
    LOG_INFO("Configuration changed notification received, reloading algorithm parameters\n");

    // 重新初始化算法参数
    int result = InitAlgoParams();
    if (result == SUCCESS) {
        LOG_INFO("Algorithm parameters reloaded successfully after config change\n");
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
            pStatus->OnStatusUpdate("配置已更新，算法参数重新加载成功");
        }
    } else {
        LOG_ERROR("Failed to reload algorithm parameters after config change, error: %d\n", result);
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) {
            pStatus->OnStatusUpdate("配置更新后算法参数重新加载失败");
        }
    }
}


// 实现BasePresenter纯虚函数：相机状态变化通知
void HolePitPositionPresenter::OnCameraStatusChanged(int cameraIndex, bool isConnected)
{
    LOG_INFO("Camera %d status changed: %s\n", cameraIndex, isConnected ? "connected" : "disconnected");

    // 通知UI更新相机状态
    if (GetStatusCallback<IYHolePitPositionStatus>()) {
        if (cameraIndex == 1) {
            if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnCamera1StatusChanged(isConnected);
        } else if (cameraIndex == 2) {
            if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnCamera2StatusChanged(isConnected);
        }

        // 获取相机名称用于状态消息
        QString cameraName;
        int arrayIndex = cameraIndex - 1;
        if (arrayIndex >= 0 && arrayIndex < static_cast<int>(m_vrEyeDeviceList.size())) {
            cameraName = QString::fromStdString(m_vrEyeDeviceList[arrayIndex].first);
        } else {
            cameraName = QString("相机%1").arg(cameraIndex);
        }

        QString statusMsg = QString("%1%2").arg(cameraName).arg(isConnected ? "已连接" : "已断开");
        if (auto pStatus = GetStatusCallback<IYHolePitPositionStatus>()) pStatus->OnStatusUpdate(statusMsg.toStdString());
    }

    // 检查并更新工作状态
    CheckAndUpdateWorkStatus();
}

// 实现BasePresenter虚函数：工作状态变化通知
void HolePitPositionPresenter::OnWorkStatusChanged(WorkStatus status)
{
    auto pStatus = GetStatusCallback<IYHolePitPositionStatus>();
    if (pStatus) {
        pStatus->OnWorkStatusChanged(status);
    }
}


// 实现BasePresenter虚函数：相机数量变化通知
void HolePitPositionPresenter::OnCameraCountChanged(int count)
{
    auto pStatus = GetStatusCallback<IYHolePitPositionStatus>();
    if (pStatus) {
        pStatus->OnCameraCountChanged(count);
    }
}

// 实现BasePresenter虚函数：状态文字更新通知
void HolePitPositionPresenter::OnStatusUpdate(const std::string& statusMessage)
{
    auto pStatus = GetStatusCallback<IYHolePitPositionStatus>();
    if (pStatus) {
        pStatus->OnStatusUpdate(statusMessage);
    }
}