GrabBag/App/Workpiece/WorkpieceApp/Presenter/Src/WorkpiecePresenter.cpp

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#include "WorkpiecePresenter.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 <QImage>
#include <QThread>
#include <atomic>
#include <QJsonObject>
#include <QJsonArray>
#include "Version.h"
#include "VrTimeUtils.h"
#include "VrDateUtils.h"
#include "SG_baseDataType.h"
#include "VrConvert.h"
#include "TCPServerProtocol.h"
#include "DetectPresenter.h"
#include "PathManager.h"
WorkpiecePresenter::WorkpiecePresenter(QObject *parent)
: BasePresenter(parent)
, m_vrConfig(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
}
WorkpiecePresenter::~WorkpiecePresenter()
{
// 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
// 停止配置管理器
if (m_pConfigManager) {
m_pConfigManager->Shutdown();
m_pConfigManager.reset();
}
// 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;
}
// 释放配置对象
if (m_vrConfig) {
delete m_vrConfig;
m_vrConfig = nullptr;
}
}
int WorkpiecePresenter::InitApp()
{
LOG_DEBUG("Start APP Version: %s\n", WORKPIECE_FULL_VERSION_STRING);
// 初始化连接状态
SetWorkStatus(WorkStatus::InitIng);
m_pDetectPresenter = new DetectPresenter();
// 获取配置文件路径
QString configPath = PathManager::GetInstance().GetConfigFilePath();
int nRet = SUCCESS;
// 初始化配置管理器ConfigManager 内部会创建 IVrConfig 实例)
m_pConfigManager = std::make_unique<ConfigManager>();
if (!m_pConfigManager->Initialize(configPath.toStdString())) {
LOG_ERROR("Failed to initialize ConfigManager\n");
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("配置管理器初始化失败");
return ERR_CODE(DEV_OPEN_ERR);
}
LOG_INFO("ConfigManager initialized successfully\n");
// 从 ConfigManager 获取配置结果
ConfigResult configResult = m_pConfigManager->GetConfigResult();
// 获取 IVrConfig 实例用于配置改变通知
m_vrConfig = m_pConfigManager->GetVrConfigInstance();
// 设置配置改变通知回调
if (m_vrConfig) {
m_vrConfig->SetConfigChangeNotify(this);
}
// 调用基类InitCamera进行相机初始化bRGB=false, bSwing=true
InitCamera(configResult.cameraList, false, true);
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
nRet = InitTCPServer();
if (nRet != 0) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化失败");
m_bTCPConnected = false;
} else {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化成功");
}
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("设备初始化完成");
CheckAndUpdateWorkStatus();
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("配置初始化成功");
return SUCCESS;
}
// 初始化算法参数实现BasePresenter纯虚函数
int WorkpiecePresenter::InitAlgoParams()
{
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();
// 获取手眼标定文件路径并确保文件存在
QString clibPath = PathManager::GetInstance().GetCalibrationFilePath();
LOG_INFO("Loading hand-eye matrices from: %s\n", clibPath.toStdString().c_str());
// 读取存在的矩阵数量
int nExistMatrixNum = CVrConvert::GetClibMatrixCount(clibPath.toStdString().c_str());
LOG_INFO("Found %d hand-eye calibration matrices\n", nExistMatrixNum);
// 循环加载每个矩阵
for(int matrixIndex = 0; matrixIndex < nExistMatrixNum; matrixIndex++)
{
// 构造矩阵标识符
char matrixIdent[64];
#ifdef _WIN32
sprintf_s(matrixIdent, "CalibMatrixInfo_%d", matrixIndex);
#else
sprintf(matrixIdent, "CalibMatrixInfo_%d", matrixIndex);
#endif
// 创建新的标定矩阵结构
CalibMatrix calibMatrix;
// 初始化为单位矩阵
double initClibMatrix[16] = {
1.0, 0.0, 0.0, 0.0, // 第一行
0.0, 1.0, 0.0, 0.0, // 第二行
0.0, 0.0, 1.0, 0.0, // 第三行
0.0, 0.0, 0.0, 1.0 // 第四行
};
// 加载矩阵数据
bool loadSuccess = CVrConvert::LoadClibMatrix(clibPath.toStdString().c_str(), matrixIdent, "dCalibMatrix", calibMatrix.clibMatrix);
if(loadSuccess)
{
m_clibMatrixList.push_back(calibMatrix);
LOG_INFO("Successfully loaded matrix %d\n", matrixIndex);
// 输出矩阵内容
QString clibMatrixStr;
LOG_INFO("Matrix %d content:\n", matrixIndex);
for (int i = 0; i < 4; ++i) {
clibMatrixStr.clear();
for (int j = 0; j < 4; ++j) {
clibMatrixStr += QString::asprintf("%8.4f ", calibMatrix.clibMatrix[i * 4 + j]);
}
LOG_INFO(" %s\n", clibMatrixStr.toStdString().c_str());
}
}
else
{
LOG_WARNING("Failed to load matrix %d, using identity matrix\n", matrixIndex);
// 如果加载失败,使用单位矩阵
memcpy(calibMatrix.clibMatrix, initClibMatrix, sizeof(initClibMatrix));
m_clibMatrixList.push_back(calibMatrix);
}
}
LOG_INFO("Total loaded %zu hand-eye calibration matrices\n", m_clibMatrixList.size());
// 从 ConfigManager 获取已加载的配置(避免重复加载)
ConfigResult configResult = m_pConfigManager->GetConfigResult();
// 如果 ConfigManager 配置无效或 m_vrConfig 为空,尝试直接加载
if (configResult.cameraList.empty() && m_vrConfig) {
LOG_WARNING("ConfigResult from ConfigManager is empty, trying direct load\n");
QString configPath = PathManager::GetInstance().GetConfigFilePath();
LOG_INFO("Loading config: %s\n", configPath.toStdString().c_str());
int ret = m_vrConfig->LoadConfig(configPath.toStdString(), configResult);
if (ret != LOAD_CONFIG_SUCCESS) {
LOG_ERROR("Failed to load config file directly, error code: %d\n", ret);
}
}
const VrAlgorithmParams& xmlParams = configResult.algorithmParams;
// 保存调试参数
m_debugParam = configResult.debugParam;
LOG_INFO("Loaded XML params - Workpiece: lineLen=%.1f\n", xmlParams.workpieceParam.lineLen);
LOG_INFO("Loaded XML params - Filter: continuityTh=%.1f, outlierTh=%.1f\n", xmlParams.filterParam.continuityTh, xmlParams.filterParam.outlierTh);
// 直接使用配置结构
m_algorithmParams = xmlParams;
LOG_INFO("Algorithm parameters initialized successfully:\n");
LOG_INFO(" Workpiece: lineLen=%.1f\n",
m_algorithmParams.workpieceParam.lineLen);
// 循环打印所有相机的调平参数(添加安全检查)
LOG_INFO("Loading plane calibration parameters for all cameras:\n");
if (!m_algorithmParams.planeCalibParam.cameraCalibParams.empty()) {
for (const auto& cameraParam : m_algorithmParams.planeCalibParam.cameraCalibParams) {
try {
LOG_INFO("Camera %d (%s) calibration parameters:\n",
cameraParam.cameraIndex, cameraParam.cameraName.c_str());
LOG_INFO(" Is calibrated: %s\n", cameraParam.isCalibrated ? "YES" : "NO");
LOG_INFO(" Plane height: %.3f\n", cameraParam.planeHeight);
LOG_INFO(" Plane calibration matrix:\n");
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.planeCalib[0], cameraParam.planeCalib[1], cameraParam.planeCalib[2]);
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.planeCalib[3], cameraParam.planeCalib[4], cameraParam.planeCalib[5]);
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.planeCalib[6], cameraParam.planeCalib[7], cameraParam.planeCalib[8]);
LOG_INFO(" Inverse rotation matrix:\n");
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.invRMatrix[0], cameraParam.invRMatrix[1], cameraParam.invRMatrix[2]);
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.invRMatrix[3], cameraParam.invRMatrix[4], cameraParam.invRMatrix[5]);
LOG_INFO(" [%.3f, %.3f, %.3f]\n", cameraParam.invRMatrix[6], cameraParam.invRMatrix[7], cameraParam.invRMatrix[8]);
LOG_INFO(" --------------------------------\n");
} catch (const std::exception& e) {
LOG_ERROR("Exception while printing camera calibration parameters: %s\n", e.what());
} catch (...) {
LOG_ERROR("Unknown exception while printing camera calibration parameters\n");
}
}
} else {
LOG_WARNING("No plane calibration parameters found in configuration\n");
}
return SUCCESS;
}
// 手眼标定矩阵管理方法实现
CalibMatrix WorkpiecePresenter::GetClibMatrix(int index) const
{
CalibMatrix clibMatrix;
double initClibMatrix[16] = {
1.0, 0.0, 0.0, 0.0, // 第一行
0.0, 1.0, 0.0, 0.0, // 第二行
0.0, 0.0, 1.0, 0.0, // 第三行
0.0, 0.0, 0.0, 1.0 // 第四行
};
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;
}
void WorkpiecePresenter::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 WorkpiecePresenter::ProcessAlgoDetection(std::vector<std::pair<EVzResultDataType, SVzLaserLineData>>& detectionDataCache)
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{
LOG_INFO("[Algo Thread] Start real detection task using algorithm\n");
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// 1. 获取缓存的点云数据(已由基类验证非空)
unsigned int lineNum = detectionDataCache.size();
if(GetStatusCallback<IYWorkpieceStatus>()){
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("扫描线数:" + std::to_string(lineNum) + ",正在算法检测...");
}
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// 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 (GetStatusCallback<IYWorkpieceStatus>()) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("检测处理器未初始化");
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}
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);
DetectionResult detectionResult;
int nRet = m_pDetectPresenter->DetectWorkpiece(m_currentCameraIndex, detectionDataCache,
m_algorithmParams, m_debugParam, m_dataLoader,
currentClibMatrix.clibMatrix, detectionResult);
// 根据项目类型选择处理方式
if (GetStatusCallback<IYWorkpieceStatus>()) {
QString err = QString("错误:%1").arg(nRet);
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate(QString("检测%1").arg(SUCCESS == nRet ? "成功": err).toStdString());
}
LOG_INFO("[Algo Thread] sx_getWorkpiecePostion detected %zu objects time : %.2f ms\n", detectionResult.positions.size(), oTimeUtils.GetElapsedTimeInMilliSec());
ERR_CODE_RETURN(nRet);
// 8. 通知UI检测结果
detectionResult.cameraIndex = m_currentCameraIndex;
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) {
pStatus->OnDetectionResult(detectionResult);
}
// 更新状态
QString statusMsg = QString("检测完成,发现%1个目标").arg(detectionResult.positions.size());
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) 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 WorkpiecePresenter::OnConfigChanged(const ConfigResult& configResult)
{
LOG_INFO("Configuration changed notification received, reloading algorithm parameters\n");
// 更新调试参数
m_debugParam = configResult.debugParam;
// 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 (GetStatusCallback<IYWorkpieceStatus>()) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) 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 (GetStatusCallback<IYWorkpieceStatus>()) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("配置更新后算法参数重新加载失败");
}
}
}
// 根据相机索引获取调平参数
SSG_planeCalibPara WorkpiecePresenter::_GetCameraCalibParam(int cameraIndex)
{
// 查找指定相机索引的调平参数
SSG_planeCalibPara calibParam;
// 使用单位矩阵(未校准状态)
double identityMatrix[9] = {1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0};
for (int i = 0; i < 9; i++) {
calibParam.planeCalib[i] = identityMatrix[i];
calibParam.invRMatrix[i] = identityMatrix[i];
}
calibParam.planeHeight = -1.0; // 使用默认高度
for (const auto& cameraParam : m_algorithmParams.planeCalibParam.cameraCalibParams) {
if (cameraParam.cameraIndex == cameraIndex) {
// 根据isCalibrated标志决定使用标定矩阵还是单位矩阵
if (cameraParam.isCalibrated) {
// 使用实际的标定矩阵
for (int i = 0; i < 9; i++) {
calibParam.planeCalib[i] = cameraParam.planeCalib[i];
calibParam.invRMatrix[i] = cameraParam.invRMatrix[i];
}
calibParam.planeHeight = cameraParam.planeHeight;
}
}
}
return calibParam;
}
// 实现IConfigChangeListener接口
void WorkpiecePresenter::OnSystemConfigChanged(const SystemConfig& config)
{
LOG_INFO("System configuration changed, applying new configuration\n");
// 更新内部配置状态
if (m_vrConfig) {
// 可以选择性地重新初始化算法参数
InitAlgoParams();
}
if (GetStatusCallback<IYWorkpieceStatus>()) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("系统配置已更新");
}
}
void WorkpiecePresenter::OnCameraParamChanged(int cameraIndex, const CameraUIParam& cameraParam)
{
LOG_INFO("Camera %d parameters changed: expose=%.2f, gain=%.2f, frameRate=%.2f\n",
cameraIndex, cameraParam.exposeTime, cameraParam.gain, cameraParam.frameRate);
// 应用相机参数到实际设备
if (cameraIndex >= 1 && cameraIndex <= static_cast<int>(m_vrEyeDeviceList.size())) {
IVrEyeDevice* device = m_vrEyeDeviceList[cameraIndex - 1].second;
if (device) {
// 设置曝光时间
if (cameraParam.exposeTime > 0) {
unsigned int exposeTime = static_cast<unsigned int>(cameraParam.exposeTime);
int ret = device->SetEyeExpose(exposeTime);
if (ret == SUCCESS) {
LOG_INFO("Set expose time %.2f for camera %d successfully\n", cameraParam.exposeTime, cameraIndex);
} else {
LOG_ERROR("Failed to set expose time for camera %d, error: %d\n", cameraIndex, ret);
}
}
// 设置增益
if (cameraParam.gain > 0) {
unsigned int gain = static_cast<unsigned int>(cameraParam.gain);
int ret = device->SetEyeGain(gain);
if (ret == SUCCESS) {
LOG_INFO("Set gain %.2f for camera %d successfully\n", cameraParam.gain, cameraIndex);
} else {
LOG_ERROR("Failed to set gain for camera %d, error: %d\n", cameraIndex, ret);
}
}
// 设置帧率
if (cameraParam.frameRate > 0) {
int frameRate = static_cast<int>(cameraParam.frameRate);
int ret = device->SetFrame(frameRate);
if (ret == SUCCESS) {
LOG_INFO("Set frame rate %.2f for camera %d successfully\n", cameraParam.frameRate, cameraIndex);
} else {
LOG_ERROR("Failed to set frame rate for camera %d, error: %d\n", cameraIndex, ret);
}
}
// 设置摆动速度
if (cameraParam.swingSpeed > 0) {
float swingSpeed = static_cast<float>(cameraParam.swingSpeed);
int ret = device->SetSwingSpeed(swingSpeed);
if (ret == SUCCESS) {
LOG_INFO("Set swing speed %.2f for camera %d successfully\n", cameraParam.swingSpeed, cameraIndex);
} else {
LOG_ERROR("Failed to set swing speed for camera %d, error: %d\n", cameraIndex, ret);
}
}
// 设置摆动角度
if (cameraParam.swingStartAngle != cameraParam.swingStopAngle) {
float startAngle = static_cast<float>(cameraParam.swingStartAngle);
float stopAngle = static_cast<float>(cameraParam.swingStopAngle);
int ret = device->SetSwingAngle(startAngle, stopAngle);
if (ret == SUCCESS) {
LOG_INFO("Set swing angle %.2f-%.2f for camera %d successfully\n",
cameraParam.swingStartAngle, cameraParam.swingStopAngle, cameraIndex);
} else {
LOG_ERROR("Failed to set swing angle for camera %d, error: %d\n", cameraIndex, ret);
}
}
}
}
if (GetStatusCallback<IYWorkpieceStatus>()) {
QString cameraName = (cameraIndex >= 1 && cameraIndex <= static_cast<int>(m_vrEyeDeviceList.size())) ?
QString::fromStdString(m_vrEyeDeviceList[cameraIndex - 1].first) : QString("相机%1").arg(cameraIndex);
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate(QString("%1参数已更新").arg(cameraName).toStdString());
}
}
void WorkpiecePresenter::OnAlgorithmParamChanged(const VrAlgorithmParams& algorithmParams)
{
LOG_INFO("Algorithm parameters changed, updating internal configuration\n");
// 直接更新算法参数
m_algorithmParams = algorithmParams;
LOG_INFO("Updated algorithm parameters:\n");
LOG_INFO(" Workpiece: lineLen=%.1f\n",
m_algorithmParams.workpieceParam.lineLen);
LOG_INFO(" TreeGrow: yDeviation_max=%.1f, zDeviation_max=%.1f, maxLineSkipNum=%d\n",
m_algorithmParams.growParam.yDeviation_max, m_algorithmParams.growParam.zDeviation_max, m_algorithmParams.growParam.maxLineSkipNum);
LOG_INFO(" Corner: cornerTh=%.3f, jumpCornerTh_1=%.3f, jumpCornerTh_2=%.3f\n",
m_algorithmParams.cornerParam.cornerTh, m_algorithmParams.cornerParam.jumpCornerTh_1, m_algorithmParams.cornerParam.jumpCornerTh_2);
if (GetStatusCallback<IYWorkpieceStatus>()) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnStatusUpdate("算法参数已更新");
}
}
// 实现BasePresenter纯虚函数相机状态变化通知
void WorkpiecePresenter::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<IYWorkpieceStatus>()) {
if (cameraIndex == 1) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) pStatus->OnCamera1StatusChanged(isConnected);
} else if (cameraIndex == 2) {
if (auto pStatus = GetStatusCallback<IYWorkpieceStatus>()) 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<IYWorkpieceStatus>()) 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 WorkpiecePresenter::OnWorkStatusChanged(WorkStatus status)
{
auto pStatus = GetStatusCallback<IYWorkpieceStatus>();
if (pStatus) {
pStatus->OnWorkStatusChanged(status);
}
}
// 实现BasePresenter虚函数相机数量变化通知
void WorkpiecePresenter::OnCameraCountChanged(int count)
{
auto pStatus = GetStatusCallback<IYWorkpieceStatus>();
if (pStatus) {
pStatus->OnCameraCountChanged(count);
}
}
// 实现BasePresenter虚函数状态文字更新通知
void WorkpiecePresenter::OnStatusUpdate(const std::string& statusMessage)
{
auto pStatus = GetStatusCallback<IYWorkpieceStatus>();
if (pStatus) {
pStatus->OnStatusUpdate(statusMessage);
}
}