698 lines
25 KiB
C++
Raw Normal View History

#include "BagThreadPositionPresenter.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"
#include "IGlLineLaserDevice.h" // GlLineLaserDevice接口
BagThreadPositionPresenter::BagThreadPositionPresenter(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
}
BagThreadPositionPresenter::~BagThreadPositionPresenter()
{
// 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析构函数会自动调用Shutdown
if (m_pConfigManager) {
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 BagThreadPositionPresenter::InitApp()
{
LOG_DEBUG("Start APP Version: %s\n", BAGTHREADPOSITION_FULL_VERSION_STRING);
// 初始化连接状态
SetWorkStatus(WorkStatus::InitIng);
m_pDetectPresenter = new DetectPresenter();
int nRet = SUCCESS;
// 创建 ConfigManager 实例
m_pConfigManager = new ConfigManager();
if (!m_pConfigManager) {
LOG_ERROR("Failed to create ConfigManager instance\n");
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate("配置管理器创建失败");
return ERR_CODE(DEV_CONFIG_ERR);
}
// 初始化 ConfigManager
if (!m_pConfigManager->Initialize()) {
LOG_ERROR("Failed to initialize ConfigManager\n");
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate("配置管理器初始化失败");
return ERR_CODE(DEV_CONFIG_ERR);
}
LOG_INFO("Configuration loaded successfully\n");
// 获取配置结果
ConfigResult configResult = m_pConfigManager->GetConfigResult();
// 调用基类InitCamera进行相机初始化bRGB=false, bSwing=false
// 注意BagThreadPosition使用GlLineLaserDevice通过重写CreateDevice实现
InitCamera(configResult.cameraList, false, false);
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<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化失败");
m_bTCPConnected = false;
} else {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate("TCP服务器初始化成功");
}
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate("设备初始化完成");
CheckAndUpdateWorkStatus();
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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 BagThreadPositionPresenter::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 获取配置结果
ConfigResult configResult = m_pConfigManager->GetConfigResult();
const VrAlgorithmParams& xmlParams = configResult.algorithmParams;
LOG_INFO("Loaded XML params - Thread: isHorizonScan=%s\n",
xmlParams.threadParam.isHorizonScan ? "true" : "false");
LOG_INFO("Loaded XML params - Filter: continuityTh=%.1f, outlierTh=%.1f\n",
xmlParams.filterParam.continuityTh, xmlParams.filterParam.outlierTh);
LOG_INFO("Algorithm parameters initialized successfully\n");
return SUCCESS;
}
// 手眼标定矩阵管理方法实现
CalibMatrix BagThreadPositionPresenter::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 BagThreadPositionPresenter::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 BagThreadPositionPresenter::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(GetStatusCallback<IYBagThreadPositionStatus>()){
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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 (GetStatusCallback<IYBagThreadPositionStatus>()) {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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);
// 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;
DetectionResult detectionResult;
int nRet = m_pDetectPresenter->DetectScrew(m_currentCameraIndex, detectionDataCache,
algorithmParams, debugParam, m_dataLoader,
currentClibMatrix.clibMatrix, detectionResult);
// 根据项目类型选择处理方式
if (GetStatusCallback<IYBagThreadPositionStatus>()) {
QString err = QString("错误:%1").arg(nRet);
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnStatusUpdate(QString("检测%1").arg(SUCCESS == nRet ? "成功": err).toStdString());
}
LOG_INFO("[Algo Thread] sx_bagThreadMeasure 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<IYBagThreadPositionStatus>()) {
pStatus->OnDetectionResult(detectionResult);
}
// 更新状态
QString statusMsg = QString("检测完成,发现%1条拆线").arg(detectionResult.positions.size() / 2);
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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 BagThreadPositionPresenter::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 (GetStatusCallback<IYBagThreadPositionStatus>()) {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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<IYBagThreadPositionStatus>()) {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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 BagThreadPositionPresenter::_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
// 从 ConfigManager 获取算法参数
VrAlgorithmParams algorithmParams = m_pConfigManager->GetAlgorithmParams();
for (const auto& cameraParam : 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BasePresenter纯虚函数相机状态变化通知
void BagThreadPositionPresenter::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<IYBagThreadPositionStatus>()) {
if (cameraIndex == 1) {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) pStatus->OnCamera1StatusChanged(isConnected);
} else if (cameraIndex == 2) {
if (auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>()) 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<IYBagThreadPositionStatus>()) 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 BagThreadPositionPresenter::OnWorkStatusChanged(WorkStatus status)
{
auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>();
if (pStatus) {
pStatus->OnWorkStatusChanged(status);
}
}
// 实现BasePresenter虚函数相机数量变化通知
void BagThreadPositionPresenter::OnCameraCountChanged(int count)
{
auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>();
if (pStatus) {
pStatus->OnCameraCountChanged(count);
}
}
// 实现BasePresenter虚函数状态文字更新通知
void BagThreadPositionPresenter::OnStatusUpdate(const std::string& statusMessage)
{
auto pStatus = GetStatusCallback<IYBagThreadPositionStatus>();
if (pStatus) {
pStatus->OnStatusUpdate(statusMessage);
}
}
// ============ 实现 ICameraLevelCalculator 接口 ============
bool BagThreadPositionPresenter::CalculatePlaneCalibration(
const std::vector<std::pair<EVzResultDataType, SVzLaserLineData>>& scanData,
double planeCalib[9],
double& planeHeight,
double invRMatrix[9])
{
try {
// 检查是否有足够的扫描数据
if (scanData.empty()) {
LOG_ERROR("No scan data available for plane calibration\n");
return false;
}
LOG_INFO("Calculating plane calibration from %zu scan lines\n", scanData.size());
// 转换为算法需要的XYZ格式
LaserDataLoader dataLoader;
std::vector<std::vector<SVzNL3DPosition>> xyzData;
int convertResult = dataLoader.ConvertToSVzNL3DPosition(scanData, xyzData);
if (convertResult != SUCCESS || xyzData.empty()) {
LOG_WARNING("Failed to convert data to XYZ format or no XYZ data available\n");
return false;
}
// 拆线定位项目暂时使用简单的平面拟合
// 使用默认的单位矩阵
double identity[9] = {1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0};
memcpy(planeCalib, identity, sizeof(double) * 9);
memcpy(invRMatrix, identity, sizeof(double) * 9);
planeHeight = -1.0;
LOG_INFO("Plane calibration calculated successfully: height=%.3f\n", planeHeight);
return true;
} catch (const std::exception& e) {
LOG_ERROR("Exception in CalculatePlaneCalibration: %s\n", e.what());
return false;
} catch (...) {
LOG_ERROR("Unknown exception in CalculatePlaneCalibration\n");
return false;
}
}
// ============ 实现 ICameraLevelResultSaver 接口 ============
bool BagThreadPositionPresenter::SaveLevelingResults(double planeCalib[9], double planeHeight, double invRMatrix[9],
int cameraIndex, const QString& cameraName)
{
try {
if (!m_pConfigManager) {
LOG_ERROR("ConfigManager is null, cannot save leveling results\n");
return false;
}
// 验证传入的相机参数
if (cameraIndex <= 0) {
LOG_ERROR("Invalid camera index: %d\n", cameraIndex);
return false;
}
if (cameraName.isEmpty()) {
LOG_ERROR("Camera name is empty\n");
return false;
}
// 获取当前配置
QString configPath = PathManager::GetInstance().GetConfigFilePath();
LOG_INFO("Config path: %s\n", configPath.toUtf8().constData());
SystemConfig systemConfig = m_pConfigManager->GetConfig();
// 创建或更新指定相机的调平参数
VrCameraPlaneCalibParam cameraParam;
cameraParam.cameraIndex = cameraIndex;
cameraParam.cameraName = cameraName.toStdString();
cameraParam.planeHeight = planeHeight;
cameraParam.isCalibrated = true;
// 复制校准矩阵
for (int i = 0; i < 9; i++) {
cameraParam.planeCalib[i] = planeCalib[i];
cameraParam.invRMatrix[i] = invRMatrix[i];
}
// 更新配置中的相机校准参数
systemConfig.configResult.algorithmParams.planeCalibParam.SetCameraCalibParam(cameraParam);
// 更新并保存配置
if (!m_pConfigManager->UpdateFullConfig(systemConfig)) {
LOG_ERROR("Failed to update config with leveling results\n");
return false;
}
if (!m_pConfigManager->SaveConfigToFile(configPath.toStdString())) {
LOG_ERROR("Failed to save config file with leveling results\n");
return false;
}
LOG_INFO("Leveling results saved successfully for camera %d (%s)\n", cameraIndex, cameraName.toUtf8().constData());
LOG_INFO("Plane height: %.3f\n", planeHeight);
LOG_INFO("Calibration marked as completed\n");
return true;
} catch (const std::exception& e) {
LOG_ERROR("Exception in SaveLevelingResults: %s\n", e.what());
return false;
}
}
bool BagThreadPositionPresenter::LoadLevelingResults(int cameraIndex, const QString& cameraName,
double planeCalib[9], double& planeHeight, double invRMatrix[9])
{
try {
if (!m_pConfigManager) {
LOG_ERROR("ConfigManager is null, cannot load calibration data\n");
return false;
}
// 从ConfigManager获取配置结果
ConfigResult configResult = m_pConfigManager->GetConfigResult();
// 获取指定相机的标定参数
VrCameraPlaneCalibParam cameraParamValue;
if (!configResult.algorithmParams.planeCalibParam.GetCameraCalibParam(cameraIndex, cameraParamValue) || !cameraParamValue.isCalibrated) {
LOG_INFO("No calibration data found for camera %d (%s)\n", cameraIndex, cameraName.toUtf8().constData());
return false;
}
// 复制标定数据
for (int i = 0; i < 9; i++) {
planeCalib[i] = cameraParamValue.planeCalib[i];
invRMatrix[i] = cameraParamValue.invRMatrix[i];
}
planeHeight = cameraParamValue.planeHeight;
LOG_INFO("Calibration data loaded successfully for camera %d (%s)\n", cameraIndex, cameraName.toUtf8().constData());
LOG_INFO("Plane height: %.3f\n", planeHeight);
return true;
} catch (const std::exception& e) {
LOG_ERROR("Exception in LoadLevelingResults: %s\n", e.what());
return false;
}
}
// 反初始化
void BagThreadPositionPresenter::DeinitApp()
{
LOG_DEBUG("Deinitializing BagThreadPositionPresenter\n");
// 停止检测
StopDetection();
// 释放TCP服务器
if (m_pTCPServer) {
m_pTCPServer->Deinitialize();
delete m_pTCPServer;
m_pTCPServer = nullptr;
}
// 释放ConfigManager析构函数会自动调用Shutdown
if (m_pConfigManager) {
delete m_pConfigManager;
m_pConfigManager = nullptr;
}
// 释放检测处理器
if (m_pDetectPresenter) {
delete m_pDetectPresenter;
m_pDetectPresenter = nullptr;
}
LOG_DEBUG("BagThreadPositionPresenter deinitialized\n");
}
// 触发检测
bool BagThreadPositionPresenter::TriggerDetection(int cameraIndex)
{
// 设置相机索引
if (cameraIndex > 0) {
SetDefaultCameraIndex(cameraIndex);
}
// 检查是否已连接相机
if (!m_bCameraConnected) {
LOG_WARNING("Camera not connected, cannot trigger detection\n");
return false;
}
// 触发检测
int ret = StartDetection(cameraIndex, false);
if (ret != SUCCESS) {
LOG_ERROR("Failed to trigger detection, error: %d\n", ret);
return false;
}
return true;
}
// 加载文件并检测
int BagThreadPositionPresenter::LoadAndDetect(const QString& fileName)
{
LOG_INFO("Loading data from file: %s\n", fileName.toStdString().c_str());
// 使用基类的方法加载调试数据并执行检测
return LoadDebugDataAndDetect(fileName.toStdString());
}
// 重连相机
void BagThreadPositionPresenter::ReconnectCamera()
{
LOG_INFO("Attempting to reconnect cameras\n");
TryReconnectCameras();
}
// 获取算法参数
BagThreadPositionPresenter::AlgoParams BagThreadPositionPresenter::GetAlgoParams() const
{
AlgoParams params;
if (m_pConfigManager) {
VrAlgorithmParams algorithmParams = m_pConfigManager->GetAlgorithmParams();
params.threadParam = algorithmParams.threadParam;
params.cornerParam = algorithmParams.cornerParam;
params.filterParam = algorithmParams.filterParam;
params.growParam = algorithmParams.growParam;
} else {
// 使用默认参数
params.threadParam.isHorizonScan = true;
}
return params;
}
// 设置算法参数
void BagThreadPositionPresenter::SetAlgoParams(const AlgoParams& params)
{
if (!m_pConfigManager) {
LOG_WARNING("ConfigManager not initialized, cannot set algorithm params\n");
return;
}
// 获取当前配置
VrAlgorithmParams algorithmParams = m_pConfigManager->GetAlgorithmParams();
// 更新参数
algorithmParams.threadParam = params.threadParam;
algorithmParams.cornerParam = params.cornerParam;
algorithmParams.filterParam = params.filterParam;
algorithmParams.growParam = params.growParam;
// 更新到ConfigManager
m_pConfigManager->UpdateAlgorithmParams(algorithmParams);
LOG_INFO("Algorithm parameters updated\n");
}
// 重写BasePresenter虚函数创建设备对象
// BagThreadPosition项目使用GlLineLaserDevice
int BagThreadPositionPresenter::CreateDevice(IVrEyeDevice** ppDevice)
{
if (!ppDevice) {
return ERR_CODE(DEV_ARG_INVAILD);
}
// 使用IGlLineLaserDevice工厂方法创建GlLineLaserDevice
IGlLineLaserDevice* pGlDevice = nullptr;
int nRet = IGlLineLaserDevice::CreateGlLineLaserObject(&pGlDevice);
if (nRet == SUCCESS && pGlDevice) {
*ppDevice = pGlDevice;
LOG_INFO("[BagThreadPositionPresenter] Created GlLineLaser device\n");
return SUCCESS;
}
LOG_ERROR("[BagThreadPositionPresenter] Failed to create GlLineLaser device, error: %d\n", nRet);
return ERR_CODE(DEV_OPEN_ERR);
}