6 Commits
0.2.0 ... main

22 changed files with 3060 additions and 457 deletions

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@@ -1,5 +1,5 @@
cmake_minimum_required(VERSION 3.15)
project(D330Viewer VERSION 1.0.0 LANGUAGES CXX C)
project(Viewer VERSION 1.0.0 LANGUAGES CXX C)
# 设置C++标准
set(CMAKE_CXX_STANDARD 17)
@@ -34,7 +34,7 @@ find_package(Qt6 REQUIRED COMPONENTS
)
# 查找PCL
find_package(PCL REQUIRED COMPONENTS common io visualization)
find_package(PCL REQUIRED COMPONENTS common io visualization filters)
if(PCL_FOUND)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
@@ -101,6 +101,52 @@ add_executable(${PROJECT_NAME} WIN32
${RESOURCES}
)
# ==================== 标定文件(cmos0)检查 ====================
set(VIEWER_CALIBRATION_DIR "${CMAKE_SOURCE_DIR}/cmos0")
set(VIEWER_REQUIRED_CALIB_FILES
"coe.txt"
"kc.txt"
"KK.txt"
)
set(VIEWER_MISSING_CALIB_FILES "")
foreach(_calib_file IN LISTS VIEWER_REQUIRED_CALIB_FILES)
if(NOT EXISTS "${VIEWER_CALIBRATION_DIR}/${_calib_file}")
list(APPEND VIEWER_MISSING_CALIB_FILES "${_calib_file}")
endif()
endforeach()
option(VIEWER_REQUIRE_CALIB_FILES "Fail configure when required cmos0 calibration files are missing" ON)
if(VIEWER_MISSING_CALIB_FILES)
if(VIEWER_REQUIRE_CALIB_FILES)
message(FATAL_ERROR
"Missing calibration file(s) in ${VIEWER_CALIBRATION_DIR}: ${VIEWER_MISSING_CALIB_FILES}\n"
"Please ensure cmos0 contains: ${VIEWER_REQUIRED_CALIB_FILES}"
)
else()
message(WARNING
"Missing calibration file(s) in ${VIEWER_CALIBRATION_DIR}: ${VIEWER_MISSING_CALIB_FILES}\n"
"Build continues, but runtime or MSI may be incomplete."
)
endif()
else()
message(STATUS "Calibration files found: ${VIEWER_REQUIRED_CALIB_FILES}")
endif()
# 复制标定文件到运行目录bin/cmos0
if(EXISTS "${VIEWER_CALIBRATION_DIR}" AND NOT VIEWER_MISSING_CALIB_FILES)
add_custom_command(TARGET ${PROJECT_NAME} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E make_directory "$<TARGET_FILE_DIR:${PROJECT_NAME}>/cmos0"
COMMAND ${CMAKE_COMMAND} -E copy_directory
"${VIEWER_CALIBRATION_DIR}"
"$<TARGET_FILE_DIR:${PROJECT_NAME}>/cmos0"
COMMENT "Copy cmos0 calibration files to runtime directory"
)
else()
message(WARNING "Skip copying cmos0 because required calibration files are missing.")
endif()
# 链接库
target_link_libraries(${PROJECT_NAME}
Qt6::Core
@@ -141,25 +187,34 @@ install(DIRECTORY ${CMAKE_SOURCE_DIR}/bin/platforms/
FILES_MATCHING PATTERN "*.dll"
)
# 安装标定文件目录用于MSI
if(EXISTS "${VIEWER_CALIBRATION_DIR}" AND NOT VIEWER_MISSING_CALIB_FILES)
install(DIRECTORY ${VIEWER_CALIBRATION_DIR}/
DESTINATION cmos0
FILES_MATCHING
PATTERN "*.txt"
)
endif()
# ==================== CPack配置 - MSI安装程序 ====================
set(CPACK_PACKAGE_NAME "D330Viewer")
set(CPACK_PACKAGE_NAME "Viewer")
set(CPACK_PACKAGE_VENDOR "Lorenzo Zhao")
set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "D330M Depth Camera Control System")
set(CPACK_PACKAGE_VERSION "0.2.0")
set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "Depth Camera Control System")
set(CPACK_PACKAGE_VERSION "0.3.3")
set(CPACK_PACKAGE_VERSION_MAJOR "0")
set(CPACK_PACKAGE_VERSION_MINOR "2")
set(CPACK_PACKAGE_VERSION_PATCH "0")
set(CPACK_PACKAGE_INSTALL_DIRECTORY "D330Viewer")
set(CPACK_PACKAGE_VERSION_MINOR "3")
set(CPACK_PACKAGE_VERSION_PATCH "3")
set(CPACK_PACKAGE_INSTALL_DIRECTORY "Viewer")
# WiX生成器配置用于MSI
set(CPACK_GENERATOR "WIX")
set(CPACK_WIX_UPGRADE_GUID "42365CB0-5840-487F-A2C8-56F9699A9022")
set(CPACK_WIX_PROGRAM_MENU_FOLDER "D330Viewer")
set(CPACK_WIX_PROGRAM_MENU_FOLDER "Viewer")
set(CPACK_WIX_LICENSE_RTF "${CMAKE_SOURCE_DIR}/LICENSE.rtf")
# 创建开始菜单和桌面快捷方式
set(CPACK_PACKAGE_EXECUTABLES "D330Viewer" "D330Viewer")
set(CPACK_CREATE_DESKTOP_LINKS "D330Viewer")
set(CPACK_PACKAGE_EXECUTABLES "Viewer" "Viewer")
set(CPACK_CREATE_DESKTOP_LINKS "Viewer")
# 包含CPack模块
include(CPack)

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@@ -149,6 +149,7 @@ C:\Program Files\D330Viewer\
- ✅ 自动设备扫描和发现
- ✅ 相机连接管理(连接/断开)
- ✅ 命令发送START/STOP
- ✅ 下位机动态切换IP可随时切换上位机
#### 可视化
- ✅ 实时左红外、右红外相机图像显示
@@ -167,19 +168,64 @@ C:\Program Files\D330Viewer\
- ✅ 网络配置IP地址、端口设置
- ✅ 连接状态指示
- ✅ 配置持久化QSettings
- ✅ 点云颜色映射(深度着色)
- ✅ 多视角预设(正视、侧视、俯视)
### 🚧 当前开发计划
根据需求文档和用户反馈,后续待添加功能如下:
- 录制功能(连续保存多帧)
- 点云颜色映射(深度着色)
- 点云滤波选项(降噪、平滑)
- 测量工具(距离、角度测量)
- 多视角预设(正视、侧视、俯视)
- 性能监控CPU/GPU使用率、内存使用
- 其他相机参数调节(增益、白平衡等)
## 点云去噪原理与参数说明
### 去噪处理流程(当前版本)
当前点云去噪不是单一滤波器,而是多阶段组合策略,目标是在保留主体结构的同时抑制放射状无效点和外围杂点。
1. 有效点预筛:去掉非有限值和 `z<=0` 的点,得到基础有效掩码。
2. 中心ROI深度门控基于中心区域中位深度自适应裁剪深度窗口先去掉明显离群深度。
3. 邻域一致性筛选:统计每个点在局部窗口内“深度相近邻居”的数量,邻域支持不足的点剔除。
4. 形态学轻清理:移除局部孤立残点,减少毛刺。
5. 近距离尾部裁剪:对低深度尾部进行比例裁剪,抑制中心放射状噪点。
6. 连通簇筛选:按面积、深度一致性和中心重叠等条件保留主簇及相关簇,抑制周边散簇。
7. 最终细枝清理:对近距离且邻居不足的细枝点做额外抑制。
8. 时序稳定:对关键阈值做帧间平滑和限跳,减少块状点云“时有时无”的闪烁。
### 三个参数的作用与范围
参数都在“曝光与拍照 -> 拍照参数 -> 点云去噪参数”中,实时生效。
1. 邻域支持阈值
- 范围:`3 ~ 12`
- 含义:一个点要保留,局部邻域内至少需要多少个深度相近邻居。
- 调大:噪点更少,但边缘和细小结构更容易被吃掉。
- 调小:细节更多,但散点噪声会增加。
2. 射线裁剪强度 (‰)
- 范围:`5 ~ 50`
- 含义:近距离低深度尾部的裁剪比例(千分比)。
- 调大:中心放射状噪点减少更明显,但近距离真实细节可能减少。
- 调小:近距离细节保留更多,但放射状点可能增多。
3. 周边抑制带宽 (‰)
- 范围:`40 ~ 180`
- 含义:控制连通簇保留深度带宽、回补范围和近距离毛刺门限。
- 调小:抑制更激进,周边杂点更少,但主体可能偏“硬”、易丢块。
- 调大:主体与细节更完整,但外围杂点回升概率更高。
### 推荐起始参数
用于室内桌椅等常见场景,可先从以下值起步,再按效果微调:
- 邻域支持阈值:`8 ~ 10`
- 射线裁剪强度:`12 ~ 18`
- 周边抑制带宽:`90 ~ 130`
## 项目结构
```
@@ -283,4 +329,4 @@ d330viewer/
- 使用Qt6信号槽机制进行模块间通信
- OpenCL kernel代码内联在C++源文件中
- 配置使用QSettings持久化
- 日志输出到 `bin/d330viewer.log`
- 日志输出到 `%LOCALAPPDATA%/Viewer/Viewer/viewer.log`(例如 `C:/Users/<用户名>/AppData/Local/Viewer/Viewer/viewer.log`

3
cmos0/KK.txt Normal file
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@@ -0,0 +1,3 @@
1.4328957e+03 0.0000000e+00 6.3751170e+02
0.0000000e+00 1.4326590e+03 5.2187200e+02
0.0000000e+00 0.0000000e+00 1.0000000e+00

1224
cmos0/coe.txt Normal file

File diff suppressed because it is too large Load Diff

5
cmos0/kc.txt Normal file
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@@ -0,0 +1,5 @@
-1.2009005e-01
1.1928703e-01
9.6197371e-05
-1.4896083e-04
0.0000000e+00

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@@ -4,7 +4,7 @@ REM CMake配置脚本 - Windows版本
REM 请根据实际安装路径修改以下变量
echo ========================================
echo D330Viewer CMake配置脚本
echo Viewer CMake配置脚本
echo ========================================
echo.
@@ -47,7 +47,7 @@ if %ERRORLEVEL% EQU 0 (
echo ========================================
echo.
echo 下一步:
echo 1. 打开 build\D330Viewer.sln 使用Visual Studio编译
echo 1. 打开 build\Viewer.sln 使用Visual Studio编译
echo 2. 或运行: cmake --build build --config Release
echo.
) else (

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@@ -22,11 +22,15 @@
#define PIXEL_FORMAT_MONO16 0x01100005 // Mono16 format (legacy)
#define PIXEL_FORMAT_MONO16_LEFT 0x01100006 // Mono16 format for left IR camera
#define PIXEL_FORMAT_MONO16_RIGHT 0x01100007 // Mono16 format for right IR camera
#define PIXEL_FORMAT_MONO8_LEFT 0x01080006 // Mono8 format for left IR camera (downsampled)
#define PIXEL_FORMAT_MONO8_RIGHT 0x01080007 // Mono8 format for right IR camera (downsampled)
#define PIXEL_FORMAT_MJPEG 0x02180001 // MJPEG format for RGB camera
// Image dimensions
#define IMAGE_WIDTH 1224
#define IMAGE_HEIGHT 1024
#define IR_DISPLAY_WIDTH 612 // Downsampled IR display width
#define IR_DISPLAY_HEIGHT 512 // Downsampled IR display height
#define RGB_WIDTH 1920
#define RGB_HEIGHT 1080

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@@ -1,8 +1,10 @@
#ifndef POINTCLOUDPROCESSOR_H
#ifndef POINTCLOUDPROCESSOR_H
#define POINTCLOUDPROCESSOR_H
#include <QObject>
#include <QByteArray>
#include <atomic>
#include <mutex>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
#include <CL/cl.h>
@@ -15,44 +17,38 @@ public:
explicit PointCloudProcessor(QObject *parent = nullptr);
~PointCloudProcessor();
// 初始化OpenCL
bool initializeOpenCL();
// 设置相机内参
void setCameraIntrinsics(float fx, float fy, float cx, float cy);
// 设置Z缩放因子
void setZScaleFactor(float scale);
// 将深度数据转换为点云使用OpenCL GPU加速
void processDepthData(const QByteArray &depthData, uint32_t blockId);
// 处理已经计算好的点云数据x,y,z格式
void processPointCloudData(const QByteArray &cloudData, uint32_t blockId);
void setDenoiseEnabled(bool enabled);
void setDenoiseNeighborSupport(int minNeighbors);
void setDenoiseLowTailPermille(int permille);
void setDenoiseDepthBandPermille(int permille);
signals:
void pointCloudReady(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, uint32_t blockId);
void errorOccurred(const QString &error);
private:
// 清理OpenCL资源
pcl::PointCloud<pcl::PointXYZ>::Ptr applyDenoise(const pcl::PointCloud<pcl::PointXYZ>::Ptr &input);
void loadLowerCalibration();
void cleanupOpenCL();
// 相机内参
float m_fx;
float m_fy;
float m_cx;
float m_cy;
// Z缩放因子
float m_zScale;
// 图像尺寸
int m_imageWidth;
int m_imageHeight;
int m_totalPoints;
// OpenCL资源
cl_platform_id m_platform;
cl_device_id m_device;
cl_context m_context;
@@ -62,6 +58,30 @@ private:
cl_mem m_depthBuffer;
cl_mem m_xyzBuffer;
bool m_clInitialized;
std::atomic_bool m_denoiseEnabled;
float m_voxelLeafSize;
std::atomic_int m_denoiseNeighborSupport;
std::atomic_int m_denoiseLowTailPermille;
std::atomic_int m_denoiseDepthBandPermille;
// Calibration params aligned with lower-machine model
float m_k1;
float m_k2;
float m_p1;
float m_p2;
float m_p5;
float m_p6;
float m_p7;
float m_p8;
bool m_hasLowerCalibration;
// Temporal stabilizers for denoise to reduce frame-to-frame flicker.
std::mutex m_denoiseStateMutex;
bool m_hasAnchorMeanZ;
float m_anchorMeanZFiltered;
bool m_hasLowCutZ;
float m_lowCutZFiltered;
};
#endif // POINTCLOUDPROCESSOR_H

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@@ -23,6 +23,9 @@ public:
~PointCloudGLWidget();
void updatePointCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud);
void setColorMode(bool enabled) { m_colorMode = enabled ? 1 : 0; update(); }
bool colorMode() const { return m_colorMode != 0; }
void resetView(); // 重置视角到初始状态
protected:
void initializeGL() override;
@@ -48,25 +51,31 @@ private:
// 点云数据
std::vector<float> m_vertices;
int m_pointCount;
// 固定的点云中心点(避免抖动)
QVector3D m_fixedCenter;
bool m_centerInitialized;
float m_minZ, m_maxZ; // 深度范围(用于着色)
// 相机参数
QMatrix4x4 m_projection;
QMatrix4x4 m_view;
QMatrix4x4 m_model;
float m_orthoSize; // 正交投影视野大小(控制缩放)
float m_fov; // 透视投影视场角
float m_rotationX; // X轴旋转角度
float m_rotationY; // Y轴旋转角度
QVector3D m_translation; // 平移
QVector3D m_cloudCenter; // 点云中心
float m_viewDistance; // 观察距离
QVector3D m_panOffset; // 用户平移偏移
float m_zoom; // 缩放因子
// 鼠标交互状态
QPoint m_lastMousePos;
bool m_leftButtonPressed;
bool m_rightButtonPressed;
// 首帧标志(只在首帧时自动居中)
bool m_firstFrame;
// 颜色模式0=黑白1=彩色)
int m_colorMode;
};
#endif // POINTCLOUDGLWIDGET_H

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@@ -19,6 +19,10 @@ public:
// 更新点云显示
void updatePointCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud);
// 颜色模式控制
void setColorMode(bool enabled);
bool colorMode() const;
private:
QLabel *m_statusLabel;
PointCloudGLWidget *m_glWidget;

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@@ -1,7 +1,7 @@
#include "config/ConfigManager.h"
ConfigManager::ConfigManager()
: m_settings(std::make_unique<QSettings>("D330Viewer", "D330Viewer"))
: m_settings(std::make_unique<QSettings>("Viewer", "Viewer"))
{
// 构造函数初始化QSettings
}
@@ -45,7 +45,7 @@ void ConfigManager::setDataPort(int port)
// ========== 相机配置 ==========
int ConfigManager::getExposureTime() const
{
return m_settings->value("Camera/ExposureTime", 10000).toInt();
return m_settings->value("Camera/ExposureTime", 5980).toInt();
}
void ConfigManager::setExposureTime(int exposure)

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@@ -1,6 +1,8 @@
#include "DeviceScanner.h"
#include <QNetworkDatagram>
#include <QNetworkInterface>
#include <QCoreApplication>
#include <QThread>
#include <QDebug>
DeviceScanner::DeviceScanner(QObject *parent)
@@ -8,8 +10,9 @@ DeviceScanner::DeviceScanner(QObject *parent)
, m_socket(new QUdpSocket(this))
, m_timeoutTimer(new QTimer(this))
, m_scanTimer(new QTimer(this))
, m_currentHost(HOST_START)
, m_totalHosts(HOST_END - HOST_START + 1)
, m_prefixLength(24)
, m_currentHost(0)
, m_totalHosts(0)
, m_isScanning(false)
{
connect(m_socket, &QUdpSocket::readyRead, this, &DeviceScanner::onReadyRead);
@@ -33,8 +36,9 @@ void DeviceScanner::startScan(const QString &subnet)
return;
}
m_subnet = subnet.isEmpty() ? getLocalSubnet() : subnet;
m_currentHost = HOST_START;
// Get network info (base IP and prefix length)
getLocalNetworkInfo(m_baseIp, m_prefixLength);
m_foundDevices.clear();
m_isScanning = true;
@@ -44,17 +48,62 @@ void DeviceScanner::startScan(const QString &subnet)
return;
}
qDebug() << "Starting fast device scan on subnet:" << m_subnet;
// Send DISCOVER to all hosts at once (batch mode)
for (int host = HOST_START; host <= HOST_END; host++) {
QString ip = m_subnet + "." + QString::number(host);
sendDiscoveryPacket(ip);
// Calculate IP range based on prefix length
QStringList parts = m_baseIp.split('.');
if (parts.size() != 4) {
emit scanError("Invalid base IP");
m_isScanning = false;
return;
}
// Wait 3 seconds for all responses
m_timeoutTimer->start(3000);
qDebug() << "Sent discovery packets to all hosts, waiting for responses...";
quint32 baseAddr = (parts[0].toUInt() << 24) | (parts[1].toUInt() << 16) |
(parts[2].toUInt() << 8) | parts[3].toUInt();
quint32 mask = (0xFFFFFFFF << (32 - m_prefixLength)) & 0xFFFFFFFF;
quint32 networkAddr = baseAddr & mask;
quint32 broadcastAddr = networkAddr | (~mask & 0xFFFFFFFF);
qDebug() << "Starting device scan - Base IP:" << m_baseIp << "Prefix:" << m_prefixLength;
int packetsSent = 0;
// For large subnets (/16 or larger), use broadcast + batched unicast
if (m_prefixLength <= 16) {
// First: send to subnet broadcast address
QHostAddress broadcast(broadcastAddr);
qDebug() << "Large subnet detected, using broadcast discovery:" << broadcast.toString();
sendDiscoveryPacket(broadcast.toString());
packetsSent++;
// Second: scan all /24 subnets with throttling to avoid buffer overflow
qDebug() << "Scanning all /24 subnets within /16 range (throttled)...";
for (int oct3 = 0; oct3 <= 255; oct3++) {
quint32 subNetBase = (networkAddr & 0xFFFF0000) | (oct3 << 8);
for (int oct4 = 1; oct4 <= 254; oct4++) {
quint32 addr = subNetBase | oct4;
sendDiscoveryPacket(QHostAddress(addr).toString());
packetsSent++;
}
// Process events and add small delay every /24 subnet to avoid buffer overflow
QCoreApplication::processEvents();
QThread::msleep(5);
}
} else {
// For smaller subnets, scan all hosts
qDebug() << "Network range:" << QHostAddress(networkAddr + 1).toString()
<< "to" << QHostAddress(broadcastAddr - 1).toString();
for (quint32 addr = networkAddr + 1; addr < broadcastAddr; addr++) {
sendDiscoveryPacket(QHostAddress(addr).toString());
packetsSent++;
}
}
m_totalHosts = packetsSent;
qDebug() << "Sent" << packetsSent << "discovery packets, waiting for responses...";
// Adjust timeout based on network size
int timeout = (m_prefixLength >= 24) ? 3000 : 10000;
m_timeoutTimer->start(timeout);
}
void DeviceScanner::stopScan()
@@ -91,10 +140,17 @@ void DeviceScanner::onReadyRead()
qDebug() << "Received response from" << senderIp << ":" << response;
if (response.contains("D330M_CAMERA")) {
if (response.startsWith("EXPOSURE:")) {
bool ok;
int exposure = response.mid(9).trimmed().toInt(&ok);
if (ok && exposure > 0) {
qDebug() << "Received exposure from camera:" << exposure << "us";
emit exposureReceived(exposure);
}
} else if (response.contains("D330M_CAMERA")) {
DeviceInfo device;
device.ipAddress = senderIp;
device.deviceName = "D330M Camera";
device.deviceName = "Camera";
device.port = SCAN_PORT;
device.responseTime = 0;
@@ -122,7 +178,7 @@ void DeviceScanner::sendDiscoveryPacket(const QString &ip)
m_socket->writeDatagram(data, QHostAddress(ip), SCAN_PORT);
}
QString DeviceScanner::getLocalSubnet()
void DeviceScanner::getLocalNetworkInfo(QString &baseIp, int &prefixLength)
{
// Get all network interfaces
QList<QNetworkInterface> interfaces = QNetworkInterface::allInterfaces();
@@ -144,12 +200,14 @@ QString DeviceScanner::getLocalSubnet()
for (const QNetworkAddressEntry &entry : entries) {
QHostAddress addr = entry.ip();
if (addr.protocol() == QAbstractSocket::IPv4Protocol && !addr.isLoopback()) {
QString ip = addr.toString();
QStringList parts = ip.split('.');
if (parts.size() == 4) {
qDebug() << "Found Ethernet adapter:" << iface.humanReadableName() << "IP:" << ip;
return parts[0] + "." + parts[1] + "." + parts[2];
baseIp = addr.toString();
prefixLength = entry.prefixLength();
if (prefixLength <= 0 || prefixLength > 32) {
prefixLength = 24; // Default to /24 if invalid
}
qDebug() << "Found Ethernet adapter:" << iface.humanReadableName()
<< "IP:" << baseIp << "Prefix:" << prefixLength;
return;
}
}
}
@@ -169,15 +227,19 @@ QString DeviceScanner::getLocalSubnet()
for (const QNetworkAddressEntry &entry : entries) {
QHostAddress addr = entry.ip();
if (addr.protocol() == QAbstractSocket::IPv4Protocol && !addr.isLoopback()) {
QString ip = addr.toString();
QStringList parts = ip.split('.');
if (parts.size() == 4) {
qDebug() << "Found adapter:" << iface.humanReadableName() << "IP:" << ip;
return parts[0] + "." + parts[1] + "." + parts[2];
baseIp = addr.toString();
prefixLength = entry.prefixLength();
if (prefixLength <= 0 || prefixLength > 32) {
prefixLength = 24;
}
qDebug() << "Found adapter:" << iface.humanReadableName()
<< "IP:" << baseIp << "Prefix:" << prefixLength;
return;
}
}
}
return "192.168.0";
// Default fallback
baseIp = "192.168.0.1";
prefixLength = 24;
}

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@@ -29,6 +29,7 @@ public:
signals:
void deviceFound(const DeviceInfo &device);
void exposureReceived(int exposureUs);
void scanProgress(int current, int total);
void scanFinished(int devicesFound);
void scanError(const QString &error);
@@ -40,13 +41,14 @@ private slots:
private:
void sendDiscoveryPacket(const QString &ip);
QString getLocalSubnet();
void getLocalNetworkInfo(QString &baseIp, int &prefixLength);
QUdpSocket *m_socket;
QTimer *m_timeoutTimer;
QTimer *m_scanTimer;
QString m_subnet;
QString m_baseIp;
int m_prefixLength;
int m_currentHost;
int m_totalHosts;
bool m_isScanning;
@@ -55,8 +57,6 @@ private:
static constexpr int SCAN_PORT = 6790; // Control port for device discovery
static constexpr int SCAN_TIMEOUT = 10;
static constexpr int HOST_START = 1;
static constexpr int HOST_END = 254;
};
#endif // DEVICESCANNER_H

View File

@@ -96,9 +96,9 @@ void GVSPParser::handleLeaderPacket(const uint8_t *data, size_t size)
// 根据像素格式选择对应的状态
StreamState *state = nullptr;
if (pixelFormat == PIXEL_FORMAT_MONO16_LEFT) {
if (pixelFormat == PIXEL_FORMAT_MONO16_LEFT || pixelFormat == PIXEL_FORMAT_MONO8_LEFT) {
state = &m_leftIRState;
} else if (pixelFormat == PIXEL_FORMAT_MONO16_RIGHT) {
} else if (pixelFormat == PIXEL_FORMAT_MONO16_RIGHT || pixelFormat == PIXEL_FORMAT_MONO8_RIGHT) {
state = &m_rightIRState;
} else if (pixelFormat == PIXEL_FORMAT_MJPEG) {
state = &m_rgbState;
@@ -118,6 +118,9 @@ void GVSPParser::handleLeaderPacket(const uint8_t *data, size_t size)
if (pixelFormat == PIXEL_FORMAT_MJPEG) {
// MJPEG是压缩格式实际大小未知设置为0表示动态接收
state->expectedSize = 0;
} else if (pixelFormat == PIXEL_FORMAT_MONO8_LEFT || pixelFormat == PIXEL_FORMAT_MONO8_RIGHT) {
// 8-bit灰度格式下采样
state->expectedSize = imageWidth * imageHeight;
} else {
// 16-bit或12-bit灰度等固定格式
state->expectedSize = imageWidth * imageHeight * 2;
@@ -268,6 +271,29 @@ void GVSPParser::processImageData(GVSPParser::StreamState *state)
return;
}
// 处理Mono8格式左右红外相机下采样8位数据
if (state->pixelFormat == PIXEL_FORMAT_MONO8_LEFT) {
// 检查数据大小
if (state->dataBuffer.size() < state->expectedSize) {
return;
}
// 左红外8位数据
emit leftImageReceived(state->dataBuffer, state->blockId);
m_imageSequence++;
return;
}
if (state->pixelFormat == PIXEL_FORMAT_MONO8_RIGHT) {
// 检查数据大小
if (state->dataBuffer.size() < state->expectedSize) {
return;
}
// 右红外8位数据
emit rightImageReceived(state->dataBuffer, state->blockId);
m_imageSequence++;
return;
}
// 兼容旧版本使用序号区分legacy
if (state->pixelFormat == PIXEL_FORMAT_MONO16) {
// 检查数据大小

View File

@@ -16,6 +16,9 @@ NetworkManager::NetworkManager(QObject *parent)
connect(m_dataSocket, &QUdpSocket::readyRead, this, &NetworkManager::onReadyRead);
connect(m_dataSocket, &QUdpSocket::errorOccurred, this, &NetworkManager::onError);
// 连接控制socket接收信号用于接收相机回复如曝光值
connect(m_controlSocket, &QUdpSocket::readyRead, this, &NetworkManager::onControlReadyRead);
// 连接GVSP解析器信号
connect(m_gvspParser, &GVSPParser::imageReceived, this, &NetworkManager::imageReceived);
connect(m_gvspParser, &GVSPParser::leftImageReceived, this, &NetworkManager::leftImageReceived);
@@ -38,7 +41,7 @@ bool NetworkManager::connectToCamera(const QString &ip, int controlPort, int dat
m_dataPort = dataPort;
// 绑定控制Socket到任意端口让系统自动分配
if (!m_controlSocket->bind(QHostAddress::Any, 0)) {
if(!m_controlSocket->bind(QHostAddress::Any, 0)) {
QString error = QString("Failed to bind control socket: %1")
.arg(m_controlSocket->errorString());
qDebug() << error;
@@ -48,7 +51,7 @@ bool NetworkManager::connectToCamera(const QString &ip, int controlPort, int dat
qDebug() << "Successfully bound control socket to port" << m_controlSocket->localPort();
// 绑定数据接收端口
if (!m_dataSocket->bind(QHostAddress::Any, m_dataPort)) {
if(!m_dataSocket->bind(QHostAddress::Any, m_dataPort)) {
QString error = QString("Failed to bind data port %1: %2")
.arg(m_dataPort)
.arg(m_dataSocket->errorString());
@@ -67,6 +70,10 @@ bool NetworkManager::connectToCamera(const QString &ip, int controlPort, int dat
m_isConnected = true;
qDebug() << "Connected to camera:" << m_cameraIp << "Control port:" << m_controlPort << "Data port:" << m_dataPort;
// Send DISCOVER to get camera's current exposure value
sendCommand("DISCOVER");
qDebug() << "Sent DISCOVER to fetch camera exposure";
// Send STOP command to register client IP on camera
sendStopCommand();
qDebug() << "Sent STOP command to register client IP";
@@ -77,7 +84,7 @@ bool NetworkManager::connectToCamera(const QString &ip, int controlPort, int dat
void NetworkManager::disconnectFromCamera()
{
if (m_isConnected) {
if(m_isConnected) {
m_controlSocket->close();
m_dataSocket->close();
m_isConnected = false;
@@ -94,7 +101,7 @@ bool NetworkManager::isConnected() const
// ========== 发送控制命令 ==========
bool NetworkManager::sendCommand(const QString &command)
{
if (!m_isConnected) {
if(!m_isConnected) {
qDebug() << "Not connected to camera";
return false;
}
@@ -109,7 +116,7 @@ bool NetworkManager::sendCommand(const QString &command)
qint64 sent = m_controlSocket->writeDatagram(data, QHostAddress(m_cameraIp), m_controlPort);
qDebug() << "writeDatagram returned:" << sent;
if (sent == -1) {
if(sent == -1) {
QString error = QString("Failed to send command: %1").arg(m_controlSocket->errorString());
qDebug() << error;
qDebug() << "Socket error code:" << m_controlSocket->error();
@@ -134,23 +141,8 @@ bool NetworkManager::sendStopCommand()
bool NetworkManager::sendExposureCommand(int exposureTime)
{
// 同时发送结构光曝光命令UART控制激光器单位μs
QString exposureCommand = QString("EXPOSURE:%1").arg(exposureTime);
bool success1 = sendCommand(exposureCommand);
// 同时发送红外相机曝光命令通过触发脉冲宽度控制单位μs
// 下位机会将此值用作manual_trigger_pulse()的脉冲宽度参数
// 脉冲宽度直接决定相机的实际曝光时间
int irExposure = exposureTime;
// 限制在有效范围内1000μs ~ 100000μs避免脉冲太短导致相机无法触发
if (irExposure < 1000) irExposure = 1000;
if (irExposure > 100000) irExposure = 100000;
QString irExposureCommand = QString("IR_EXPOSURE:%1").arg(irExposure);
bool success2 = sendCommand(irExposureCommand);
return success1 && success2;
return sendCommand(exposureCommand);
}
// ========== 传输开关命令 ==========
@@ -208,7 +200,7 @@ void NetworkManager::onReadyRead()
m_dataSocket->readDatagram(datagram.data(), datagram.size(), &sender, &senderPort);
// 只打印前5个包的详细信息
if (packetCount < 5) {
if(packetCount < 5) {
// qDebug() << "[NetworkManager] Packet" << packetCount
// << "from" << sender.toString() << ":" << senderPort
// << "size:" << datagram.size() << "bytes";
@@ -223,11 +215,32 @@ void NetworkManager::onReadyRead()
}
// 每1000个包打印一次统计减少日志量
if (packetCount % 1000 == 0) {
if(packetCount % 1000 == 0) {
// qDebug() << "[NetworkManager] Total packets received:" << packetCount;
}
}
void NetworkManager::onControlReadyRead()
{
while (m_controlSocket->hasPendingDatagrams()) {
QByteArray datagram;
datagram.resize(m_controlSocket->pendingDatagramSize());
m_controlSocket->readDatagram(datagram.data(), datagram.size());
QString response = QString::fromUtf8(datagram);
qDebug() << "[NetworkManager] Control response:" << response;
if (response.startsWith("EXPOSURE:")) {
bool ok;
int exposure = response.mid(9).trimmed().toInt(&ok);
if (ok && exposure > 0) {
qDebug() << "[NetworkManager] Camera exposure:" << exposure << "us";
emit exposureReceived(exposure);
}
}
}
}
void NetworkManager::onError(QAbstractSocket::SocketError socketError)
{
QString error = QString("Socket error: %1").arg(m_dataSocket->errorString());

View File

@@ -43,6 +43,7 @@ public:
signals:
void connected();
void disconnected();
void exposureReceived(int exposureUs);
void errorOccurred(const QString &error);
void dataReceived(const QByteArray &data);
void imageReceived(const QImage &image, uint32_t blockId);
@@ -54,6 +55,7 @@ signals:
private slots:
void onReadyRead();
void onControlReadyRead();
void onError(QAbstractSocket::SocketError socketError);
private:

View File

@@ -1,12 +1,93 @@
#include "core/PointCloudProcessor.h"
#include <QDebug>
#include <QCoreApplication>
#include <QDir>
#include <QFile>
#include <QRegularExpression>
#include <QStringList>
#include <vector>
#include <cmath>
#include <cstdint>
#include <algorithm>
#include <unordered_map>
#include <pcl/common/point_tests.h>
#ifndef M_PI
#define M_PI 3.14159265358979323846
#endif
namespace {
struct VoxelKey {
int x;
int y;
int z;
bool operator==(const VoxelKey &other) const noexcept
{
return x == other.x && y == other.y && z == other.z;
}
};
struct VoxelKeyHash {
size_t operator()(const VoxelKey &k) const noexcept
{
// FNV-1a hash for 3D integer voxel index.
uint64_t h = 1469598103934665603ull;
auto mix = [&h](uint64_t v) {
h ^= v;
h *= 1099511628211ull;
};
mix(static_cast<uint32_t>(k.x));
mix(static_cast<uint32_t>(k.y));
mix(static_cast<uint32_t>(k.z));
return static_cast<size_t>(h);
}
};
struct VoxelAccum {
float sumX = 0.0f;
float sumY = 0.0f;
float sumZ = 0.0f;
uint32_t count = 0;
};
constexpr int kNeighborOffsets[26][3] = {
{-1, -1, -1}, {0, -1, -1}, {1, -1, -1},
{-1, 0, -1}, {0, 0, -1}, {1, 0, -1},
{-1, 1, -1}, {0, 1, -1}, {1, 1, -1},
{-1, -1, 0}, {0, -1, 0}, {1, -1, 0},
{-1, 0, 0}, {1, 0, 0},
{-1, 1, 0}, {0, 1, 0}, {1, 1, 0},
{-1, -1, 1}, {0, -1, 1}, {1, -1, 1},
{-1, 0, 1}, {0, 0, 1}, {1, 0, 1},
{-1, 1, 1}, {0, 1, 1}, {1, 1, 1}
};
bool readFloatFile(const QString &path, std::vector<float> &out)
{
QFile file(path);
if (!file.open(QIODevice::ReadOnly | QIODevice::Text)) {
return false;
}
const QByteArray raw = file.readAll();
const QString text = QString::fromUtf8(raw);
const QStringList tokens = text.split(QRegularExpression("\\s+"), Qt::SkipEmptyParts);
out.clear();
out.reserve(tokens.size());
for (const QString &token : tokens) {
bool ok = false;
float value = token.toFloat(&ok);
if (ok) {
out.push_back(value);
}
}
return !out.empty();
}
} // namespace
PointCloudProcessor::PointCloudProcessor(QObject *parent)
: QObject(parent)
, m_fx(1432.8957f)
@@ -26,7 +107,26 @@ PointCloudProcessor::PointCloudProcessor(QObject *parent)
, m_depthBuffer(nullptr)
, m_xyzBuffer(nullptr)
, m_clInitialized(false)
, m_denoiseEnabled(false)
, m_voxelLeafSize(2.5f)
, m_denoiseNeighborSupport(6)
, m_denoiseLowTailPermille(15)
, m_denoiseDepthBandPermille(80)
, m_k1(0.0f)
, m_k2(0.0f)
, m_p1(0.0f)
, m_p2(0.0f)
, m_p5(1.0f / 1432.8957f)
, m_p6(-637.5117f / 1432.8957f)
, m_p7(1.0f / 1432.6590f)
, m_p8(-521.8720f / 1432.6590f)
, m_hasLowerCalibration(false)
, m_hasAnchorMeanZ(false)
, m_anchorMeanZFiltered(0.0f)
, m_hasLowCutZ(false)
, m_lowCutZFiltered(0.0f)
{
loadLowerCalibration();
}
PointCloudProcessor::~PointCloudProcessor()
@@ -40,6 +140,14 @@ void PointCloudProcessor::setCameraIntrinsics(float fx, float fy, float cx, floa
m_fy = fy;
m_cx = cx;
m_cy = cy;
// Keep lower-machine style projection terms in sync when intrinsics are changed at runtime.
if (m_fx != 0.0f && m_fy != 0.0f) {
m_p5 = 1.0f / m_fx;
m_p6 = -m_cx / m_fx;
m_p7 = 1.0f / m_fy;
m_p8 = -m_cy / m_fy;
}
}
void PointCloudProcessor::setZScaleFactor(float scale)
@@ -47,6 +155,557 @@ void PointCloudProcessor::setZScaleFactor(float scale)
m_zScale = scale;
}
void PointCloudProcessor::loadLowerCalibration()
{
const QString appDir = QCoreApplication::applicationDirPath();
QStringList candidates;
candidates
<< QDir::current().filePath("cmos0")
<< QDir(appDir).filePath("cmos0")
<< QDir(appDir).filePath("../cmos0")
<< QDir(appDir).filePath("../../cmos0");
for (const QString &dirPath : candidates) {
const QString kcPath = QDir(dirPath).filePath("kc.txt");
const QString kkPath = QDir(dirPath).filePath("KK.txt");
if (!QFile::exists(kcPath) || !QFile::exists(kkPath)) {
continue;
}
std::vector<float> kcVals;
std::vector<float> kkVals;
if (!readFloatFile(kcPath, kcVals) || !readFloatFile(kkPath, kkVals)) {
continue;
}
if (kcVals.size() < 4 || kkVals.size() < 6) {
continue;
}
const float fx = kkVals[0];
const float cx = kkVals[2];
const float fy = kkVals[4];
const float cy = kkVals[5];
if (fx == 0.0f || fy == 0.0f) {
continue;
}
m_k1 = kcVals[0];
m_k2 = kcVals[1];
m_p1 = kcVals[2];
m_p2 = kcVals[3];
m_fx = fx;
m_fy = fy;
m_cx = cx;
m_cy = cy;
m_p5 = 1.0f / fx;
m_p6 = -cx / fx;
m_p7 = 1.0f / fy;
m_p8 = -cy / fy;
m_hasLowerCalibration = true;
qDebug() << "[PointCloud] Loaded lower calibration from" << dirPath
<< "kc size:" << static_cast<int>(kcVals.size())
<< "KK size:" << static_cast<int>(kkVals.size());
return;
}
m_hasLowerCalibration = false;
qDebug() << "[PointCloud] lower calibration txt not found, using fallback intrinsics";
}
void PointCloudProcessor::setDenoiseEnabled(bool enabled)
{
m_denoiseEnabled.store(enabled, std::memory_order_relaxed);
}
void PointCloudProcessor::setDenoiseNeighborSupport(int minNeighbors)
{
m_denoiseNeighborSupport.store(std::clamp(minNeighbors, 3, 12), std::memory_order_relaxed);
}
void PointCloudProcessor::setDenoiseLowTailPermille(int permille)
{
m_denoiseLowTailPermille.store(std::clamp(permille, 5, 50), std::memory_order_relaxed);
}
void PointCloudProcessor::setDenoiseDepthBandPermille(int permille)
{
m_denoiseDepthBandPermille.store(std::clamp(permille, 40, 180), std::memory_order_relaxed);
}
pcl::PointCloud<pcl::PointXYZ>::Ptr PointCloudProcessor::applyDenoise(
const pcl::PointCloud<pcl::PointXYZ>::Ptr &input)
{
if (!input || input->empty()) {
return input;
}
const size_t total = input->points.size();
const int width = static_cast<int>(input->width);
const int height = static_cast<int>(input->height);
const int supportMinNeighbors = m_denoiseNeighborSupport.load(std::memory_order_relaxed);
const int lowTailPermille = m_denoiseLowTailPermille.load(std::memory_order_relaxed);
const int depthBandPermille = m_denoiseDepthBandPermille.load(std::memory_order_relaxed);
bool hasPrevAnchor = false;
float prevAnchorMeanZ = 0.0f;
bool hasPrevLowCut = false;
float prevLowCutZ = 0.0f;
{
std::lock_guard<std::mutex> lock(m_denoiseStateMutex);
hasPrevAnchor = m_hasAnchorMeanZ;
prevAnchorMeanZ = m_anchorMeanZFiltered;
hasPrevLowCut = m_hasLowCutZ;
prevLowCutZ = m_lowCutZFiltered;
}
bool anchorUpdated = false;
float anchorToStore = 0.0f;
bool lowCutUpdated = false;
float lowCutToStore = 0.0f;
// Fallback for unorganized clouds: only remove invalid points.
if (width <= 1 || height <= 1 || static_cast<size_t>(width) * static_cast<size_t>(height) != total) {
pcl::PointCloud<pcl::PointXYZ>::Ptr validOnly(new pcl::PointCloud<pcl::PointXYZ>());
validOnly->points.reserve(total);
for (const auto &p : input->points) {
if (pcl::isFinite(p) && p.z > 0.0f) {
validOnly->points.push_back(p);
}
}
if (validOnly->points.empty()) {
return input;
}
validOnly->width = static_cast<uint32_t>(validOnly->points.size());
validOnly->height = 1;
validOnly->is_dense = true;
return validOnly;
}
const auto idx = [width](int r, int c) -> int { return r * width + c; };
std::vector<uint8_t> validMask(total, 0);
float minZ = std::numeric_limits<float>::max();
float maxZ = std::numeric_limits<float>::lowest();
int validCount = 0;
for (size_t i = 0; i < total; ++i) {
const auto &p = input->points[i];
if (pcl::isFinite(p) && p.z > 0.0f) {
validMask[i] = 1;
++validCount;
if (p.z < minZ) minZ = p.z;
if (p.z > maxZ) maxZ = p.z;
}
}
if (validCount < 1200) {
return input;
}
// Pass 0: adaptive conditional depth gate (inspired by ConditionalRemoval/CropBox idea).
// Use center ROI median depth as reference, then keep a dynamic depth band.
const float spanZ = std::max(0.0f, maxZ - minZ);
int gatedCount = validCount;
if (spanZ > 1e-3f) {
const int r0 = static_cast<int>(height * 0.35f);
const int r1 = static_cast<int>(height * 0.75f);
const int c0 = static_cast<int>(width * 0.35f);
const int c1 = static_cast<int>(width * 0.65f);
std::vector<float> centerZ;
centerZ.reserve(static_cast<size_t>((r1 - r0) * (c1 - c0)));
for (int r = r0; r < r1; ++r) {
for (int c = c0; c < c1; ++c) {
const int i = idx(r, c);
if (validMask[i]) {
centerZ.push_back(input->points[i].z);
}
}
}
if (centerZ.size() > 800) {
const size_t mid = centerZ.size() / 2;
std::nth_element(centerZ.begin(), centerZ.begin() + mid, centerZ.end());
const float zRef = centerZ[mid];
const float zNear = std::max(minZ, zRef - std::max(80.0f, spanZ * 0.08f));
const float zFar = std::min(maxZ, zRef + std::max(250.0f, spanZ * 0.22f));
gatedCount = 0;
for (size_t i = 0; i < total; ++i) {
if (!validMask[i]) {
continue;
}
const float z = input->points[i].z;
if (z < zNear || z > zFar) {
validMask[i] = 0;
} else {
++gatedCount;
}
}
// If gate is too aggressive, rollback.
if (gatedCount < 2000) {
std::fill(validMask.begin(), validMask.end(), 0);
gatedCount = 0;
for (size_t i = 0; i < total; ++i) {
const auto &p = input->points[i];
if (pcl::isFinite(p) && p.z > 0.0f) {
validMask[i] = 1;
++gatedCount;
}
}
}
}
}
// Pass 1: local depth-consistency support in 3x3 neighborhood.
// This suppresses thin ray artifacts while preserving contiguous surfaces.
std::vector<uint8_t> supportMask(total, 0);
int supportCount = 0;
for (int r = 2; r < height - 2; ++r) {
for (int c = 2; c < width - 2; ++c) {
const int center = idx(r, c);
if (!validMask[center]) {
continue;
}
const float z = input->points[center].z;
const float dzThreshold = std::max(12.0f, z * 0.015f);
int neighbors = 0;
for (int rr = -2; rr <= 2; ++rr) {
for (int cc = -2; cc <= 2; ++cc) {
if (rr == 0 && cc == 0) {
continue;
}
const int ni = idx(r + rr, c + cc);
if (!validMask[ni]) {
continue;
}
if (std::fabs(input->points[ni].z - z) <= dzThreshold) {
++neighbors;
}
}
}
if (neighbors >= supportMinNeighbors) {
supportMask[center] = 1;
++supportCount;
}
}
}
if (supportCount < 1500) {
return input;
}
// Pass 1.5: one morphology-like cleanup to remove sparse remnants.
std::vector<uint8_t> cleanMask = supportMask;
int cleanCount = 0;
for (int r = 1; r < height - 1; ++r) {
for (int c = 1; c < width - 1; ++c) {
const int center = idx(r, c);
if (!supportMask[center]) {
continue;
}
int kept = 0;
for (int rr = -1; rr <= 1; ++rr) {
for (int cc = -1; cc <= 1; ++cc) {
if (rr == 0 && cc == 0) {
continue;
}
if (supportMask[idx(r + rr, c + cc)]) {
++kept;
}
}
}
if (kept < 2) {
cleanMask[center] = 0;
}
if (cleanMask[center]) {
++cleanCount;
}
}
}
if (cleanCount >= 1500) {
supportMask.swap(cleanMask);
supportCount = cleanCount;
}
// Pass 2: clip the near-camera low-depth tail to suppress center-radiating streaks.
std::vector<uint8_t> finalMask = supportMask;
if (spanZ > 1e-3f) {
constexpr int kBins = 256;
std::vector<int> hist(kBins, 0);
for (size_t i = 0; i < total; ++i) {
if (!supportMask[i]) {
continue;
}
const float z = input->points[i].z;
int b = static_cast<int>((z - minZ) / spanZ * static_cast<float>(kBins - 1));
b = std::clamp(b, 0, kBins - 1);
++hist[b];
}
const int lowTailTarget = std::max(120, static_cast<int>(supportCount * (static_cast<float>(lowTailPermille) / 1000.0f)));
int accum = 0;
int lowBin = 0;
for (int b = 0; b < kBins; ++b) {
accum += hist[b];
if (accum >= lowTailTarget) {
lowBin = b;
break;
}
}
const float rawLowCut = minZ + spanZ * (static_cast<float>(lowBin) / static_cast<float>(kBins - 1));
float zLowCut = rawLowCut;
if (hasPrevLowCut) {
const float maxJump = std::max(120.0f, spanZ * 0.10f);
const float clamped = std::clamp(rawLowCut, prevLowCutZ - maxJump, prevLowCutZ + maxJump);
zLowCut = prevLowCutZ * 0.65f + clamped * 0.35f;
}
lowCutUpdated = true;
lowCutToStore = zLowCut;
int finalCount = 0;
for (size_t i = 0; i < total; ++i) {
if (finalMask[i] && input->points[i].z < zLowCut) {
finalMask[i] = 0;
}
if (finalMask[i]) {
++finalCount;
}
}
if (finalCount < 1200) {
finalMask = supportMask;
}
}
// Pass 2.5: 2D connected components + foreground-priority keep.
// This suppresses surrounding residual blobs while preserving the near main object.
struct ComponentStat {
std::vector<int> pixels;
int area = 0;
float zSum = 0.0f;
int centerOverlap = 0;
};
const int centerR0 = static_cast<int>(height * 0.35f);
const int centerR1 = static_cast<int>(height * 0.75f);
const int centerC0 = static_cast<int>(width * 0.35f);
const int centerC1 = static_cast<int>(width * 0.65f);
std::vector<uint8_t> visited(total, 0);
std::vector<ComponentStat> comps;
comps.reserve(32);
std::vector<int> queue;
queue.reserve(4096);
constexpr int cdr[8] = {-1, -1, -1, 0, 0, 1, 1, 1};
constexpr int cdc[8] = {-1, 0, 1, -1, 1, -1, 0, 1};
for (int r = 0; r < height; ++r) {
for (int c = 0; c < width; ++c) {
const int seed = idx(r, c);
if (!finalMask[seed] || visited[seed]) {
continue;
}
ComponentStat comp;
queue.clear();
queue.push_back(seed);
visited[seed] = 1;
for (size_t head = 0; head < queue.size(); ++head) {
const int cur = queue[head];
const int rr = cur / width;
const int cc = cur % width;
comp.pixels.push_back(cur);
comp.area += 1;
comp.zSum += input->points[cur].z;
if (rr >= centerR0 && rr < centerR1 && cc >= centerC0 && cc < centerC1) {
comp.centerOverlap += 1;
}
for (int k = 0; k < 8; ++k) {
const int nr = rr + cdr[k];
const int nc = cc + cdc[k];
if (nr < 0 || nr >= height || nc < 0 || nc >= width) {
continue;
}
const int ni = idx(nr, nc);
if (!finalMask[ni] || visited[ni]) {
continue;
}
visited[ni] = 1;
queue.push_back(ni);
}
}
comps.push_back(std::move(comp));
}
}
if (!comps.empty()) {
int anchor = -1;
float anchorMeanZ = std::numeric_limits<float>::max();
int anchorArea = 0;
float bestScore = -std::numeric_limits<float>::max();
const float temporalBand = std::max(120.0f, spanZ * 0.10f);
// Stable anchor selection with temporal bias to reduce frame-to-frame jumping.
for (int i = 0; i < static_cast<int>(comps.size()); ++i) {
const auto &cp = comps[i];
if (cp.area < 300) {
continue;
}
const float meanZ = cp.zSum / static_cast<float>(cp.area);
float score = static_cast<float>(cp.centerOverlap) * 6.0f
+ static_cast<float>(std::min(cp.area, 12000)) * 0.25f;
if (hasPrevAnchor) {
const float dz = std::fabs(meanZ - prevAnchorMeanZ);
score -= dz * 0.35f;
if (dz <= temporalBand) {
score += 1200.0f;
}
}
if (score > bestScore) {
bestScore = score;
anchor = i;
anchorMeanZ = meanZ;
anchorArea = cp.area;
}
}
if (anchor >= 0) {
float stableAnchorMeanZ = anchorMeanZ;
if (hasPrevAnchor) {
const float maxJump = std::max(180.0f, spanZ * 0.15f);
const float clamped = std::clamp(anchorMeanZ, prevAnchorMeanZ - maxJump, prevAnchorMeanZ + maxJump);
stableAnchorMeanZ = prevAnchorMeanZ * 0.60f + clamped * 0.40f;
}
anchorUpdated = true;
anchorToStore = stableAnchorMeanZ;
std::vector<uint8_t> ccMask(total, 0);
int kept = 0;
// Make depth-band slider more perceptible: 40 -> tight (strong suppression), 180 -> loose.
const float bandT = std::clamp((static_cast<float>(depthBandPermille) - 40.0f) / 140.0f, 0.0f, 1.0f);
const float zKeepBandFloor = 90.0f + 260.0f * bandT;
const float zKeepBandSpanFactor = 0.03f + 0.19f * bandT;
const float zKeepBandBase = std::max(zKeepBandFloor, spanZ * zKeepBandSpanFactor);
const float zKeepBand = hasPrevAnchor
? (zKeepBandBase * (1.15f + 0.35f * bandT))
: (zKeepBandBase * (1.00f + 0.25f * bandT));
const float minKeepAreaRatio = 0.035f - 0.020f * bandT;
const int minKeepArea = std::max(60, static_cast<int>(anchorArea * minKeepAreaRatio));
for (const auto &cp : comps) {
if (cp.area < minKeepArea) {
continue;
}
const float meanZ = cp.zSum / static_cast<float>(cp.area);
const float overlapBonus = (cp.centerOverlap > 0) ? (zKeepBand * 0.45f) : 0.0f;
if (meanZ > stableAnchorMeanZ + zKeepBand + overlapBonus) {
continue;
}
for (int p : cp.pixels) {
ccMask[p] = 1;
++kept;
}
}
// Apply when preserving a reasonable part of support mask to avoid frame jumps.
const float minStableRatio = 0.18f - 0.10f * bandT;
const int minStableKeep = std::max(1000, static_cast<int>(supportCount * minStableRatio));
if (kept >= minStableKeep) {
// Soft fallback: keep previously accepted support points that are depth-consistent.
const float softKeepFar = stableAnchorMeanZ + zKeepBand * (1.20f + 1.60f * bandT);
for (size_t i = 0; i < total; ++i) {
if (finalMask[i] && !ccMask[i] && input->points[i].z <= softKeepFar) {
ccMask[i] = 1;
}
}
finalMask.swap(ccMask);
}
}
}
// Pass 2.8: final spur cleanup to reduce radiating thin points.
{
std::vector<uint8_t> pruned = finalMask;
int keptAfterPrune = 0;
const float bandT = std::clamp((static_cast<float>(depthBandPermille) - 40.0f) / 140.0f, 0.0f, 1.0f);
const float nearRaySpanFactor = 0.10f - 0.06f * bandT;
const float nearRayOffset = std::max(70.0f, spanZ * nearRaySpanFactor);
const float nearRayGate = lowCutUpdated
? (lowCutToStore + nearRayOffset)
: (minZ + spanZ * (0.22f - 0.10f * bandT));
for (int r = 1; r < height - 1; ++r) {
for (int c = 1; c < width - 1; ++c) {
const int center = idx(r, c);
if (!finalMask[center]) {
continue;
}
int n = 0;
for (int rr = -1; rr <= 1; ++rr) {
for (int cc = -1; cc <= 1; ++cc) {
if (rr == 0 && cc == 0) {
continue;
}
if (finalMask[idx(r + rr, c + cc)]) {
++n;
}
}
}
if (n < 2 && input->points[center].z < nearRayGate) {
pruned[center] = 0;
}
if (pruned[center]) {
++keptAfterPrune;
}
}
}
if (keptAfterPrune >= 1200) {
finalMask.swap(pruned);
}
}
pcl::PointCloud<pcl::PointXYZ>::Ptr denoised(new pcl::PointCloud<pcl::PointXYZ>());
denoised->points.reserve(static_cast<size_t>(supportCount));
for (size_t i = 0; i < total; ++i) {
if (finalMask[i]) {
denoised->points.push_back(input->points[i]);
}
}
if (denoised->points.empty()) {
return input;
}
denoised->width = static_cast<uint32_t>(denoised->points.size());
denoised->height = 1;
denoised->is_dense = true;
{
std::lock_guard<std::mutex> lock(m_denoiseStateMutex);
if (anchorUpdated) {
m_anchorMeanZFiltered = anchorToStore;
m_hasAnchorMeanZ = true;
}
if (lowCutUpdated) {
m_lowCutZFiltered = lowCutToStore;
m_hasLowCutZ = true;
}
}
return denoised;
}
bool PointCloudProcessor::initializeOpenCL()
{
if (m_clInitialized) {
@@ -106,9 +765,8 @@ bool PointCloudProcessor::initializeOpenCL()
"int y = idx / width; "
"int x = idx % width; "
"float z = depth[idx] * z_scale; "
// 完全平面的圆柱投影X和Y直接使用像素坐标缩放到合适的范围
"xyz[idx*3] = (x - cx) * 2.0f; " // X坐标缩放系数2.0
"xyz[idx*3+1] = -(y - cy) * 2.0f; " // Y坐标取反修正上下颠倒
"xyz[idx*3] = (x - cx) * z * inv_fx; "
"xyz[idx*3+1] = (y - cy) * z * inv_fy; "
"xyz[idx*3+2] = z; "
"}";
@@ -248,6 +906,9 @@ void PointCloudProcessor::processDepthData(const QByteArray &depthData, uint32_t
// 注释掉频繁的日志输出
// qDebug() << "[PointCloud] Block" << blockId << "processed successfully";
if (m_denoiseEnabled.load(std::memory_order_relaxed)) {
cloud = applyDenoise(cloud);
}
emit pointCloudReady(cloud, blockId);
}
@@ -283,36 +944,65 @@ void PointCloudProcessor::processPointCloudData(const QByteArray &cloudData, uin
// 从int16_t数组读取点云数据
const int16_t* cloudShort = reinterpret_cast<const int16_t*>(cloudData.constData());
// 与下位机 gpu_calculate_pointcloud.cl 对齐的参数:
// u = p5 * (j - 0.5) + p6, v = p7 * (i + 1) + p8
// (k1,k2,p1,p2,p5,p6,p7,p8) 由 cmos0/kc.txt 与 cmos0/KK.txt 加载。
if (isZOnly) {
// Z-only格式转换为正交投影(柱形)
// Z-only格式标准针孔模型反投影
for (size_t i = 0; i < m_totalPoints; i++) {
int row = i / m_imageWidth;
int col = i % m_imageWidth;
// 读取深度值(单位:毫米)
float z = static_cast<float>(cloudShort[i]) * m_zScale;
// 正交投影X、Y使用像素坐标Y轴翻转以修正镜像
cloud->points[i].x = static_cast<float>(col);
cloud->points[i].y = static_cast<float>(m_imageHeight - 1 - row);
// 旧公式保留,便于快速回退:
// cloud->points[i].x = (col - m_cx) * z * inv_fx;
// cloud->points[i].y = (row - m_cy) * z * inv_fy;
// 下位机同款:先求(u,v)并做畸变修正得到(unc,vnc)再乘z得到(x,y)
float u = m_p5 * (static_cast<float>(col) - 0.5f) + m_p6;
float v = m_p7 * (static_cast<float>(row) + 1.0f) + m_p8;
float r = u * u + v * v;
float temp3 = 1.0f / (1.0f + m_k1 * r + m_k2 * r * r);
float unc = temp3 * (u - 2.0f * m_p1 * u * v - m_p2 * (r + 2.0f * u * u));
float vnc = temp3 * (v - m_p1 * (r + 2.0f * v * v) - 2.0f * m_p2 * u * v);
cloud->points[i].x = unc * z;
cloud->points[i].y = vnc * z;
cloud->points[i].z = z;
}
} else {
// XYZ格式完整的三维坐标
// 转换为正交投影柱形使用像素坐标作为X、Y
// XYZ格式使用Z值进行针孔模型反投影
for (size_t i = 0; i < m_totalPoints; i++) {
int row = i / m_imageWidth;
int col = i % m_imageWidth;
// 正交投影X、Y使用像素坐标Y轴翻转以修正镜像Z使用深度值
cloud->points[i].x = static_cast<float>(col);
cloud->points[i].y = static_cast<float>(m_imageHeight - 1 - row);
cloud->points[i].z = static_cast<float>(cloudShort[i * 3 + 2]) * m_zScale;
float z = static_cast<float>(cloudShort[i * 3 + 2]) * m_zScale;
// 旧公式保留,便于快速回退:
// cloud->points[i].x = (col - m_cx) * z * inv_fx;
// cloud->points[i].y = (row - m_cy) * z * inv_fy;
// 下位机同款:先求(u,v)并做畸变修正得到(unc,vnc)再乘z得到(x,y)
float u = m_p5 * (static_cast<float>(col) - 0.5f) + m_p6;
float v = m_p7 * (static_cast<float>(row) + 1.0f) + m_p8;
float r = u * u + v * v;
float temp3 = 1.0f / (1.0f + m_k1 * r + m_k2 * r * r);
float unc = temp3 * (u - 2.0f * m_p1 * u * v - m_p2 * (r + 2.0f * u * u));
float vnc = temp3 * (v - m_p1 * (r + 2.0f * v * v) - 2.0f * m_p2 * u * v);
cloud->points[i].x = unc * z;
cloud->points[i].y = vnc * z;
cloud->points[i].z = z;
}
}
// qDebug() << "[PointCloud] Block" << blockId << "processed successfully,"
// << m_totalPoints << "points";
if (m_denoiseEnabled.load(std::memory_order_relaxed)) {
cloud = applyDenoise(cloud);
}
emit pointCloudReady(cloud, blockId);
}

File diff suppressed because it is too large Load Diff

View File

@@ -140,6 +140,8 @@ private:
QPushButton *m_leftIRToggle;
QPushButton *m_rightIRToggle;
QPushButton *m_rgbToggle;
QPushButton *m_pointCloudColorToggle; // 点云颜色开关
QPushButton *m_pointCloudDenoiseToggle; // Point cloud denoise toggle
// 单目/双目模式切换按钮
QPushButton *m_monocularBtn;
@@ -156,6 +158,12 @@ private:
QPushButton *m_browseSavePathBtn;
class QComboBox *m_depthFormatCombo;
class QComboBox *m_pointCloudFormatCombo;
QSlider *m_denoiseSupportSlider;
QSpinBox *m_denoiseSupportSpinBox;
QSlider *m_denoiseTailSlider;
QSpinBox *m_denoiseTailSpinBox;
QSlider *m_denoiseBandSlider;
QSpinBox *m_denoiseBandSpinBox;
// 显示控件
QLabel *m_statusLabel;
@@ -207,8 +215,18 @@ private:
int m_totalRgbFrameCount;
double m_currentRgbFps;
// RGB解码处理标志(防止线程积压)
// 解码处理标志(防止线程积压导致闪烁
QAtomicInt m_rgbProcessing;
QAtomicInt m_leftIRProcessing;
QAtomicInt m_rightIRProcessing;
QAtomicInt m_pointCloudProcessing;
QAtomicInt m_pointCloudDropCounter;
bool m_leftIrDisplayRangeInited;
float m_leftIrDisplayMin;
float m_leftIrDisplayMax;
bool m_rightIrDisplayRangeInited;
float m_rightIrDisplayMin;
float m_rightIrDisplayMax;
int m_rgbSkipCounter; // RGB帧跳过计数器
// 相机启用状态标志(防止关闭后闪烁)

View File

@@ -1,5 +1,6 @@
#include "gui/PointCloudGLWidget.h"
#include <QDebug>
#include <QPushButton>
#include <cmath>
#include <cfloat>
@@ -9,16 +10,32 @@ PointCloudGLWidget::PointCloudGLWidget(QWidget *parent)
, m_vertexBuffer(nullptr)
, m_vao(nullptr)
, m_pointCount(0)
, m_fixedCenter(0.0f, 0.0f, 0.0f)
, m_centerInitialized(false)
, m_orthoSize(2000.0f) // 正交投影视野大小
, m_minZ(0.0f)
, m_maxZ(1000.0f)
, m_fov(60.0f) // 透视投影视场角
, m_rotationX(0.0f) // 从正面看0度
, m_rotationY(0.0f) // 不旋转Y轴
, m_translation(0.0f, 0.0f, 0.0f)
, m_cloudCenter(0.0f, 0.0f, 0.0f)
, m_viewDistance(1000.0f)
, m_panOffset(0.0f, 0.0f, 0.0f)
, m_zoom(1.0f) // 缩放因子
, m_leftButtonPressed(false)
, m_rightButtonPressed(false)
, m_firstFrame(true)
, m_colorMode(0) // 默认黑白模式
{
setMinimumSize(400, 400);
// 添加重置视角按钮
QPushButton *resetBtn = new QPushButton("重置", this);
resetBtn->setFixedSize(60, 30);
resetBtn->move(10, 10);
resetBtn->setStyleSheet(
"QPushButton { background-color: rgba(50, 50, 50, 180); color: white; border: 1px solid #555; border-radius: 4px; }"
"QPushButton:hover { background-color: rgba(70, 70, 70, 200); }"
"QPushButton:pressed { background-color: rgba(40, 40, 40, 220); }"
);
connect(resetBtn, &QPushButton::clicked, this, &PointCloudGLWidget::resetView);
}
PointCloudGLWidget::~PointCloudGLWidget()
@@ -42,7 +59,7 @@ void PointCloudGLWidget::initializeGL()
{
initializeOpenGLFunctions();
glClearColor(0.0f, 0.0f, 0.0f, 1.0f);
glClearColor(0.1f, 0.1f, 0.15f, 1.0f); // 深灰色背景
glEnable(GL_DEPTH_TEST);
glEnable(GL_PROGRAM_POINT_SIZE);
@@ -67,18 +84,39 @@ void PointCloudGLWidget::setupShaders()
#version 330 core
layout(location = 0) in vec3 position;
uniform mat4 mvp;
uniform float minZ;
uniform float maxZ;
out float depth;
void main() {
gl_Position = mvp * vec4(position, 1.0);
gl_PointSize = 1.0; // 减小点的大小
gl_PointSize = 1.0;
depth = (position.z - minZ) / (maxZ - minZ);
}
)";
// 片段着色器
// 片段着色器 - 支持黑白和彩色两种模式
const char *fragmentShaderSource = R"(
#version 330 core
in float depth;
uniform int colorMode;
out vec4 fragColor;
void main() {
fragColor = vec4(1.0, 1.0, 1.0, 1.0);
float d = clamp(depth, 0.0, 1.0);
if (colorMode == 0) {
fragColor = vec4(1.0, 1.0, 1.0, 1.0);
} else {
vec3 color;
if (d < 0.25) {
color = mix(vec3(0.0, 0.0, 1.0), vec3(0.0, 1.0, 1.0), d * 4.0);
} else if (d < 0.5) {
color = mix(vec3(0.0, 1.0, 1.0), vec3(0.0, 1.0, 0.0), (d - 0.25) * 4.0);
} else if (d < 0.75) {
color = mix(vec3(0.0, 1.0, 0.0), vec3(1.0, 1.0, 0.0), (d - 0.5) * 4.0);
} else {
color = mix(vec3(1.0, 1.0, 0.0), vec3(1.0, 0.0, 0.0), (d - 0.75) * 4.0);
}
fragColor = vec4(color, 1.0);
}
}
)";
@@ -99,11 +137,12 @@ void PointCloudGLWidget::resizeGL(int w, int h)
{
m_projection.setToIdentity();
// 使用正交投影代替透视投影,避免"喷射状"效果
// 使用正交投影,避免透视变形
float aspect = float(w) / float(h);
m_projection.ortho(-m_orthoSize * aspect, m_orthoSize * aspect,
-m_orthoSize, m_orthoSize,
-50000.0f, 50000.0f); // 近平面和远平面
float orthoSize = m_viewDistance * 0.5f / m_zoom;
m_projection.ortho(-orthoSize * aspect, orthoSize * aspect,
-orthoSize, orthoSize,
-50000.0f, 50000.0f);
}
void PointCloudGLWidget::paintGL()
@@ -114,18 +153,25 @@ void PointCloudGLWidget::paintGL()
return;
}
// 每帧重新计算正交投影矩阵确保使用最新的m_orthoSize
// 重新计算正交投影矩阵
m_projection.setToIdentity();
float aspect = float(width()) / float(height());
m_projection.ortho(-m_orthoSize * aspect, m_orthoSize * aspect,
-m_orthoSize, m_orthoSize,
float orthoSize = m_viewDistance * 0.5f / m_zoom;
m_projection.ortho(-orthoSize * aspect, orthoSize * aspect,
-orthoSize, orthoSize,
-50000.0f, 50000.0f);
// 设置view矩阵
// 设置view矩阵 - 轨道相机模式(围绕点云中心旋转)
m_view.setToIdentity();
// 1. 用户平移偏移
m_view.translate(m_panOffset);
// 2. 相机后退到观察距离
m_view.translate(0.0f, 0.0f, -m_viewDistance);
// 3. 应用旋转(围绕原点,即点云中心)
m_view.rotate(m_rotationX, 1.0f, 0.0f, 0.0f);
m_view.rotate(m_rotationY, 0.0f, 1.0f, 0.0f);
m_view.translate(m_translation);
// 4. 将点云中心移到原点
m_view.translate(-m_cloudCenter);
// 设置model矩阵
m_model.setToIdentity();
@@ -136,6 +182,9 @@ void PointCloudGLWidget::paintGL()
// 绑定shader和设置uniform
m_program->bind();
m_program->setUniformValue("mvp", mvp);
m_program->setUniformValue("minZ", m_minZ);
m_program->setUniformValue("maxZ", m_maxZ);
m_program->setUniformValue("colorMode", m_colorMode);
// 绑定VAO和绘制
m_vao->bind();
@@ -166,10 +215,10 @@ void PointCloudGLWidget::mouseMoveEvent(QMouseEvent *event)
m_rotationY += delta.x() * 0.5f;
update();
} else if (m_rightButtonPressed) {
// 右键:平移(根据正交投影视野大小调整平移速度)
float scale = m_orthoSize * 0.002f;
m_translation.setX(m_translation.x() + delta.x() * scale);
m_translation.setY(m_translation.y() - delta.y() * scale);
// 右键:平移(根据观察距离调整平移速度)
float scale = m_viewDistance * 0.002f;
m_panOffset.setX(m_panOffset.x() + delta.x() * scale);
m_panOffset.setY(m_panOffset.y() - delta.y() * scale);
update();
}
}
@@ -185,12 +234,12 @@ void PointCloudGLWidget::mouseReleaseEvent(QMouseEvent *event)
void PointCloudGLWidget::wheelEvent(QWheelEvent *event)
{
// 滚轮:缩放(调整正交投影视野大小
// 滚轮:缩放(调整zoom因子
float delta = event->angleDelta().y() / 120.0f;
m_orthoSize *= (1.0f - delta * 0.1f);
m_orthoSize = qMax(100.0f, qMin(m_orthoSize, 10000.0f)); // 范围:100-10000
m_zoom *= (1.0f + delta * 0.1f);
m_zoom = qMax(0.1f, qMin(m_zoom, 10.0f)); // 范围:0.1-10倍
update(); // 触发重绘paintGL会使用新的m_orthoSize
update();
}
void PointCloudGLWidget::updatePointCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud)
@@ -199,66 +248,87 @@ void PointCloudGLWidget::updatePointCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr cl
return;
}
// 过滤全零点并转换为顶点数组
// 过滤全零点并转换为顶点数组,同时计算包围盒
m_vertices.clear();
float minX = FLT_MAX, maxX = -FLT_MAX;
float minY = FLT_MAX, maxY = -FLT_MAX;
float minZ = FLT_MAX, maxZ = -FLT_MAX;
for (const auto& point : cloud->points) {
if (point.z > 0.01f) {
if (point.z > 0.01f) { // 过滤掉无效的零点
const float displayZ = -point.z; // Flip front/back axis for viewer convention.
m_vertices.push_back(point.x);
m_vertices.push_back(point.y);
m_vertices.push_back(point.z);
m_vertices.push_back(-point.y);
m_vertices.push_back(displayZ);
// 统计坐标范围
// 更新包围盒
if (point.x < minX) minX = point.x;
if (point.x > maxX) maxX = point.x;
if (point.y < minY) minY = point.y;
if (point.y > maxY) maxY = point.y;
if (point.z < minZ) minZ = point.z;
if (point.z > maxZ) maxZ = point.z;
if (displayZ < minZ) minZ = displayZ;
if (displayZ > maxZ) maxZ = displayZ;
}
}
m_pointCount = m_vertices.size() / 3;
// 计算点云中心并进行中心化处理
// 保存深度范围用于着色
if (m_pointCount > 0) {
m_minZ = minZ;
m_maxZ = maxZ;
}
// 只在首帧时自动调整相机位置,之后保持用户交互状态
if (m_pointCount > 0 && m_firstFrame) {
// 计算点云中心
float centerX = (minX + maxX) / 2.0f;
float centerY = (minY + maxY) / 2.0f;
float centerZ = (minZ + maxZ) / 2.0f;
// 第一帧:初始化固定中心点
if (!m_centerInitialized) {
m_fixedCenter = QVector3D(centerX, centerY, centerZ);
m_centerInitialized = true;
qDebug() << "[PointCloudGLWidget] Fixed center initialized:" << m_fixedCenter;
}
// 计算点云尺寸
float depthRange = maxZ - minZ;
float sizeX = maxX - minX;
float sizeY = maxY - minY;
float maxSize = std::max({sizeX, sizeY, depthRange});
// 使用固定的中心点进行中心化(避免抖动)
for (size_t i = 0; i < m_vertices.size(); i += 3) {
m_vertices[i] -= m_fixedCenter.x(); // X坐标
m_vertices[i + 1] -= m_fixedCenter.y(); // Y坐标
m_vertices[i + 2] -= m_fixedCenter.z(); // Z坐标
}
}
// 设置点云中心
m_cloudCenter = QVector3D(centerX, centerY, centerZ);
// 添加调试日志
static int updateCount = 0;
if (updateCount < 3 || updateCount % 100 == 0) {
// qDebug() << "[PointCloudGLWidget] Update" << updateCount << "- Points:" << m_pointCount
// << "Total cloud size:" << cloud->size();
// qDebug() << " X range:" << minX << "to" << maxX;
// qDebug() << " Y range:" << minY << "to" << maxY;
// qDebug() << " Z range:" << minZ << "to" << maxZ;
// 计算观察距离,让相机从外部观察点云
m_viewDistance = maxSize * 1.5f;
// 重置平移偏移和旋转角度
m_panOffset = QVector3D(0.0f, 0.0f, 0.0f);
m_rotationX = 0.0f;
m_rotationY = 0.0f;
// 设置缩放
m_zoom = 1.0f;
qDebug() << "[PointCloudGLWidget] 首帧自动居中 - 点云中心:" << centerX << centerY << centerZ
<< "观察距离:" << m_viewDistance;
m_firstFrame = false; // 标记首帧已处理
}
updateCount++;
updateBuffers();
update();
}
void PointCloudGLWidget::resetView()
{
// 重置所有视角参数到初始状态
m_rotationX = 0.0f;
m_rotationY = 0.0f;
m_panOffset = QVector3D(0.0f, 0.0f, 0.0f);
m_zoom = 1.0f;
m_firstFrame = true; // 标记为首帧,下次更新时会重新计算视角
update();
qDebug() << "[PointCloudGLWidget] 视角已重置";
}
void PointCloudGLWidget::updateBuffers()
{
if (m_vertices.empty() || !m_vao || !m_vertexBuffer) {

View File

@@ -54,3 +54,15 @@ void PointCloudWidget::updatePointCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr clou
// 更新OpenGL显示
m_glWidget->updatePointCloud(cloud);
}
void PointCloudWidget::setColorMode(bool enabled)
{
if (m_glWidget) {
m_glWidget->setColorMode(enabled);
}
}
bool PointCloudWidget::colorMode() const
{
return m_glWidget ? m_glWidget->colorMode() : false;
}

View File

@@ -1,12 +1,15 @@
#include <QApplication>
#include <QDateTime>
#include <QDir>
#include <QStandardPaths>
#include "gui/MainWindow.h"
#include "core/Logger.h"
// Custom message handler to redirect qDebug output to Logger
// Redirect Qt log output to file logger.
void messageHandler(QtMsgType type, const QMessageLogContext &context, const QString &msg)
{
Q_UNUSED(context);
Logger *logger = Logger::instance();
switch (type) {
@@ -30,29 +33,32 @@ int main(int argc, char *argv[])
{
QApplication app(argc, argv);
// 设置应用程序信息
app.setOrganizationName("D330Viewer");
app.setApplicationName("D330Viewer");
app.setApplicationVersion("0.2.0");
app.setOrganizationName("Viewer");
app.setApplicationName("Viewer");
app.setApplicationVersion("0.3.3");
// 初始化Logger在可执行文件同目录下
QString logPath = QCoreApplication::applicationDirPath() + "/d330viewer.log";
// Prefer LocalAppData so MSI installs under Program Files can always write logs.
QString logDir = QStandardPaths::writableLocation(QStandardPaths::AppLocalDataLocation);
if (logDir.isEmpty()) {
logDir = QCoreApplication::applicationDirPath();
}
QDir().mkpath(logDir);
const QString logPath = QDir(logDir).filePath("viewer.log");
Logger::instance()->setLogFile(logPath);
Logger::instance()->setMaxLines(10000); // 保留最新10000行
Logger::instance()->setMaxLines(10000);
// 安装消息处理器
qInstallMessageHandler(messageHandler);
qDebug() << "D330Viewer started";
qDebug() << "Viewer started";
qDebug() << "Log file:" << logPath;
// 创建并显示主窗口
MainWindow mainWindow;
mainWindow.show();
int result = app.exec();
const int result = app.exec();
qDebug() << "D330Viewer exiting";
qDebug() << "Viewer exiting";
return result;
}