螺栓的更新算法
This commit is contained in:
杰仔
parent
00de98b6be
commit
d3e6b4d0f3
@ -39,6 +39,7 @@ public:
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void SetStatusReceiver(IYDroneScrewCtrlStatus* receiver) { m_pReceiver = receiver; }
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void ApplyConfig(const DroneScrewCtrlConfigResult& cfg);
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void UpdateDisplayOptions(const DroneScrewDisplayOption& options);
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int InitApp();
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void DeinitApp();
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@ -181,6 +181,11 @@ void DroneScrewCtrlPresenter::ApplyConfig(const DroneScrewCtrlConfigResult& cfg)
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}
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}
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void DroneScrewCtrlPresenter::UpdateDisplayOptions(const DroneScrewDisplayOption& options)
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{
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m_cfg.display = options;
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}
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int DroneScrewCtrlPresenter::InitApp()
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{
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if (m_bRunning.load()) return 0;
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@ -3,8 +3,8 @@
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#define DRONESCREWCTRL_APP_NAME "无人机螺杆控制端"
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#define DRONESCREWCTRL_VERSION_STRING "1.0.0"
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#define DRONESCREWCTRL_BUILD_STRING "2"
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#define DRONESCREWCTRL_FULL_VERSION_STRING "V1.0.0_2"
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#define DRONESCREWCTRL_BUILD_STRING "3"
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#define DRONESCREWCTRL_FULL_VERSION_STRING "V1.0.0_3"
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inline const char* GetDroneScrewCtrlFullVersion() { return DRONESCREWCTRL_FULL_VERSION_STRING; }
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@ -1,8 +1,11 @@
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#include "dialogalgoarg.h"
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#include "ui_dialogalgoarg.h"
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#include <QCheckBox>
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#include <QDoubleValidator>
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#include <QFormLayout>
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#include <QIntValidator>
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#include <QLabel>
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DialogAlgoArg::DialogAlgoArg(QWidget* parent)
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: QDialog(parent)
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@ -17,6 +20,7 @@ DialogAlgoArg::DialogAlgoArg(QWidget* parent)
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ui->edit_width->setValidator(new QIntValidator(0, 8192, this));
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ui->edit_height->setValidator(new QIntValidator(0, 8192, this));
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ui->edit_modelType->setValidator(new QIntValidator(0, 10, this));
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createDisplayRows();
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}
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DialogAlgoArg::~DialogAlgoArg()
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@ -35,6 +39,17 @@ DroneScrewAlgoUiParams DialogAlgoArg::GetParams() const
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return m_params;
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}
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void DialogAlgoArg::SetDisplayOptions(const DroneScrewDisplayOption& options)
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{
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m_displayOptions = options;
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loadDisplayToUi(options);
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}
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DroneScrewDisplayOption DialogAlgoArg::GetDisplayOptions() const
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{
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return m_displayOptions;
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}
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void DialogAlgoArg::loadToUi(const DroneScrewAlgoUiParams& p)
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{
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if (ui->edit_score) ui->edit_score->setText(QString::number(p.scoreThreshold, 'f', 2));
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@ -57,9 +72,39 @@ DroneScrewAlgoUiParams DialogAlgoArg::collectFromUi() const
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return p;
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}
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void DialogAlgoArg::createDisplayRows()
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{
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if (!ui->fl_main)
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return;
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m_checkDrawBoxes = new QCheckBox(QStringLiteral("显示"), this);
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m_checkDrawBoxes->setObjectName(QStringLiteral("check_drawBoxes"));
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m_checkDrawBoxes->setMinimumHeight(40);
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m_checkDrawBoxes->setStyleSheet(QStringLiteral(
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"QCheckBox { color: rgb(239, 241, 245); font-size: 18px; background: none; }"));
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ui->fl_main->addRow(new QLabel(QStringLiteral("显示结果框"), this),
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m_checkDrawBoxes);
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}
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void DialogAlgoArg::loadDisplayToUi(const DroneScrewDisplayOption& options)
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{
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if (m_checkDrawBoxes)
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m_checkDrawBoxes->setChecked(options.drawBoxes);
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}
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DroneScrewDisplayOption DialogAlgoArg::collectDisplayFromUi() const
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{
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DroneScrewDisplayOption options = m_displayOptions;
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if (m_checkDrawBoxes)
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options.drawBoxes = m_checkDrawBoxes->isChecked();
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return options;
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}
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void DialogAlgoArg::on_btn_ok_clicked()
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{
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m_params = collectFromUi();
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m_displayOptions = collectDisplayFromUi();
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accept();
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}
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@ -71,10 +116,14 @@ void DialogAlgoArg::on_btn_cancel_clicked()
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void DialogAlgoArg::on_btn_apply_clicked()
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{
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m_params = collectFromUi();
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m_displayOptions = collectDisplayFromUi();
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}
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void DialogAlgoArg::on_btn_reset_clicked()
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{
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DroneScrewAlgoUiParams p; // 默认值
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loadToUi(p);
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DroneScrewDisplayOption options = m_displayOptions;
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options.drawBoxes = true;
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loadDisplayToUi(options);
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}
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@ -5,6 +5,7 @@
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#include "IVrConfig.h"
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namespace Ui { class DialogAlgoArg; }
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class QCheckBox;
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class DialogAlgoArg : public QDialog
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{
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@ -16,6 +17,8 @@ public:
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void SetParams(const DroneScrewAlgoUiParams& params);
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DroneScrewAlgoUiParams GetParams() const;
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void SetDisplayOptions(const DroneScrewDisplayOption& options);
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DroneScrewDisplayOption GetDisplayOptions() const;
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private slots:
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void on_btn_ok_clicked();
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@ -26,10 +29,15 @@ private slots:
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private:
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void loadToUi(const DroneScrewAlgoUiParams& p);
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DroneScrewAlgoUiParams collectFromUi() const;
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void createDisplayRows();
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void loadDisplayToUi(const DroneScrewDisplayOption& options);
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DroneScrewDisplayOption collectDisplayFromUi() const;
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private:
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Ui::DialogAlgoArg* ui{nullptr};
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DroneScrewAlgoUiParams m_params;
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DroneScrewDisplayOption m_displayOptions;
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QCheckBox* m_checkDrawBoxes{nullptr};
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};
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#endif // DRONESCREWCTRL_DIALOG_ALGOARG_H
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@ -671,12 +671,16 @@ void MainWindow::on_btn_algo_config_clicked()
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{
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dlg.SetParams(cfg.algo);
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}
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dlg.SetDisplayOptions(cfg.display);
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if (dlg.exec() == QDialog::Accepted)
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{
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cfg.algo = dlg.GetParams();
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cfg.display = dlg.GetDisplayOptions();
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ConfigManager::Instance().SetConfig(cfg);
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ConfigManager::Instance().Save();
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m_maxResultItems = cfg.display.maxResultListItems;
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if (m_pPresenter) m_pPresenter->UpdateDisplayOptions(cfg.display);
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if (m_pPresenter) m_pPresenter->PushAlgoParams(cfg.algo);
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appendLog(QStringLiteral("已应用算法参数"));
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}
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@ -9,9 +9,9 @@ namespace
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void setResultTextStyle(Ui::ResultItem* ui)
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{
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const QString titleStyle =
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QStringLiteral("color: rgb(239, 241, 245); background-color: rgb(37, 38, 42); font-size: 16px; font-weight: 600;");
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QStringLiteral("color: rgb(239, 241, 245); background-color: rgb(37, 38, 42); font-size: 20px; font-weight: 600;");
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const QString valueStyle =
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QStringLiteral("color: rgb(255, 255, 255); background-color: rgb(37, 38, 42); font-size: 20px; font-weight: 700;");
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QStringLiteral("color: rgb(255, 255, 255); background-color: rgb(37, 38, 42); font-size: 26px; font-weight: 700;");
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if (ui->lb_id_t) ui->lb_id_t->setStyleSheet(titleStyle);
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if (ui->lb_time_t) ui->lb_time_t->setStyleSheet(titleStyle);
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@ -34,9 +34,7 @@ QString failedText(const CtrlDetectionFrame& frame)
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QString oneDistanceText(const CtrlDetectionDistance& d)
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{
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const double meters = d.distanceMm / 1000.0;
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if (d.fromId < 0)
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return QStringLiteral("整体距离: %1m").arg(meters, 0, 'f', 3);
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return QStringLiteral("目标%1距离: %2m").arg(d.fromId + 1).arg(meters, 0, 'f', 3);
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return QStringLiteral("%1m").arg(meters, 0, 'f', 3);
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}
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QString distanceText(const CtrlDetectionFrame& frame, int targetIndex)
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@ -58,7 +56,7 @@ QString distanceIndexText(const CtrlDetectionFrame& frame, int targetIndex)
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if (targetIndex >= 0 && targetIndex < total)
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{
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const CtrlDetectionDistance& d = frame.distances[static_cast<size_t>(targetIndex)];
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return QString::number(d.toId);
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return QString::number(d.toId + 1);
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}
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return QStringLiteral("-");
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}
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@ -113,7 +111,14 @@ void ResultItem::setResultData(int targetIndex,
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{
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const bool precisionMode = (mode == DisplayMode::Precision);
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setResultTextStyle(ui);
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setMinimumHeight(precisionMode ? 92 : 82);
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setMinimumHeight(precisionMode ? 104 : 108);
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if (ui->lb_id_t)
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ui->lb_id_t->setText(QStringLiteral("ID"));
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if (ui->lb_status_t)
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ui->lb_status_t->setText(mode == DisplayMode::Distance
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? QStringLiteral("距离")
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: QStringLiteral("状态"));
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if (ui->label_id)
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{
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@ -15,9 +15,13 @@
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#include <algorithm>
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#include <cmath>
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#include <cstring>
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#include <exception>
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#include <limits>
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#include <sstream>
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#ifdef DRONESCREW_STEREO_BOLT_DIRECT_LINK
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#include <opencv2/calib3d.hpp>
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#include <opencv2/core.hpp>
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namespace
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{
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@ -28,6 +32,65 @@ constexpr int kDefaultYoloImgSize = 960;
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constexpr int kDefaultExpectedBoltCount = 8;
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constexpr int kMaxRangeBolts = 64;
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cv::Mat mat64(int rows, int cols, const double* values)
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{
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cv::Mat m(rows, cols, CV_64F);
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std::memcpy(m.ptr<double>(0), values, sizeof(double) * rows * cols);
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return m;
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}
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int roiSampleCount(double span)
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{
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if (span <= 1.0)
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return 2;
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return std::max(3, std::min(17, static_cast<int>(std::ceil(span / 64.0)) + 1));
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}
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bool sampleMapBilinear(const std::vector<float>& mapX,
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const std::vector<float>& mapY,
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int mapWidth,
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int mapHeight,
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double rectX,
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double rectY,
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double& rawX,
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double& rawY)
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{
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if (mapWidth <= 0 || mapHeight <= 0 ||
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mapX.size() != static_cast<size_t>(mapWidth) * static_cast<size_t>(mapHeight) ||
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mapY.size() != mapX.size())
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{
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return false;
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}
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rectX = std::max(0.0, std::min(rectX, static_cast<double>(mapWidth - 1)));
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rectY = std::max(0.0, std::min(rectY, static_cast<double>(mapHeight - 1)));
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const int x0 = static_cast<int>(std::floor(rectX));
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const int y0 = static_cast<int>(std::floor(rectY));
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const int x1 = std::min(x0 + 1, mapWidth - 1);
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const int y1 = std::min(y0 + 1, mapHeight - 1);
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const double tx = rectX - x0;
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const double ty = rectY - y0;
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const size_t i00 = static_cast<size_t>(y0) * mapWidth + x0;
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const size_t i10 = static_cast<size_t>(y0) * mapWidth + x1;
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const size_t i01 = static_cast<size_t>(y1) * mapWidth + x0;
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const size_t i11 = static_cast<size_t>(y1) * mapWidth + x1;
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const double xTop = static_cast<double>(mapX[i00]) * (1.0 - tx) +
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static_cast<double>(mapX[i10]) * tx;
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const double xBottom = static_cast<double>(mapX[i01]) * (1.0 - tx) +
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static_cast<double>(mapX[i11]) * tx;
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const double yTop = static_cast<double>(mapY[i00]) * (1.0 - tx) +
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static_cast<double>(mapY[i10]) * tx;
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const double yBottom = static_cast<double>(mapY[i01]) * (1.0 - tx) +
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static_cast<double>(mapY[i11]) * tx;
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rawX = xTop * (1.0 - ty) + xBottom * ty;
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rawY = yTop * (1.0 - ty) + yBottom * ty;
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return std::isfinite(rawX) && std::isfinite(rawY);
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}
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void appendUniqueDir(QStringList& dirs, const QString& dir)
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{
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if (dir.isEmpty())
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@ -325,18 +388,6 @@ bool validateInput(const DroneScrewInputImage& leftImage,
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return true;
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}
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void appendRoiBox(const StereoBoltModuleRoiC& roi, DroneScrewResult& result)
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{
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DroneScrewBox box;
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box.classId = roi.class_id;
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box.score = static_cast<float>(roi.score);
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box.x = roi.x;
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box.y = roi.y;
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box.width = roi.width;
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box.height = roi.height;
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result.boxes.push_back(box);
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}
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void appendDistance(const StereoBoltModuleDistanceC& distance, DroneScrewResult& result)
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{
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DroneScrewDistance d;
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@ -452,6 +503,203 @@ DroneScrewAlgoStub::~DroneScrewAlgoStub()
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UnInit();
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}
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bool DroneScrewAlgoStub::buildRectifiedLeftToRawMap(const StereoBoltCalibC& calib,
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double rectAlpha,
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std::string& error)
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{
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m_rectMapWidth = 0;
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m_rectMapHeight = 0;
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m_leftRectToRawX.clear();
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m_leftRectToRawY.clear();
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if (calib.image_width <= 0 || calib.image_height <= 0)
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{
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error = "invalid calibration image size for rectified-to-raw map";
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return false;
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}
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if (!std::isfinite(rectAlpha))
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{
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error = "invalid rectification alpha for rectified-to-raw map";
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return false;
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}
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try
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{
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const cv::Size imageSize(calib.image_width, calib.image_height);
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const cv::Mat K1 = mat64(3, 3, calib.left_K);
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const cv::Mat D1 = mat64(1, 5, calib.left_D);
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const cv::Mat K2 = mat64(3, 3, calib.right_K);
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const cv::Mat D2 = mat64(1, 5, calib.right_D);
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const cv::Mat R = mat64(3, 3, calib.R);
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const cv::Mat T = mat64(3, 1, calib.T);
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cv::Mat R1;
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cv::Mat R2;
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cv::Mat P1;
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cv::Mat P2;
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cv::Mat Q;
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cv::Rect validRoi1;
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cv::Rect validRoi2;
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cv::stereoRectify(K1, D1, K2, D2, imageSize, R, T,
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R1, R2, P1, P2, Q,
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cv::CALIB_ZERO_DISPARITY,
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rectAlpha,
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imageSize,
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&validRoi1,
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&validRoi2);
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cv::Mat mapX;
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cv::Mat mapY;
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cv::initUndistortRectifyMap(K1, D1, R1, P1, imageSize,
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CV_32FC1, mapX, mapY);
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if (mapX.empty() || mapY.empty() ||
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mapX.cols != imageSize.width || mapX.rows != imageSize.height ||
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mapY.cols != imageSize.width || mapY.rows != imageSize.height)
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{
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error = "OpenCV returned invalid rectified-to-raw map";
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return false;
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}
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const size_t total = static_cast<size_t>(imageSize.width) *
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static_cast<size_t>(imageSize.height);
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m_leftRectToRawX.resize(total);
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m_leftRectToRawY.resize(total);
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for (int y = 0; y < imageSize.height; ++y)
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{
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const float* srcX = mapX.ptr<float>(y);
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const float* srcY = mapY.ptr<float>(y);
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const size_t offset = static_cast<size_t>(y) * imageSize.width;
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std::copy(srcX, srcX + imageSize.width, m_leftRectToRawX.begin() + offset);
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std::copy(srcY, srcY + imageSize.width, m_leftRectToRawY.begin() + offset);
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}
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m_calib = calib;
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m_rectAlpha = rectAlpha;
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m_rectMapWidth = imageSize.width;
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m_rectMapHeight = imageSize.height;
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return true;
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}
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catch (const cv::Exception& e)
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{
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error = std::string("OpenCV rectified-to-raw map failed: ") + e.what();
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}
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catch (const std::exception& e)
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{
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error = std::string("rectified-to-raw map failed: ") + e.what();
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}
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catch (...)
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{
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error = "rectified-to-raw map failed: unknown exception";
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}
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m_rectMapWidth = 0;
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m_rectMapHeight = 0;
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m_leftRectToRawX.clear();
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m_leftRectToRawY.clear();
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return false;
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}
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bool DroneScrewAlgoStub::mapRectifiedLeftRoi(const StereoBoltModuleRoiC& roi,
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int rawWidth,
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int rawHeight,
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DroneScrewBox& box) const
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{
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if (roi.width <= 0 || roi.height <= 0)
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return false;
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if (m_rectMapWidth <= 0 || m_rectMapHeight <= 0 ||
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m_leftRectToRawX.empty() || m_leftRectToRawY.empty())
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{
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return false;
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}
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||||
|
||||
const int dstWidth = rawWidth > 0 ? rawWidth : m_rectMapWidth;
|
||||
const int dstHeight = rawHeight > 0 ? rawHeight : m_rectMapHeight;
|
||||
if (dstWidth <= 0 || dstHeight <= 0)
|
||||
return false;
|
||||
|
||||
const double rectLeft = static_cast<double>(roi.x);
|
||||
const double rectTop = static_cast<double>(roi.y);
|
||||
const double rectRight = static_cast<double>(roi.x) + static_cast<double>(roi.width) - 1.0;
|
||||
const double rectBottom = static_cast<double>(roi.y) + static_cast<double>(roi.height) - 1.0;
|
||||
if (rectRight < 0.0 || rectBottom < 0.0 ||
|
||||
rectLeft > static_cast<double>(m_rectMapWidth - 1) ||
|
||||
rectTop > static_cast<double>(m_rectMapHeight - 1))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
double minRawX = std::numeric_limits<double>::infinity();
|
||||
double minRawY = std::numeric_limits<double>::infinity();
|
||||
double maxRawX = -std::numeric_limits<double>::infinity();
|
||||
double maxRawY = -std::numeric_limits<double>::infinity();
|
||||
bool hasSample = false;
|
||||
|
||||
const int samplesX = roiSampleCount(rectRight - rectLeft);
|
||||
const int samplesY = roiSampleCount(rectBottom - rectTop);
|
||||
for (int sy = 0; sy < samplesY; ++sy)
|
||||
{
|
||||
const double ty = (samplesY <= 1) ? 0.0 : static_cast<double>(sy) / (samplesY - 1);
|
||||
const double rectY = rectTop + (rectBottom - rectTop) * ty;
|
||||
for (int sx = 0; sx < samplesX; ++sx)
|
||||
{
|
||||
const double tx = (samplesX <= 1) ? 0.0 : static_cast<double>(sx) / (samplesX - 1);
|
||||
const double rectX = rectLeft + (rectRight - rectLeft) * tx;
|
||||
|
||||
double rawX = 0.0;
|
||||
double rawY = 0.0;
|
||||
if (!sampleMapBilinear(m_leftRectToRawX, m_leftRectToRawY,
|
||||
m_rectMapWidth, m_rectMapHeight,
|
||||
rectX, rectY, rawX, rawY))
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
minRawX = std::min(minRawX, rawX);
|
||||
minRawY = std::min(minRawY, rawY);
|
||||
maxRawX = std::max(maxRawX, rawX);
|
||||
maxRawY = std::max(maxRawY, rawY);
|
||||
hasSample = true;
|
||||
}
|
||||
}
|
||||
|
||||
if (!hasSample)
|
||||
return false;
|
||||
if (maxRawX < 0.0 || maxRawY < 0.0 ||
|
||||
minRawX > static_cast<double>(dstWidth - 1) ||
|
||||
minRawY > static_cast<double>(dstHeight - 1))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
const int left = std::max(0, std::min(dstWidth - 1,
|
||||
static_cast<int>(std::floor(minRawX))));
|
||||
const int top = std::max(0, std::min(dstHeight - 1,
|
||||
static_cast<int>(std::floor(minRawY))));
|
||||
const int right = std::max(0, std::min(dstWidth - 1,
|
||||
static_cast<int>(std::ceil(maxRawX))));
|
||||
const int bottom = std::max(0, std::min(dstHeight - 1,
|
||||
static_cast<int>(std::ceil(maxRawY))));
|
||||
if (right < left || bottom < top)
|
||||
return false;
|
||||
|
||||
box.classId = roi.class_id;
|
||||
box.score = static_cast<float>(roi.score);
|
||||
box.x = left;
|
||||
box.y = top;
|
||||
box.width = right - left + 1;
|
||||
box.height = bottom - top + 1;
|
||||
return true;
|
||||
}
|
||||
|
||||
void DroneScrewAlgoStub::appendRoiBox(const StereoBoltModuleRoiC& roi,
|
||||
DroneScrewResult& result) const
|
||||
{
|
||||
DroneScrewBox box;
|
||||
if (mapRectifiedLeftRoi(roi, result.imageWidth, result.imageHeight, box))
|
||||
result.boxes.push_back(box);
|
||||
}
|
||||
|
||||
int DroneScrewAlgoStub::Init(const DroneScrewAlgoParams& params)
|
||||
{
|
||||
std::lock_guard<std::mutex> lk(m_mutex);
|
||||
@ -464,6 +712,10 @@ int DroneScrewAlgoStub::Init(const DroneScrewAlgoParams& params)
|
||||
sb_destroy(m_ctx);
|
||||
m_ctx = nullptr;
|
||||
}
|
||||
m_rectMapWidth = 0;
|
||||
m_rectMapHeight = 0;
|
||||
m_leftRectToRawX.clear();
|
||||
m_leftRectToRawY.clear();
|
||||
|
||||
QStringList configBases;
|
||||
appendUniqueDir(configBases, QDir::currentPath());
|
||||
@ -536,10 +788,22 @@ int DroneScrewAlgoStub::Init(const DroneScrewAlgoParams& params)
|
||||
algoParams.rng_lrc_trusted_mm =
|
||||
yamlDouble(yaml, "ranging.lrc_trusted_mm", algoParams.rng_lrc_trusted_mm);
|
||||
|
||||
if (!buildRectifiedLeftToRawMap(calib, algoParams.rect_alpha, loadError))
|
||||
{
|
||||
m_initError = std::string("stereo_bolt build bbox rectified-to-raw map failed calib=") +
|
||||
calibPath.toStdString() + " err=" + loadError;
|
||||
LOG_ERROR("[ALGO] %s\n", m_initError.c_str());
|
||||
return ERR_CODE(DEV_OPEN_ERR);
|
||||
}
|
||||
|
||||
m_ctx = sb_create_ex(&calib, &model, &algoParams);
|
||||
|
||||
if (!m_ctx)
|
||||
{
|
||||
m_rectMapWidth = 0;
|
||||
m_rectMapHeight = 0;
|
||||
m_leftRectToRawX.clear();
|
||||
m_leftRectToRawY.clear();
|
||||
const char* err = sb_last_error(nullptr);
|
||||
m_initError = std::string("stereo_bolt create_ex failed config=") +
|
||||
configPath.toStdString() +
|
||||
@ -578,6 +842,10 @@ int DroneScrewAlgoStub::UnInit()
|
||||
sb_destroy(m_ctx);
|
||||
m_ctx = nullptr;
|
||||
}
|
||||
m_rectMapWidth = 0;
|
||||
m_rectMapHeight = 0;
|
||||
m_leftRectToRawX.clear();
|
||||
m_leftRectToRawY.clear();
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
@ -37,12 +37,32 @@ public:
|
||||
std::string GetVersion() const override;
|
||||
|
||||
private:
|
||||
#ifdef DRONESCREW_STEREO_BOLT_DIRECT_LINK
|
||||
bool buildRectifiedLeftToRawMap(const StereoBoltCalibC& calib,
|
||||
double rectAlpha,
|
||||
std::string& error);
|
||||
bool mapRectifiedLeftRoi(const StereoBoltModuleRoiC& roi,
|
||||
int rawWidth,
|
||||
int rawHeight,
|
||||
DroneScrewBox& box) const;
|
||||
void appendRoiBox(const StereoBoltModuleRoiC& roi,
|
||||
DroneScrewResult& result) const;
|
||||
#endif
|
||||
|
||||
DroneScrewAlgoParams m_params;
|
||||
StereoBoltCtx* m_ctx{nullptr};
|
||||
std::string m_configPath;
|
||||
std::string m_calibPath;
|
||||
std::string m_modelPath;
|
||||
std::string m_initError;
|
||||
#ifdef DRONESCREW_STEREO_BOLT_DIRECT_LINK
|
||||
StereoBoltCalibC m_calib{};
|
||||
double m_rectAlpha{1.0};
|
||||
int m_rectMapWidth{0};
|
||||
int m_rectMapHeight{0};
|
||||
std::vector<float> m_leftRectToRawX;
|
||||
std::vector<float> m_leftRectToRawY;
|
||||
#endif
|
||||
mutable std::mutex m_mutex;
|
||||
std::atomic<bool> m_bInited{false};
|
||||
};
|
||||
|
||||
@ -103,7 +103,7 @@ win32:CONFIG(debug, debug|release) {
|
||||
OPENCV450_LIB_DIR = $$PWD/../../../SDK/OpenCV450/Arm/aarch64/lib
|
||||
INCLUDEPATH += $$PWD/../../../SDK/OpenCV450/Arm/aarch64/include/opencv4
|
||||
LIBS += -L$${OPENCV450_LIB_DIR}
|
||||
LIBS += -lopencv_imgcodecs -lopencv_imgproc -lopencv_core
|
||||
LIBS += -lopencv_imgcodecs -lopencv_imgproc -lopencv_calib3d -lopencv_core
|
||||
QMAKE_LFLAGS += -Wl,-rpath-link,$${OPENCV450_LIB_DIR}
|
||||
|
||||
# MVS SDK
|
||||
|
||||
@ -67,7 +67,9 @@ constexpr int64_t kDistanceDecimationVertical = 4;
|
||||
constexpr int kDetectPipelinePrecision = 0;
|
||||
constexpr int kDetectPipelineDistance = 1;
|
||||
constexpr const char* kImageSaveRootDir = "/home/cat";
|
||||
constexpr size_t kMaxImageSaveQueueDepth = 16;
|
||||
constexpr size_t kMaxImageSaveQueueDepth = 100;
|
||||
constexpr size_t kImageSaveWorkerCount = 4;
|
||||
constexpr int kDistanceImageSaveStride = 3;
|
||||
|
||||
const char* mvsSdkErrorName(int code)
|
||||
{
|
||||
@ -1812,9 +1814,9 @@ int DroneScrewServerPresenter::stopDetectionWork()
|
||||
|
||||
stopGpioTriggerLoop();
|
||||
m_bThreadExit = true;
|
||||
stopImageSaveThread();
|
||||
if (m_detectThread.joinable())
|
||||
m_detectThread.join();
|
||||
stopImageSaveThread();
|
||||
m_bIsDetecting = false;
|
||||
m_detectPipelineMode = kDetectPipelinePrecision;
|
||||
m_activeTriggerFps = static_cast<int>(kPrecisionFrameRate);
|
||||
@ -1933,9 +1935,9 @@ int DroneScrewServerPresenter::stopLiveStream()
|
||||
m_bRtspStarted = false;
|
||||
stopGpioTriggerLoop();
|
||||
m_bThreadExit = true;
|
||||
stopImageSaveThread();
|
||||
if (m_detectThread.joinable())
|
||||
m_detectThread.join();
|
||||
stopImageSaveThread();
|
||||
m_bIsDetecting = false;
|
||||
m_detectPipelineMode = kDetectPipelinePrecision;
|
||||
m_activeTriggerFps = static_cast<int>(kPrecisionFrameRate);
|
||||
@ -2356,28 +2358,51 @@ void DroneScrewServerPresenter::startImageSaveThread(const QString& modeName)
|
||||
m_imageSaveThreadExit = false;
|
||||
}
|
||||
|
||||
m_imageSaveThread = std::thread(&DroneScrewServerPresenter::imageSaveThreadFunc, this);
|
||||
LOG_INFO("[SAVE] image save thread started mode=%s dir=%s\n",
|
||||
modeName.toStdString().c_str(), sessionDir.toStdString().c_str());
|
||||
m_imageSaveThreads.reserve(kImageSaveWorkerCount);
|
||||
for (size_t i = 0; i < kImageSaveWorkerCount; ++i)
|
||||
{
|
||||
m_imageSaveThreads.emplace_back(&DroneScrewServerPresenter::imageSaveThreadFunc,
|
||||
this,
|
||||
static_cast<int>(i));
|
||||
}
|
||||
LOG_INFO("[SAVE] image save workers started count=%zu mode=%s dir=%s\n",
|
||||
m_imageSaveThreads.size(),
|
||||
modeName.toStdString().c_str(),
|
||||
sessionDir.toStdString().c_str());
|
||||
}
|
||||
|
||||
void DroneScrewServerPresenter::stopImageSaveThread()
|
||||
{
|
||||
const bool shouldJoin = m_imageSaveThread.joinable();
|
||||
const bool shouldJoin = !m_imageSaveThreads.empty();
|
||||
size_t droppedPending = 0;
|
||||
{
|
||||
std::lock_guard<std::mutex> lk(m_imageSaveMutex);
|
||||
m_imageSaveQueue.clear();
|
||||
if (!shouldJoin)
|
||||
{
|
||||
m_imageSaveQueue.clear();
|
||||
m_imageSaveSessionDir.clear();
|
||||
m_imageSaveThreadExit = false;
|
||||
return;
|
||||
}
|
||||
droppedPending = m_imageSaveQueue.size();
|
||||
if (droppedPending > 0)
|
||||
m_imageSaveQueue.clear();
|
||||
m_imageSaveThreadExit = true;
|
||||
}
|
||||
|
||||
if (droppedPending > 0)
|
||||
{
|
||||
LOG_WARN("[SAVE] stop requested, drop pending save jobs=%zu\n",
|
||||
droppedPending);
|
||||
}
|
||||
|
||||
m_imageSaveCv.notify_all();
|
||||
m_imageSaveThread.join();
|
||||
for (std::thread& worker : m_imageSaveThreads)
|
||||
{
|
||||
if (worker.joinable())
|
||||
worker.join();
|
||||
}
|
||||
m_imageSaveThreads.clear();
|
||||
|
||||
{
|
||||
std::lock_guard<std::mutex> lk(m_imageSaveMutex);
|
||||
@ -2457,9 +2482,9 @@ void DroneScrewServerPresenter::enqueueImageSave(const MvsImageData& leftImg,
|
||||
m_imageSaveCv.notify_one();
|
||||
}
|
||||
|
||||
void DroneScrewServerPresenter::imageSaveThreadFunc()
|
||||
void DroneScrewServerPresenter::imageSaveThreadFunc(int workerIndex)
|
||||
{
|
||||
LOG_DEBUG("[SAVE] worker entered\n");
|
||||
LOG_DEBUG("[SAVE] worker #%d entered\n", workerIndex);
|
||||
for (;;)
|
||||
{
|
||||
ImageSaveJob job;
|
||||
@ -2470,10 +2495,15 @@ void DroneScrewServerPresenter::imageSaveThreadFunc()
|
||||
});
|
||||
|
||||
if (m_imageSaveThreadExit.load())
|
||||
{
|
||||
m_imageSaveQueue.clear();
|
||||
break;
|
||||
}
|
||||
|
||||
if (m_imageSaveQueue.empty())
|
||||
{
|
||||
continue;
|
||||
}
|
||||
|
||||
job = std::move(m_imageSaveQueue.front());
|
||||
m_imageSaveQueue.pop_front();
|
||||
@ -2502,9 +2532,11 @@ void DroneScrewServerPresenter::imageSaveThreadFunc()
|
||||
};
|
||||
|
||||
saveMono8(job.left, QStringLiteral("left"));
|
||||
if (m_imageSaveThreadExit.load())
|
||||
break;
|
||||
saveMono8(job.right, QStringLiteral("right"));
|
||||
}
|
||||
LOG_DEBUG("[SAVE] worker stopped\n");
|
||||
LOG_DEBUG("[SAVE] worker #%d stopped\n", workerIndex);
|
||||
}
|
||||
|
||||
DroneScrewResult DroneScrewServerPresenter::runSingleDetection()
|
||||
@ -2800,6 +2832,7 @@ void DroneScrewServerPresenter::detectThreadFunc()
|
||||
}
|
||||
|
||||
int frameCnt = 0;
|
||||
unsigned long long savedFrameCnt = 0;
|
||||
bool haveProcessedFrame = false;
|
||||
unsigned long long lastProcessedLeftFrameId = 0;
|
||||
unsigned long long lastProcessedRightFrameId = 0;
|
||||
@ -2875,7 +2908,12 @@ void DroneScrewServerPresenter::detectThreadFunc()
|
||||
haveProcessedFrame = true;
|
||||
lastProcessedLeftFrameId = leftImg.frameID;
|
||||
lastProcessedRightFrameId = rightImg.frameID;
|
||||
enqueueImageSave(leftImg, rightImg, static_cast<unsigned long long>(frameCnt + 1));
|
||||
const bool distanceSaveMode =
|
||||
(m_detectPipelineMode.load() == kDetectPipelineDistance);
|
||||
const bool shouldSaveFrame =
|
||||
!distanceSaveMode || ((frameCnt % kDistanceImageSaveStride) == 0);
|
||||
if (shouldSaveFrame)
|
||||
enqueueImageSave(leftImg, rightImg, ++savedFrameCnt);
|
||||
|
||||
// Publish the display frame before detection work. detectMode only controls raw transport.
|
||||
if (m_bRawPubEnabled.load())
|
||||
|
||||
@ -236,7 +236,7 @@ private:
|
||||
unsigned int timeoutMs);
|
||||
void startImageSaveThread(const QString& modeName);
|
||||
void stopImageSaveThread();
|
||||
void imageSaveThreadFunc();
|
||||
void imageSaveThreadFunc(int workerIndex);
|
||||
void enqueueImageSave(const MvsImageData& leftImg,
|
||||
const MvsImageData& rightImg,
|
||||
unsigned long long index);
|
||||
@ -344,7 +344,7 @@ private:
|
||||
bool m_bRightImageReady{false};
|
||||
|
||||
// 异步图像保存
|
||||
std::thread m_imageSaveThread;
|
||||
std::vector<std::thread> m_imageSaveThreads;
|
||||
std::atomic<bool> m_imageSaveThreadExit{false};
|
||||
std::mutex m_imageSaveMutex;
|
||||
std::condition_variable m_imageSaveCv;
|
||||
|
||||
@ -8,6 +8,6 @@
|
||||
#define DRONESCREWSERVER_COMPANY_NAME "VisionTech"
|
||||
#define DRONESCREWSERVER_COPYRIGHT "Copyright (C) 2026"
|
||||
#define DRONESCREWSERVER_VERSION_STRING "1.0.0"
|
||||
#define DRONESCREWSERVER_VERSION_BUILD "2"
|
||||
#define DRONESCREWSERVER_VERSION_BUILD "3"
|
||||
|
||||
#endif // DRONESCREW_VERSION_H
|
||||
|
||||
@ -1,13 +1,38 @@
|
||||
# ABI fingerprint — self-contained delivery
|
||||
# OpenCV 4.5.0 (source build, standard SONAME — no Debian 'd' suffix)
|
||||
#
|
||||
# Target: aarch64, Ubuntu 22.04, glibc >= 2.32, RK3588 NPU driver
|
||||
# Bundled: OpenCV 4.5.0 + librknnrt 2.3.2, total 9 libs in lib/
|
||||
# SONAME: libopencv_core.so.4.5 (NOT .4.5d)
|
||||
# System: libc / libpthread / libm / libdl / libstdc++ / libgcc_s
|
||||
#
|
||||
# Install:
|
||||
# tar xzf stereo_bolt_delivery_selfcontained.tar.gz
|
||||
# cd stereo_bolt_delivery
|
||||
# export LD_LIBRARY_PATH=/e/02_Modules/StereoVisionBoltMeasurement_cpp/lib:
|
||||
# ldd lib/libstereo_bolt.so | grep "not found" # should be empty
|
||||
# ABI fingerprint of libstereo_bolt.so
|
||||
# Your board MUST match these or the .so will not load / not run.
|
||||
# generated: 2026-07-01 (rebuilt on RK3588; OBB-axis ranging stability fix)
|
||||
# libstereo_bolt.so SHA256:
|
||||
# 67d9406c1ab69c36b8f3b363fe6cf38567fdac97c25fa160e4c80a4d63b172ae
|
||||
|
||||
[arch]
|
||||
AArch64
|
||||
|
||||
[exported symbols] (9 total: lifecycle + precise + ranging)
|
||||
# --- lifecycle / construction ---
|
||||
sb_create # create from a config.yaml path (reads files from disk)
|
||||
sb_create_ex # NEW: create from in-memory structs (zero file IO / no path / no perms)
|
||||
sb_default_params # NEW: prefilled StereoBoltParamsC for sb_create_ex
|
||||
sb_destroy
|
||||
sb_last_error
|
||||
sb_free_bolt_module_result
|
||||
# --- precise measurement (12MP) ---
|
||||
sb_process_bolt_module_files # precise, file variant
|
||||
sb_process_bolt_module_buffers # precise, in-memory buffer variant
|
||||
# --- binned ranging (3MP) ---
|
||||
sb_range_bolt_binned # binned ranging, in-memory buffer
|
||||
|
||||
[min glibc required] (your board's glibc must be >= this)
|
||||
GLIBC_2.32
|
||||
|
||||
[NEEDED shared libraries] (provide matching sonames at runtime)
|
||||
librknnrt.so
|
||||
libopencv_calib3d.so.4.5
|
||||
libopencv_imgcodecs.so.4.5
|
||||
libopencv_dnn.so.4.5
|
||||
libopencv_imgproc.so.4.5
|
||||
libopencv_core.so.4.5
|
||||
libstdc++.so.6
|
||||
libm.so.6
|
||||
libgcc_s.so.1
|
||||
libc.so.6
|
||||
ld-linux-aarch64.so.1
|
||||
|
||||
67
AppAlgo/stereo_bolt_delivery/CHANGELOG.txt
Normal file
67
AppAlgo/stereo_bolt_delivery/CHANGELOG.txt
Normal file
@ -0,0 +1,67 @@
|
||||
CHANGELOG — libstereo_bolt delivery package
|
||||
============================================
|
||||
|
||||
## 2026-07-01 v3 — stable OBB-axis ranging summary
|
||||
|
||||
Current delivery contents:
|
||||
- Model: best_obb_1024.rknn (OBB, imgsz 1024, RKNN)
|
||||
- Precise measurement and ranging share the same OBB model.
|
||||
- Runtime libraries are bundled in lib/: libstereo_bolt.so, OpenCV 4.5.0, librknnrt.so.
|
||||
- No target-board apt install is required for runtime OpenCV.
|
||||
|
||||
Algorithm:
|
||||
- Ranging now uses left/right OBB-axis pairing before the NCC fallback.
|
||||
- Even-count OBB candidates no longer average two different pair hypotheses.
|
||||
The summary distance chooses the center candidate with the more stable sampled
|
||||
axis disparity, removing the RK3588 1498/1652 mm jump.
|
||||
|
||||
Performance / validation:
|
||||
- RK3588, distance_153304_403, 21 binned frames:
|
||||
found=21/21, distance mean=1652.360 mm, min=1652.091, max=1652.582,
|
||||
std=0.149 mm, elapsed mean=153.146 ms.
|
||||
- Windows ctest: 22/22 pass.
|
||||
|
||||
## 2026-06-30 v2 — OBB model + plane skip optimization
|
||||
|
||||
Changes vs previous delivery (2026-06-24, v1):
|
||||
|
||||
### Model
|
||||
- Previous package used an HBB detector at imgsz 960.
|
||||
- Current package uses best_obb_1024.rknn (OBB, imgsz 1024, YOLOv8 oriented bbox).
|
||||
- OBB model trained on mixed 5MP + 12MP data (2026-06-29)
|
||||
- Auto-detection: library detects OBB vs HBB from RKNN output shape
|
||||
|
||||
### Config
|
||||
- yolo.task: "auto" (auto-detect OBB/HBB from model output)
|
||||
- yolo.imgsz: 960 -> 1024
|
||||
- yolo.conf: 0.5 (unchanged)
|
||||
- measurement.height_from_plane: false (height = top-to-foot along axis)
|
||||
- working_distance.z_min_mm: 1200 -> 900
|
||||
- working_distance.z_max_mm: 2800 -> 4000
|
||||
- ranging.z_min_mm: 1300 -> 900
|
||||
- ranging.z_max_mm: 3600 -> 4000
|
||||
|
||||
### Algorithm
|
||||
- Plane computation skipped when height_from_plane=false
|
||||
(saves 300-550ms per frame on 8-bolt scenes)
|
||||
- OBB auto-detection in RKNN backend
|
||||
- OBB centerline rescue + peer height consensus clamp
|
||||
|
||||
### Calibration
|
||||
- Unchanged: stereo_calib_20260621_202857_ascii.xml (baseline 482mm)
|
||||
|
||||
### C API
|
||||
- ABI unchanged: c_api.h has zero changes
|
||||
- All function signatures identical
|
||||
- Struct layouts identical
|
||||
- Drop-in .so replacement, no recompile needed for downstream
|
||||
|
||||
### Performance (RK3588 board, 8-bolt scene, height_from_plane=false)
|
||||
- Precise: ~400ms/frame (was ~800ms with plane enabled)
|
||||
- Ranging: superseded by v3 benchmark above
|
||||
|
||||
### Verified on
|
||||
- RK3588 board (linaro): 0621 dataset 21 frames, 12/21 success
|
||||
- 0627 dataset 10 frames: 10/10 success
|
||||
- 0628 dataset 10 frames: 10/10 success
|
||||
- Windows ctest at the time: 20/20 pass
|
||||
@ -1,166 +1,226 @@
|
||||
# libstereo_bolt 交付说明（.so + 头文件）
|
||||
|
||||
你拿到的是**预编译的 aarch64 动态库 + C 头文件**，不含算法源码。
|
||||
OpenCV 4.5.4、RKNN runtime 及全部传递依赖（约 131 个 `.so`）**已随包内置于 `lib/`**，
|
||||
无需在目标板上安装任何软件包（NPU 内核驱动由固件提供，不在用户态包内）。
|
||||
你拿到的是**预编译的 aarch64 动态库 + C 头文件 + 模型 + 标定 + 示例**，不含算法源码。
|
||||
运行时依赖中 **`libstereo_bolt.so`、OpenCV 4.5.0 `.so`、`librknnrt.so` 均已随包 `lib/`**；无需 apt 安装 OpenCV。NPU 驱动由板子系统提供。
|
||||
|
||||
> **本包标定 = 12MP 生产相机（4096×3000）。** 喂进来的左右图必须是该相机的 **4096×3000** 帧
|
||||
> （`config` 里 `image.width=4096 / height=3000` 已配好，指向 `calib/stereo_calib_20260607_211135.xml`）。
|
||||
> **包内不含测试图** —— 请用你自己这套 12MP 相机拍的左右图。
|
||||
> ✅ **已在板上实测**：本 12MP 标定**加载 + rectify 通过**（4096×3000，stereo_rms=0.373、baseline=200.19、f_rect=3330）。
|
||||
> ⚠️ 但**检测 + 测量在该相机上还没用真实螺杆图验过**（包内无螺杆图）。
|
||||
> ⚠️ 本标定单相机 RMS=**0.373**（5MP 那套是 0.19），已把 `calibration.max_single_rms` **放宽到 0.40** 才放行；
|
||||
> 0.373 偏松会折损测量精度，建议后续**重标到 <0.20** 再收回此闸。首次上机务必用真实螺杆图核对结果。
|
||||
> **本库导出两个独立的产品接口**（同一个 `.so`、同一个 `StereoBoltCtx`）：
|
||||
> 1. **精测（PRECISE）** `sb_process_bolt_module_buffers` / `_files` —— 12MP 高精度测量，
|
||||
> 每颗螺栓高度 / 相邻间距 / 地平面 / 3D 中心轴 / 顶底 3D 坐标。**触发式"测得准"路径（板上约 400ms/帧，依输入和 QC 耗时波动）。**
|
||||
> 2. **测距（RANGING）** `sb_range_bolt_binned` —— 2×2 binned(3MP) 实时测距，
|
||||
> 输出相机→螺栓代表直线距离。**无人机实时路径（统一用 OBB@1024，当前 distance_153304_403 复测约 153ms/帧）。**
|
||||
>
|
||||
> **创建上下文推荐用内存接口 `sb_create_ex`**（见下节）：标定、模型、参数全部经接口/buffer 传入，
|
||||
> 库**零文件 IO、无路径假设、无安装目录读权限问题**。旧的 `sb_create(config.yaml)` 仍保留作向后兼容。
|
||||
|
||||
---
|
||||
|
||||
## ★ 创建上下文：`sb_create_ex`（推荐）vs `sb_create`（兼容）
|
||||
|
||||
两个产品接口共用同一个 `StereoBoltCtx`。创建它有两种方式：
|
||||
|
||||
### 推荐：`sb_create_ex` —— 全参数经接口传入，零文件 IO
|
||||
```c
|
||||
StereoBoltCtx* sb_create_ex(const StereoBoltCalibC* calib,
|
||||
const StereoBoltModelC* model,
|
||||
const StereoBoltParamsC* params);
|
||||
StereoBoltParamsC sb_default_params(void); /* 预填默认值，再覆盖你关心的 */
|
||||
```
|
||||
- `StereoBoltCalibC`：标定 —— 左右 `K[9]`/`D[5]` + `R[9]`/`T[3]` + `baseline_mm` + 图像尺寸。**替代标定 XML。**
|
||||
- `StereoBoltModelC`：模型 —— `.rknn` 字节流 `data`+`size` + `backend`(rk3588 用 `SB_YOLO_BACKEND_RKNN`) + `imgsz`/`conf`/`iou`。**替代 weights 文件路径。**
|
||||
- `StereoBoltParamsC`：算法数值参数 —— 视差带（`wd_z_min/max_mm` 物理带，**或** `sgbm_min/num_disparities` 固定带，二选一必填）、`rectification`、`measurement.foot_rim`、`ranging.*`。**替代 config.yaml 数值键。** 带 `struct_size` 做前向兼容。
|
||||
|
||||
**这条路径库不碰磁盘**：标定/模型从哪来由你决定（你的标定流程、资源文件、相机 SDK）；本包提供的 `calib/*.xml` 与 `weights/*.rknn` 只是**给你读进来填结构体**的现成数据。
|
||||
|
||||
### 兼容：`sb_create(const char* config_yaml_path)`
|
||||
读 `config.rk3588.12mp.yaml`（其内部再按相对路径找标定 XML + 模型）。**有两文件依赖 + 工作目录/读权限要求**——正是 `sb_create_ex` 要规避的。仅在离线/快速测试时用。
|
||||
|
||||
> `sb_create` / `sb_create_ex` **只调一次**（载配置+标定+模型进 NPU，慢），之后每帧复用同一个 `ctx`。
|
||||
> `sb_destroy` / `sb_last_error` 两接口共用。线程安全：同一 `ctx` 别多线程并发。
|
||||
|
||||
---
|
||||
|
||||
## 交付边界（职责划分）
|
||||
|
||||
**本交付物是一个"算法模块"，不是完整软件系统。** 软件总体集成由你（接入方）负责。
|
||||
|
||||
| 项 | 由谁负责 |
|
||||
|---|---|
|
||||
| 双目螺栓**测量/测距算法**（`.so` + `.h` + 模型 + 标定 + 示例 + 文档） | **算法方（本包提供）** |
|
||||
| 板子**运行时环境**：aarch64 + glibc、NPU 驱动；算法依赖的 OpenCV 与 `librknnrt.so` 已随包 `lib/` | **接入方** |
|
||||
| **取图**（相机驱动 / Mono8 buffer 喂入）、上层业务、UI、调度、与上位机/无人机通信 | **接入方** |
|
||||
| **标定数据来源**（填入 `StereoBoltCalibC`）、按 `c_api.h` 调用、对 height/distance/confidence 做业务决策 | **接入方** |
|
||||
|
||||
> 算法方只交付"喂进左右图 → 返回螺栓高度/距离"的纯算法能力（C ABI）。本库不碰相机、不碰网络、
|
||||
> **不碰磁盘（`sb_create_ex` + buffer 接口）**、不做悬停/对中等业务决策。逐颗 `confidence`(trusted/suspect) + `status` 由接入方取舍。
|
||||
|
||||
## 包内容
|
||||
| 路径 | 说明 |
|
||||
|---|---|
|
||||
| `lib/libstereo_bolt.so` | 预编译共享库（aarch64） |
|
||||
| `lib/librknnrt.so` 等（共 ~131 个） | OpenCV 4.5.4 + 全部传递依赖（**已随包，无需 apt**） |
|
||||
| `lib/libstereo_bolt.so` | 预编译共享库（aarch64，含 `sb_create_ex` 内存接口） |
|
||||
| `include/stereo_bolt/c_api.h` | C ABI 头文件（唯一对外接口） |
|
||||
| `weights/best_1280_20260621.rknn` | NPU 模型（精测 + 测距共用，imgsz 1280） |
|
||||
| `calib/stereo_calib_20260621_202857_ascii.xml` | 出厂标定（0621 装配，baseline 482 mm） |
|
||||
| `config/config.rk3588.12mp.yaml` | 配置文件（兼容 `sb_create` 接口用） |
|
||||
| `example/` | 最小 C 示例（精测 + 测距） + CMakeLists |
|
||||
| `INSTALL_3588.md` | 安装与运行说明（**从这里开始**） |
|
||||
| `DEPENDENCIES.md` | 依赖库详细清单及说明 |
|
||||
| `ABI_FINGERPRINT.txt` | 二进制 ABI 指纹 |
|
||||
| `weights/best_obb_1024.rknn` | NPU 模型 —— OBB 检测（精测+测距共用，imgsz 1024，FP16） |
|
||||
| `calib/stereo_calib_20260621_202857_ascii.xml` | 12MP 双目标定（**0621 装配 baseline 482mm**，Halcon 位姿已修正） |
|
||||
| `config/config.rk3588.12mp.yaml` | 仅 `sb_create`（兼容）用 + 作参数参考；**`sb_create_ex` 不需要它** |
|
||||
| `lib/*.so` | 算法库、OpenCV 4.5.0 运行库、RKNN 运行时（aarch64 2.3.2），运行时通过 `LD_LIBRARY_PATH=./lib` 加载 |
|
||||
| `INSTALL_3588.md` / `ABI_FINGERPRINT.txt` | 板上装环境说明 / .so 二进制指纹（**你的环境必须匹配**） |
|
||||
| `example/` | C 调用示例（`main.c` 精测，**sb_create + buffer 接口**）+ CMakeLists |
|
||||
|
||||
---
|
||||
|
||||
## 你什么时候需要什么（编译期 vs 运行期）
|
||||
## 编译期 vs 运行期
|
||||
|
||||
**重点：你不需要重编这个库**（它是预编译好的成品，你也没有源码）。你只编译*你自己*
|
||||
调用它的小程序，那一步几乎零依赖。OpenCV / librknnrt 是**运行那一刻**才需要的。
|
||||
**你不需要重编这个库**（预编译成品，无源码）。你只编译*你自己*调用它的程序。
|
||||
|
||||
| 东西 | 编译你自己的调用程序 | 在板上**运行** |
|
||||
| 东西 | 编译你的调用程序 | 板上运行 |
|
||||
|---|:---:|:---:|
|
||||
| `c_api.h` | ✅ | — |
|
||||
| `libstereo_bolt.so` | ✅（链接，带 `--allow-shlib-undefined`） | ✅ |
|
||||
| OpenCV 4.5.4 | ❌ 不需要（C ABI 不暴露 cv 类型） | ✅ **已随包 `lib/`，无需安装** |
|
||||
| `librknnrt.so`（RKNN 运行时） | ❌ | ✅ **已随包 `lib/`** |
|
||||
| OpenCV | 你的程序：❌ 不需要（C ABI 不暴露 cv 类型，相机直接给 Mono8 buffer）<br>本包 example：❌ 运行不需要系统 OpenCV | ✅ 已随包 `lib/`，无需 apt |
|
||||
| `librknnrt.so` | ❌ | ✅ 已随包 `lib/`，`LD_LIBRARY_PATH=./lib` |
|
||||
| NPU 驱动 + `/dev/rknpu` | ❌ | ✅ 必须（内核态） |
|
||||
| `.rknn` 模型 + 标定 XML + `config` | ❌ | ✅ 必须（**已在本包** weights/ config/ calib/） |
|
||||
| 模型 / 标定 | ❌ | ✅（已在本包；`sb_create_ex` 由你读进来传，`sb_create` 由库读） |
|
||||
|
||||
> **“YOLO 依赖”在板上很轻**：就是 `librknnrt.so` + NPU 驱动 + `.rknn` 文件。
|
||||
> **不需要** Python / PyTorch / ultralytics / ONNXRuntime / rknn-toolkit2 —— 那些是 PC 上把
|
||||
> `.onnx` 转成 `.rknn` 用的，转完板上就用不到。
|
||||
> example 用 OpenCV 只是为了独立跑（读本包的标定 XML + 测试图）。**你的产品里相机直接给 Mono8 buffer、
|
||||
> 标定来自你自己的来源，调用端无需 OpenCV，库也始终零文件 IO。**
|
||||
|
||||
---
|
||||
|
||||
## ⚠️ 必须匹配的 ABI 指纹（动态链接的硬约束）
|
||||
## ⚠️ 必须匹配的 ABI 指纹
|
||||
|
||||
这个 `.so` 在某个具体环境里编出来，二进制里**写死了**它依赖的 so 名字和 glibc 版本。
|
||||
**“自己准备 OpenCV” 不等于随便哪个 OpenCV 都行——必须是指纹里那个 major.minor。**
|
||||
`.so` 二进制里写死了依赖的 so 名字和 glibc 版本。打开 `ABI_FINGERPRINT.txt` 确保板子满足：
|
||||
- CPU = **aarch64**；**glibc ≥ 指纹版本**（GLIBC_2.32）；
|
||||
- **运行时优先使用本包 `lib/`**（内含标准 SONAME `libopencv_*.so.4.5`，无需系统 OpenCV）；
|
||||
- **librknnrt 版本** = 转 `.rknn` 的 toolkit 版本（**2.3.x**）。
|
||||
- 指纹应列出 9 个导出符号，含 **`sb_create_ex` / `sb_default_params`**。
|
||||
|
||||
打开 `ABI_FINGERPRINT.txt`，确保你的板子满足：
|
||||
|
||||
- CPU 架构 = **aarch64**
|
||||
- **glibc ≥ 指纹里的版本**（低于它，加载即 `GLIBC_x.xx not found`）
|
||||
- **OpenCV soname 与指纹一致**（本包指纹 = `libopencv_core.so.4.5d` ⇒ 装 **OpenCV 4.5.x**；其它版本 soname 不通用）
|
||||
- **librknnrt 版本** = 转换 `.rknn` 所用 toolkit 版本（**2.3.x**）
|
||||
|
||||
一条命令自检（应当**没有任何** `not found`）：
|
||||
|
||||
```bash
|
||||
ldd lib/libstereo_bolt.so | grep "not found"
|
||||
```
|
||||
自检（应无任何 `not found`）：`ldd lib/libstereo_bolt.so | grep "not found"`
|
||||
|
||||
---
|
||||
|
||||
## 板子上需要准备的
|
||||
## 公共错误码
|
||||
|
||||
| 依赖 | 状态 |
|
||||
|---|---|
|
||||
| OpenCV 4.5.4 + 传递依赖（131 个 .so） | ✅ **已随包 `lib/`**，无需 apt |
|
||||
| `librknnrt.so`（RKNN 运行时 2.3.2） | ✅ **已随包 `lib/`** |
|
||||
| `.rknn` 模型 + 标定 XML + config | ✅ **已随包** `weights/` `calib/` `config/` |
|
||||
| NPU 内核驱动 + `/dev/rknpu` | ⚠️ **板子固件提供**，出厂 RK3588 一般已有 |
|
||||
| glibc ≥ 2.32（Ubuntu 22.04 自带 2.35） | ✅ 系统自带，无需操作 |
|
||||
|
||||
> 完整依赖说明见 `DEPENDENCIES.md`。
|
||||
`SB_OK=0` / `SB_ERR_INVALID_CONFIG=-1` / `SB_ERR_IO=-2` / `SB_ERR_ALGORITHM_REJECTED=-3` / `SB_ERR_INTERNAL=-99`。
|
||||
> `SB_ERR_ALGORITHM_REJECTED` 不是崩溃，是算法判定该帧不满足 `expected` 颗（仅精测返回）；**仍返回已测出的部分螺栓**（见下）。
|
||||
|
||||
---
|
||||
|
||||
## 怎么用（C ABI）
|
||||
## 接口 1 —— 精测（PRECISE）
|
||||
|
||||
完整示例见 `example/main.c`。有**两个**喂帧入口,生产用内存版:
|
||||
**用途**：12MP 逐颗高精度测量。触发式"测得准"路径，板上 ~2.5Hz@1024。
|
||||
**输入**：内存 Mono8 buffer（生产首选）或文件路径（离线）。buffer 尺寸**必须等于标定尺寸**，否则 `SB_ERR_IO`。
|
||||
|
||||
**① 生产路径 —— 内存版(不落盘,直接喂相机帧):**
|
||||
```c
|
||||
StereoBoltCtx* ctx = sb_create("config/config.rk3588.yaml"); // 一次:载配置/标定/RKNN 模型
|
||||
while (抓帧) {
|
||||
const uint8_t* L = camera_left_frame(); // 相机 SDK 给的 Mono8 缓冲(W*H 字节,在内存)
|
||||
const uint8_t* R = camera_right_frame();
|
||||
StereoBoltModuleResultC out;
|
||||
sb_process_bolt_module_buffers(ctx,
|
||||
L, W, H, 0, // stride=0 表示行紧凑排列(每行 W 字节)
|
||||
R, W, H, 0,
|
||||
1, // channels: 1=Mono8(灰度), 3=BGR 也接受(内部转灰度)
|
||||
8, &out); // 8 = 期望螺栓数
|
||||
/* out.success==1: out.data.bolts[i].height_mm / foot_xyz / top_xyz + adjacent_distances + ground_plane
|
||||
out.success==0: out.failure.reason + left_rois/right_rois/pairs(诊断用) */
|
||||
sb_free_bolt_module_result(&out);
|
||||
}
|
||||
sb_destroy(ctx); // 一次
|
||||
sb_status_t sb_process_bolt_module_buffers(
|
||||
StereoBoltCtx* ctx,
|
||||
const uint8_t* left_data, int left_width, int left_height, int left_stride_bytes,
|
||||
const uint8_t* right_data, int right_width, int right_height, int right_stride_bytes,
|
||||
int channels, int expected_bolt_count, StereoBoltModuleResultC* out);
|
||||
sb_status_t sb_process_bolt_module_files(StereoBoltCtx*, const char* left, const char* right,
|
||||
int expected_bolt_count, StereoBoltModuleResultC* out);
|
||||
void sb_free_bolt_module_result(StereoBoltModuleResultC* out); /* 用完必须释放 */
|
||||
```
|
||||
> `W`/`H` **必须等于标定分辨率**(`config` 的 `image.width`/`image.height`),否则返回 `SB_ERR_IO`。
|
||||
> 内存版**全程不碰磁盘**(已实测:删掉源文件后内存版照常出结果)。
|
||||
|
||||
**② 离线/测试路径 —— 文件版(读磁盘图,用你自己的 12MP 左右图):**
|
||||
**输出 `StereoBoltModuleResultC`** —— 每颗 `data.bolts[i]`：
|
||||
- **`height_mm`**（高度）
|
||||
- **`top_xyz` / `foot_xyz`**（顶 / 底 3D 坐标）
|
||||
- **`centerline`**（3D 中心轴：`point` + `direction`）
|
||||
- `left_roi` / `right_roi`（左右图 2D 框 x,y,w,h,score）
|
||||
- **`confidence`**（0=trusted / 1=suspect）+ `status`
|
||||
另含 `adjacent_distances[]`（相邻 `distance_mm`）、`ground_plane`（`model[4]`/`rms_mm`/`inlier_count`）。
|
||||
|
||||
**坐标系/单位**：高度、间距、3D 坐标 = **mm**，**校正后左相机坐标系**（x 右 / y 下 / z=深度，典型 z≈1600–2200mm）。
|
||||
|
||||
**★ 部分输出契约（去 all-or-nothing）**：即使 `success==0`（数量不符 `count_mismatch`，无论检到的多还是少于 `expected`），
|
||||
`data.bolts[]` 仍含**所有干净测出的螺栓**（各带 height/top/foot/confidence）；`failure`（reason + 完整 ROI + 配对状态）始终填充，能看出缺哪颗、为何缺。**别只看返回码就丢结果——照样遍历 `data.bolts[]`，按 `confidence` 自行取舍。**
|
||||
|
||||
**最简用法（`sb_create_ex`）**：
|
||||
```c
|
||||
sb_process_bolt_module_files(ctx, "your_left.bmp", "your_right.bmp", 8, &out);
|
||||
StereoBoltCalibC calib = {...}; /* 填 K/D/R/T/size/baseline */
|
||||
StereoBoltModelC model = {.data=rknn_bytes, .size=n, .backend=SB_YOLO_BACKEND_RKNN, .imgsz=1024, .conf=0.5f};
|
||||
StereoBoltParamsC p = sb_default_params(); p.wd_z_min_mm=1200; p.wd_z_max_mm=2800;
|
||||
StereoBoltCtx* ctx = sb_create_ex(&calib, &model, &p); /* 一次 */
|
||||
StereoBoltModuleResultC out;
|
||||
sb_process_bolt_module_buffers(ctx, L,w,h,0, R,w,h,0, 1, /*expected=*/6, &out);
|
||||
/* 遍历 out.data.bolts[i].height_mm / top_xyz / foot_xyz ... */
|
||||
sb_free_bolt_module_result(&out); sb_destroy(ctx);
|
||||
```
|
||||
> 图必须是本套 12MP 相机的 4096×3000(灰度或彩色均可),格式 .bmp/.tiff/.png。本包不含测试图。
|
||||
|
||||
错误码：`SB_OK=0` / `SB_ERR_INVALID_CONFIG=-1` / `SB_ERR_IO=-2` /
|
||||
`SB_ERR_ALGORITHM_REJECTED=-3` / `SB_ERR_INTERNAL=-99`。
|
||||
> `SB_ERR_ALGORITHM_REJECTED` 不是崩溃，是算法判定该帧不可测，`out.failure` 里有原因 + ROI + 配对状态。
|
||||
完整示例见 `example/main.c`。**imgsz 首选 1024**（OBB 模型，自动检测旋转框）；交付权重 FP16（INT8 检出全废，不可用）。
|
||||
|
||||
---
|
||||
|
||||
## 输入 / 输出（契约）
|
||||
## 高度测量模式（`measurement.height_from_plane`）
|
||||
|
||||
**输入**
|
||||
- 一次性（`sb_create`）：`config/config.rk3588.yaml`（内部指向 `calib/*.xml` 与 `weights/best.rknn`）。
|
||||
- 每帧（生产用 `sb_process_bolt_module_buffers`）：左/右 Mono8 内存缓冲 + 宽/高/stride、通道数、期望螺栓数(int)、`&out`。
|
||||
- 每帧（离线用 `sb_process_bolt_module_files`）：左图路径、右图路径、期望螺栓数(int)、`&out`。
|
||||
精测接口支持两种高度计算方式，通过 config 中 `measurement.height_from_plane` 切换：
|
||||
|
||||
**输出**（`StereoBoltModuleResultC out` + 返回码）
|
||||
- 成功 `out.success==1` → `out.data`：
|
||||
- `bolts[]` 每颗：`bolt_id` / `left_roi`,`right_roi`(x,y,width,height,score) / **`height_mm`** /
|
||||
**`foot_xyz`,`top_xyz`**(底/顶 3D 点) / `centerline`(3D 轴 = point+direction)
|
||||
- `adjacent_distances[]`：`bolt_id_i`,`bolt_id_j`,**`distance_mm`**
|
||||
- `ground_plane`：`model[4]`(ax+by+cz+d=0)、`rms_mm`、`inlier_count`
|
||||
- 失败 `out.success==0` → `out.failure`：`reason` + `left_rois[]`/`right_rois[]` + `pairs[]`(配对诊断)
|
||||
| 模式 | config 值 | 高度定义 | 是否需要平面拟合 | 板上耗时（8颗场景） |
|
||||
|---|---|---|---|---|
|
||||
| **顶到底**（默认） | `height_from_plane: false` | 螺杆顶端到可见底端沿拟合轴的长度 | **不需要**（自动跳过） | ~400ms |
|
||||
| **顶到平面** | `height_from_plane: true` | 螺杆顶端到支撑平面的法向距离 | 需要（StereoBM 拟合） | ~800ms |
|
||||
|
||||
**单位 / 坐标系**：高度、间距 = **mm**；3D 坐标(foot/top/centerline) = **mm，校正后左相机坐标系**
|
||||
（x 右 / y 下 / z=深度，典型 z≈1600–2200mm）。`score`=YOLO 置信度。
|
||||
**默认关闭平面测量**（`height_from_plane: false`），此时平面计算完全跳过，节省 300-550ms。
|
||||
|
||||
输出格式示例（**仅示意字段结构**，数值来自早先 5MP 验证机，非本包 12MP 相机）：
|
||||
|
||||
```
|
||||
success=1 bolts=8 distances=8
|
||||
bolt 0 height=151.2mm top=(-191.9,-122.9,1995.3) foot=(-204.3,2.9,2078.3)
|
||||
...
|
||||
dist 0-1=268.3mm dist 1-2=254.4mm ... dist 7-0=335.8mm
|
||||
**开启平面测量**：在 `config.rk3588.12mp.yaml` 中修改：
|
||||
```yaml
|
||||
measurement:
|
||||
height_from_plane: true # 开启：高度 = 螺杆顶端到支撑平面的法向距离
|
||||
```
|
||||
|
||||
> 一句话：**入 = 一对左右图 + 期望螺栓数（配置/标定/模型初始化时给一次）；
|
||||
> 出 = 每颗螺栓 高度 + 顶/底 3D + 3D 中心轴 + 相邻间距 + 地平面，或失败原因 + 诊断。**
|
||||
`sb_create_ex` 用户：当前 `StereoBoltParamsC` 不含此字段，默认为 false（顶到底）。如需平面模式，使用 `sb_create(config.yaml)` 并在 config 中设置。
|
||||
|
||||
---
|
||||
|
||||
## 编译你自己的调用程序 + 运行（**都在包根目录执行**）
|
||||
## 接口 2 —— 测距（RANGING）`sb_range_bolt_binned`
|
||||
|
||||
**用途**：实时回答"左目光心→螺栓多远"。容忍部分可见：**绝不要求螺栓数**，≥1 颗即给距离。当前板上约 153ms/帧（~6.5Hz）@1024。
|
||||
**输入**：2×2 binned 内存 buffer（12MP→3MP=2048×1500），Mono8/BGR。binned 内参**内部推导**，无需单独 binned 标定。
|
||||
|
||||
```c
|
||||
typedef struct { double distance_mm; int left_x,left_y,right_x,right_y; double ncc_score,lrc_px; int confidence; } StereoBoltRangeBoltC;
|
||||
typedef struct { int found; double distance_mm; int bolt_count; char status[32]; } StereoBoltRangeSummaryC;
|
||||
sb_status_t sb_range_bolt_binned(
|
||||
StereoBoltCtx* ctx,
|
||||
const uint8_t* left_data, int left_width, int left_height, int left_stride_bytes,
|
||||
const uint8_t* right_data, int right_width, int right_height, int right_stride_bytes,
|
||||
int channels, StereoBoltRangeSummaryC* out, StereoBoltRangeBoltC* bolts, int max_bolts);
|
||||
```
|
||||
**输出**：主用 `out.distance_mm`（可见杆代表距离）；`out.found` 每帧轮询；`bolts[]` 给出每颗候选的左右匹配点。OBB 轴路线下 `ncc_score` 为检测/匹配分数、`lrc_px` 为轴视差自洽度（字段名保留用于 ABI 兼容）；NCC 回退路线下为 NCC/LRC 指标。精度目标 **±50mm**（稳定区 1.3–2.4m）。
|
||||
**可选 `ranging.*` 参数**（`StereoBoltParamsC` 里 `rng_*`，都有默认）：`z_min/max_mm` 视差带、`lrc_max_mm`/`lrc_trusted_mm` 物理同根门 等。完整示例见 `example/range_example.cpp`。
|
||||
|
||||
> 注：`sb_create_ex` 即使**只做测距**也要求提供精测视差带（`wd_z_*` 或 `sgbm_*`），因为同一 `ctx` 两接口共用。
|
||||
|
||||
---
|
||||
|
||||
## 该用哪个 + 板上实测吞吐
|
||||
|
||||
| | 精测 `sb_process_bolt_module_*` | 测距 `sb_range_bolt_binned` |
|
||||
|---|---|---|
|
||||
| 问题 | 每颗螺栓高度/间距/地平面/3D 坐标 | 相机离螺栓多远（代表距离） |
|
||||
| 输入 | 12MP 原图（Mono8 buffer / 文件） | 2×2 binned 3MP buffer |
|
||||
| 螺栓数 | 要 `expected`（不符=部分输出+`count_mismatch`） | **不要**，≥1 颗即 `found` |
|
||||
| 板上吞吐@1024 | **约 400ms/帧** | **约 153ms/帧 ≈ 6.5Hz** |
|
||||
| 定位 | 触发式"测得准" | 无人机实时定位反馈 |
|
||||
|
||||
> 测距实测于 RK3588（best_obb_1024.rknn，distance_153304_403，21 帧）：均值 153.146ms，距离均值 1652.360mm，跨度 0.491mm。
|
||||
> 本交付为单模型 OBB@1024（精测+测距共用）。
|
||||
|
||||
---
|
||||
|
||||
## 编译你的调用程序 + 运行
|
||||
|
||||
示例用 C/C++，运行时库从本包 `lib/` 加载：
|
||||
```bash
|
||||
# 在包根目录（与 lib/ config/ calib/ 同级）编译
|
||||
cmake -S example -B example/build -DSB_ROOT="$(pwd)"
|
||||
cmake --build example/build
|
||||
cd example
|
||||
cmake -S . -B build -DSB_ROOT="$(cd .. && pwd)"
|
||||
cmake --build build # -> bolt_demo（精测）+ range_demo（测距）
|
||||
|
||||
# 在包根目录运行(config 里 calib/、weights/ 是相对路径,按当前目录解析)
|
||||
# example 走【内存接口】: 读 raw Mono8 裸数据(W*H 字节)喂 sb_process_bolt_module_buffers,
|
||||
# 库全程不见文件路径。your_left/right.raw = 你 12MP 相机帧 dump 的 Mono8(4096*3000 字节)
|
||||
LD_LIBRARY_PATH=lib:/usr/lib:$LD_LIBRARY_PATH \
|
||||
./example/build/bolt_demo config/config.rk3588.yaml your_left.raw your_right.raw 4096 3000 8
|
||||
# ../lib 含 libstereo_bolt.so + OpenCV 4.5.0 + librknnrt.so
|
||||
# 精测：传标定 XML + 模型 + 左右图 + 期望螺栓数
|
||||
LD_LIBRARY_PATH=../lib:$LD_LIBRARY_PATH \
|
||||
./build/bolt_demo ../calib/stereo_calib_20260621_202857_ascii.xml \
|
||||
../weights/best_obb_1024.rknn L.bmp R.bmp 6
|
||||
|
||||
# 测距：传标定 + 模型 + 左右图（demo 内部 2×2 binning；生产直接喂相机 binned buffer）
|
||||
LD_LIBRARY_PATH=../lib:$LD_LIBRARY_PATH \
|
||||
./build/range_demo ../calib/stereo_calib_20260621_202857_ascii.xml \
|
||||
../weights/best_obb_1024.rknn L.bmp R.bmp
|
||||
```
|
||||
|
||||
@ -5,74 +5,25 @@
|
||||
|
||||
---
|
||||
|
||||
## 一、包含哪些库（lib/ 目录）
|
||||
## 一、包含哪些库（lib/ 目录，共 9 个）
|
||||
|
||||
### 核心算法库（本包提供）
|
||||
| 库 | 说明 |
|
||||
|---|---|
|
||||
| `libstereo_bolt.so` | 本算法库（主体） |
|
||||
| `librknnrt.so` | RKNN NPU 推理运行时（Rockchip 2.3.2） |
|
||||
| `libopencv_core.so.4.5` | OpenCV 4.5.0 — 基础矩阵/图像容器 |
|
||||
| `libopencv_imgproc.so.4.5` | OpenCV 4.5.0 — 图像处理 |
|
||||
| `libopencv_calib3d.so.4.5` | OpenCV 4.5.0 — 立体标定、rectify、三角测量 |
|
||||
| `libopencv_imgcodecs.so.4.5` | OpenCV 4.5.0 — 图像文件读写 |
|
||||
| `libopencv_dnn.so.4.5` | OpenCV 4.5.0 — DNN 模块 |
|
||||
| `libopencv_features2d.so.4.5` | OpenCV 4.5.0 — 特征点（calib3d 依赖） |
|
||||
| `libopencv_flann.so.4.5` | OpenCV 4.5.0 — FLANN 索引（features2d 依赖） |
|
||||
|
||||
### OpenCV 4.5.4（Ubuntu 22.04 release，aarch64）
|
||||
| 库 | 用途 |
|
||||
|---|---|
|
||||
| `libopencv_core.so.4.5d` | 基础矩阵/图像容器 |
|
||||
| `libopencv_imgproc.so.4.5d` | 图像处理（滤波、边缘、几何变换） |
|
||||
| `libopencv_calib3d.so.4.5d` | 立体标定、rectify、三角测量 |
|
||||
| `libopencv_imgcodecs.so.4.5d` | 图像文件读写（bmp/png/tiff） |
|
||||
| `libopencv_dnn.so.4.5d` | DNN 模块（YOLO ONNX 推理备用后端） |
|
||||
| `libopencv_features2d.so.4.5d` | 特征点（calib3d 依赖） |
|
||||
| `libopencv_flann.so.4.5d` | FLANN 索引（features2d 依赖） |
|
||||
|
||||
### 图像编解码层（OpenCV 依赖）
|
||||
| 库 | 用途 |
|
||||
|---|---|
|
||||
| `libjpeg.so.8` | JPEG |
|
||||
| `libpng16.so.16` | PNG |
|
||||
| `libtiff.so.5` | TIFF（含 libjbig/libdeflate/liblzma/libzstd/liblz4） |
|
||||
| `libwebp.so.7` | WebP |
|
||||
| `libopenjp2.so.7` | JPEG2000 |
|
||||
| `libIlmImf-2_5.so.25` 等 | OpenEXR（IlmImf/Imath/Iex/IlmThread/Half） |
|
||||
| `libheif.so.1` 等 | HEIF/HEVC（libaom/libde265/libx265/libdav1d） |
|
||||
| `libgif.so.7` | GIF |
|
||||
| `libcharls.so.2` | JPEG-LS |
|
||||
| `libz.so.1` | zlib |
|
||||
|
||||
### 并行计算（OpenCV 依赖）
|
||||
| 库 | 用途 |
|
||||
|---|---|
|
||||
| `libtbb.so.2` | Intel TBB 线程并行 |
|
||||
|
||||
### DNN / 模型序列化（OpenCV DNN 依赖）
|
||||
| 库 | 用途 |
|
||||
|---|---|
|
||||
| `libprotobuf.so.23` | Protobuf（ONNX 模型解析） |
|
||||
|
||||
### GDAL / 地理空间（OpenCV imgcodecs 依赖，随包但运行中不主动调用）
|
||||
libgdal、libgdcm\*、libgeotiff、libproj、libgeos\*、libogdi、libspatialite、
|
||||
libnetcdf、libhdf5\*、libpq（PostgreSQL）、libmysqlclient、libsqlite3、
|
||||
libcfitsio、libkml\*、libminizip、liburiparser、libxerces-c、libfreexl、
|
||||
libarmadillo、libblas/liblapack/libgfortran、libarpack、libsuperlu、
|
||||
libqhull\_r、libfyba/libfyut/libfygm、libblosc、libsnappy、libsz/libaec、
|
||||
libmfhdfalt/libdfalt、librttopo、libxml2、libgif
|
||||
|
||||
### 字体 / PDF（libgdal → libpoppler 链）
|
||||
libpoppler、libfreetype、libbrotli\*、libfontconfig、liblcms2
|
||||
|
||||
### 网络 / 安全（libgdal → libcurl 链，随包但不主动使用）
|
||||
libcurl、libcurl-gnutls、libssl/libcrypto（OpenSSL 3）、libgnutls、
|
||||
libnettle/libhogweed/libgmp、libp11-kit、libffi、libtasn1、
|
||||
libgssapi\_krb5/libkrb5/libk5crypto/libkrb5support（Kerberos）、
|
||||
libcom\_err、libkeyutils、libnghttp2、libidn2、libunistring、
|
||||
librtmp、libssh、libpsl、libldap/liblber、libsasl2
|
||||
|
||||
### 其他系统级（随包）
|
||||
libicuuc/libicudata（Unicode）、libnss\*/libnspr4/libplc4/libplds4/libsmime3（NSS）、
|
||||
libuuid、libjson-c、libexpat、libpcre2-8、libltdl、libodbc/libodbcinst、
|
||||
libnuma、libresolv、libtirpc
|
||||
|
||||
> 上述库来自 Ubuntu 22.04 apt（OpenCV 4.5.4 的官方传递依赖闭包），均为 **release/优化版本**，
|
||||
> 非 debug 版。库数量约 **131 个**，打包后约 **70 MB**。
|
||||
> OpenCV 从源码编译（非 apt 包），**SONAME 为标准的 `libopencv_*.so.4.5`**
|
||||
> （不带 Debian/Ubuntu 的 `d` 后缀），与自行源码编译 OpenCV 4.5.x 的环境兼容。
|
||||
>
|
||||
> 图像编解码（libjpeg/libpng/libtiff/libwebp/openjpeg）、protobuf、zlib
|
||||
> 均已**静态链入** OpenCV，不再作为独立 `.so` 出现。
|
||||
|
||||
---
|
||||
|
||||
@ -86,7 +37,6 @@ libnuma、libresolv、libtirpc
|
||||
| `libpthread.so.0` | 同上（已并入 glibc 2.34+） |
|
||||
| `libm.so.6` | 同上 |
|
||||
| `libdl.so.2` | 同上 |
|
||||
| `librt.so.1` | 同上 |
|
||||
| `libstdc++.so.6` | GCC 11+（Ubuntu 22.04 自带） |
|
||||
| `libgcc_s.so.1` | 同上 |
|
||||
| `ld-linux-aarch64.so.1` | 动态链接器，系统自带 |
|
||||
@ -95,47 +45,48 @@ libnuma、libresolv、libtirpc
|
||||
|
||||
## 三、为什么这么设计
|
||||
|
||||
**问题：** OpenCV 在 Ubuntu 22.04 拖着约 131 个传递依赖（包括 GDAL、curl、Kerberos、
|
||||
OpenSSL 等）。如果只靠目标板 apt 安装，新板子需要联网、可能遇到镜像源不可达、
|
||||
版本不一致等问题，交付不可控。
|
||||
**问题：** 如果目标板通过 apt 安装 OpenCV，Debian/Ubuntu 会给 SONAME 加私有后缀
|
||||
（如 `libopencv_core.so.4.5d` 而非标准的 `…4.5`），导致与自行编译的 OpenCV 不兼容；
|
||||
另外 apt 安装需要联网，新板子部署不可控。
|
||||
|
||||
**解法：** 把整个依赖闭包随包发布。运行时通过 `LD_LIBRARY_PATH` 优先搜索 `lib/`，
|
||||
所有依赖在包内自洽。这些库只对本进程生效，**不替换系统库**，不影响系统
|
||||
ssl/网络栈/其他程序。
|
||||
**解法：** 从 OpenCV 4.5.0 官方源码编译，只构建算法实际需要的 7 个模块
|
||||
（core/imgproc/calib3d/imgcodecs/dnn/features2d/flann），图像编解码等第三方库
|
||||
全部静态链入。最终 `lib/` 只有 9 个 `.so`（含本库 + librknnrt），约 **22 MB**，
|
||||
依赖关系极简，无需联网、无需 apt。
|
||||
|
||||
---
|
||||
|
||||
## 四、运行时加载方式
|
||||
|
||||
```bash
|
||||
# 解包后，设一次环境变量，之后所有调用本库的程序都能找到这些依赖
|
||||
# 解包后，设一次环境变量
|
||||
export LD_LIBRARY_PATH="$(pwd)/lib:$LD_LIBRARY_PATH"
|
||||
|
||||
# 验证：应当没有任何 "not found" 输出
|
||||
ldd lib/libstereo_bolt.so | grep "not found"
|
||||
```
|
||||
|
||||
`LD_LIBRARY_PATH` 对所有传递依赖生效——当 `libopencv_core` 加载 `libjpeg` 时，
|
||||
链接器同样优先搜索 `lib/`，无需对每个 `.so` 单独处理。
|
||||
---
|
||||
|
||||
## 五、SONAME 兼容性说明
|
||||
|
||||
| 编译来源 | SONAME | 与本包兼容？ |
|
||||
|---|---|---|
|
||||
| **本包（源码编译 4.5.0）** | `libopencv_core.so.4.5` | ✅ |
|
||||
| **自行源码编译 4.5.x** | `libopencv_core.so.4.5` | ✅ |
|
||||
| **Ubuntu apt `libopencv-dev`** | `libopencv_core.so.4.5d` | ❌ SONAME 不匹配 |
|
||||
|
||||
本包的 `libstereo_bolt.so` 链接的 NEEDED 是标准 `libopencv_*.so.4.5`（无 `d`），
|
||||
与任何从源码编译的 OpenCV 4.5.x 兼容。如果目标板上碰巧装了 apt 的 OpenCV（带 `d`），
|
||||
只要 `LD_LIBRARY_PATH` 优先指向 `lib/`，就会用本包内的库，不会冲突。
|
||||
|
||||
---
|
||||
|
||||
## 五、编译调用程序时注意
|
||||
## 六、编译调用程序时注意
|
||||
|
||||
运行不需要 OpenCV，但**编译** `example/` 示例代码时需要 OpenCV **头文件**
|
||||
（`.h`），而 `lib/` 里只有 `.so`（运行库），没有头文件。
|
||||
**生产路径**：你自己的代码只用 `include/stereo_bolt/c_api.h`，不引用任何 OpenCV 头，
|
||||
相机 buffer 直接传给 `sb_process_bolt_module_buffers`，**完全不需要 OpenCV 头文件**。
|
||||
|
||||
两种方案：
|
||||
|
||||
**A. 目标板上 apt 装头文件（推荐，只需一次）**
|
||||
```bash
|
||||
# 只装 -dev 包获取头文件；运行库用包内 lib/ 的，不用 apt 装的 .so
|
||||
sudo apt install libopencv-dev
|
||||
```
|
||||
|
||||
**B. 仅使用 C ABI，无需 OpenCV 头（生产路径）**
|
||||
|
||||
你自己的产品代码只用 `include/stereo_bolt/c_api.h`，不引用任何 OpenCV 头，
|
||||
相机 buffer 直接传给 `sb_process_bolt_module_buffers`。这是生产路径，
|
||||
**完全不需要 OpenCV 头文件**，也不需要 apt。
|
||||
`example/` 仅作集成验证用，生产端不需要编译它。
|
||||
**编译 `example/` 示例**（可选，仅用于集成验证）：当前示例是纯 C，
|
||||
只读 headerless Mono8 raw 文件并调用 C ABI，不引用 OpenCV 头文件。
|
||||
运行时仍用本包 `lib/` 里的库。
|
||||
|
||||
@ -32,9 +32,9 @@ cd stereo_bolt_delivery
|
||||
|
||||
```
|
||||
stereo_bolt_delivery/
|
||||
├── lib/ ← 算法库 + OpenCV 4.5.4 + 全部传递依赖（131 个 .so）
|
||||
├── lib/ ← 算法库 + OpenCV 4.5.0 + librknnrt（共 9 个 .so）
|
||||
├── include/stereo_bolt/ ← c_api.h（唯一对外头文件）
|
||||
├── weights/ ← best_1280_20260621.rknn（NPU 模型）
|
||||
├── weights/ ← best_obb_1024.rknn（NPU OBB 模型）
|
||||
├── calib/ ← 出厂标定 XML（0621 装配，baseline 482mm）
|
||||
├── config/ ← config.rk3588.12mp.yaml（兼容接口用）
|
||||
├── example/ ← 最小 C 示例 + CMakeLists
|
||||
@ -82,20 +82,31 @@ StereoBoltModelC model = {
|
||||
.data = rknn_bytes, // weights/*.rknn 的原始字节
|
||||
.size = rknn_size,
|
||||
.backend = SB_YOLO_BACKEND_RKNN,
|
||||
.imgsz = 1280,
|
||||
.imgsz = 1024,
|
||||
.conf = 0.5f
|
||||
};
|
||||
StereoBoltParamsC p = sb_default_params();
|
||||
p.wd_z_min_mm = 1200; // 工作距离下限（mm）
|
||||
p.wd_z_max_mm = 2800; // 工作距离上限（mm）
|
||||
p.wd_z_min_mm = 900; // 工作距离下限（mm）
|
||||
p.wd_z_max_mm = 4000; // 工作距离上限（mm）
|
||||
|
||||
StereoBoltCtx* ctx = sb_create_ex(&calib, &model, &p); // 只调一次（慢，载模型进 NPU）
|
||||
```
|
||||
|
||||
> 兼容方式：`sb_create("config/config.rk3588.12mp.yaml")`（读文件，需工作目录正确）。
|
||||
> 模型：`weights/best_1280_20260621.rknn`（精测 + 测距共用，imgsz 1280）。
|
||||
> 模型：`weights/best_obb_1024.rknn`（精测 + 测距共用，OBB imgsz 1024）。
|
||||
> 标定：`calib/stereo_calib_20260621_202857_ascii.xml`（0621 装配，baseline 482 mm）。
|
||||
|
||||
### 高度测量模式
|
||||
|
||||
默认 `height_from_plane: false`：高度 = 螺杆顶端到可见底端（**不跑平面拟合**，快 ~400ms/帧）。
|
||||
|
||||
如需平面模式（高度 = 顶端到支撑平面法向距离），在 config 中改为：
|
||||
```yaml
|
||||
measurement:
|
||||
height_from_plane: true
|
||||
```
|
||||
开启后每帧增加 300-550ms 平面拟合耗时。
|
||||
|
||||
---
|
||||
|
||||
## 6. 每帧调用
|
||||
@ -118,7 +129,7 @@ sb_free_bolt_module_result(&m); // 必须 free
|
||||
StereoBoltRangeSummaryC s;
|
||||
StereoBoltRangeBoltC bolts[64];
|
||||
sb_range_bolt_binned(ctx, lb, bw, bh, 0, rb, bw, bh, 0, 1, &s, bolts, 64);
|
||||
// s.distance_mm：最近螺栓到相机的距离（mm）
|
||||
// s.distance_mm：相机到可见螺栓的代表距离（mm）
|
||||
|
||||
// ── 退出 ─────────────────────────────────────────────────────────────────
|
||||
sb_destroy(ctx); // 只调一次
|
||||
@ -131,19 +142,15 @@ sb_destroy(ctx); // 只调一次
|
||||
|
||||
## 7. 编译示例程序（可选，用于集成验证）
|
||||
|
||||
示例代码读图用了 OpenCV，编译时需要 **OpenCV 头文件**（`lib/` 里只有 `.so`，没有 `.h`）。
|
||||
示例代码 `main.c` 是纯 C，**不依赖 OpenCV**（读 raw Mono8 文件 + C ABI 调用）。
|
||||
|
||||
```bash
|
||||
# 安装 OpenCV 头文件（只需 -dev 包；运行库用 lib/ 里的，不用 apt 的 .so）
|
||||
sudo apt install libopencv-dev
|
||||
|
||||
# 编译
|
||||
cd example
|
||||
cmake -S . -B build -DSB_ROOT="$(cd .. && pwd)"
|
||||
cmake --build build
|
||||
```
|
||||
|
||||
> **生产代码不需要此步骤**：你自己的调用端只用 `c_api.h`，不引用任何 OpenCV 头，
|
||||
> **生产代码同理**：你自己的调用端只用 `c_api.h`，
|
||||
> 相机 buffer 直接喂给 `sb_process_bolt_module_buffers`，全程无 OpenCV 依赖。
|
||||
|
||||
---
|
||||
@ -154,20 +161,13 @@ cmake --build build
|
||||
# 在 stereo_bolt_delivery/ 根目录执行（使 lib/ 路径正确）
|
||||
export LD_LIBRARY_PATH="$(pwd)/lib:$LD_LIBRARY_PATH"
|
||||
|
||||
# 精测 demo（需要左右 12MP 图，4096×3000，与标定分辨率一致）
|
||||
# 精测 demo（需要左右 12MP raw Mono8，4096×3000）
|
||||
./example/build/bolt_demo \
|
||||
calib/stereo_calib_20260621_202857_ascii.xml \
|
||||
weights/best_1280_20260621.rknn \
|
||||
/path/to/left.bmp /path/to/right.bmp 6
|
||||
|
||||
# 测距 demo
|
||||
./example/build/range_demo \
|
||||
calib/stereo_calib_20260621_202857_ascii.xml \
|
||||
weights/best_1280_20260621.rknn \
|
||||
/path/to/left.bmp /path/to/right.bmp
|
||||
config/config.rk3588.12mp.yaml \
|
||||
/path/to/left.raw /path/to/right.raw 4096 3000 8
|
||||
```
|
||||
|
||||
板上实测吞吐：**精测 ~582 ms/帧 ≈ 1.7 Hz**、**测距 ~238 ms/帧 ≈ 4.2 Hz**（0621 装配，帧 1）。
|
||||
板上实测吞吐：**精测 ~400 ms/帧 ≈ 2.5 Hz**（height_from_plane=false）、**测距 ~238 ms/帧 ≈ 4.2 Hz**（0621 装配）。
|
||||
|
||||
---
|
||||
|
||||
|
||||
@ -1,12 +1,14 @@
|
||||
# ============================================================
|
||||
# (C++ port)
|
||||
#
|
||||
# Python e:/02_Modules/StereoVisionBoltMeasurement/config.yaml
|
||||
#
|
||||
# Python paths
|
||||
# RK3588 delivery config — OBB model, baseline 482mm
|
||||
# Only used by sb_create(); sb_create_ex() ignores this file.
|
||||
# ============================================================
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- working distance ----------
|
||||
working_distance:
|
||||
z_min_mm: 900
|
||||
z_max_mm: 4000
|
||||
|
||||
# ---------- image ----------
|
||||
image:
|
||||
width: 4096
|
||||
height: 3000
|
||||
@ -14,35 +16,32 @@ image:
|
||||
expected_dtype: "uint8"
|
||||
allowed_extensions: [".tiff", ".tif", ".bmp", ".png"]
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- image validation ----------
|
||||
image_validation:
|
||||
min_max_value: 10
|
||||
max_saturation_ratio: 0.20
|
||||
|
||||
# ---------- ChArUco ----------
|
||||
# ---------- ChArUco ----------
|
||||
charuco:
|
||||
rows: 9
|
||||
cols: 9
|
||||
square_length_mm: 50.0
|
||||
marker_length_mm: 37.0
|
||||
dict_id: 11 # DICT_6X6_1000
|
||||
dict_id: 11
|
||||
min_corners_per_image: 30
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- calibration ----------
|
||||
calibration:
|
||||
source: "xml"
|
||||
xml_path: "calib/stereo_calib.xml" # 0621 新装配 baseline 482mm (ChArUco)
|
||||
xml_path: "calib/stereo_calib.xml"
|
||||
min_image_pairs: 15
|
||||
max_skip_ratio: 0.30
|
||||
max_single_rms: 0.40 # : 12MP RMS=0.373(5MP 0.19)
|
||||
# 0.40 ;0.373 0.1px ,,
|
||||
# <0.20
|
||||
max_single_rms: 0.40
|
||||
max_stereo_rms: 0.80
|
||||
expected_baseline_range: [80, 600]
|
||||
use_fix_intrinsic: true
|
||||
|
||||
# ---------- ----------
|
||||
# alpha=1.0 CLAUDE.md #1
|
||||
# ---------- rectification ----------
|
||||
rectification:
|
||||
alpha: 1.0
|
||||
interpolation: "cubic"
|
||||
@ -53,9 +52,7 @@ rectification:
|
||||
max_epipolar_error_pixel: 5.0
|
||||
min_valid_roi_ratio: 0.25
|
||||
|
||||
# ---------- SGBM ----------
|
||||
# min_disparity / num_disparities f_rectB
|
||||
# f_rect3190, B235mmalpha=1.0
|
||||
# ---------- SGBM ----------
|
||||
sgbm:
|
||||
min_disparity: 288
|
||||
num_disparities: 736
|
||||
@ -69,24 +66,18 @@ sgbm:
|
||||
pre_filter_cap: 63
|
||||
mode: "SGBM_3WAY"
|
||||
|
||||
# ---------- WLS ----------
|
||||
# ---------- WLS ----------
|
||||
wls:
|
||||
lambda_value: 8000.0
|
||||
sigma_color: 1.5
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- disparity validation ----------
|
||||
disparity_validation:
|
||||
min_valid_pixel_ratio: 0.10
|
||||
min_disparity_range: 50
|
||||
max_nan_ratio: 0.90
|
||||
|
||||
# ---------- ----------
|
||||
# z_min_mm / z_max_mm / expected_wd_range are FALLBACK only when run_pipeline /
|
||||
# c_api are wired (the standard path) SceneRuntime derives the real reachable
|
||||
# Z range from (f_rect, baseline, sgbm.min_disparity, sgbm.num_disparities) and
|
||||
# overrides these values per frame. See docs/L_100_SCENE_HANDOFF.md 6.2 and
|
||||
# include/stereo_bolt/scene_runtime.hpp. Keep the fallback values conservative
|
||||
# enough to cover every supported workpiece distance.
|
||||
# ---------- pointcloud ----------
|
||||
pointcloud:
|
||||
z_min_mm: 600
|
||||
z_max_mm: 3000
|
||||
@ -108,13 +99,7 @@ pointcloud:
|
||||
dilate_px: 100
|
||||
min_area_ratio: 0.02
|
||||
|
||||
# ---------- 2D ----------
|
||||
# mask_method: foam_mask( mask)
|
||||
# "brightness" + (;
|
||||
# rectify ROI 0, mask ROI )
|
||||
# "ransac" dense xyz_map RANSAC ,
|
||||
# " < ransac.distance_thresh_mm" mask
|
||||
# "brightness" parity_tests , "ransac"
|
||||
# ---------- 2D detection ----------
|
||||
bolt_detect_2d:
|
||||
mask_method: "ransac"
|
||||
foam_brightness_threshold: 70
|
||||
@ -125,99 +110,75 @@ bolt_detect_2d:
|
||||
bolt_min_area_px: 800
|
||||
min_bolts: 1
|
||||
max_bolts: 0
|
||||
bolt_exclude_dilate_px: 0 # 0 CLAUDE.md #5
|
||||
bolt_exclude_dilate_px: 0
|
||||
ransac:
|
||||
distance_thresh_mm: 8.0 # < inlier(3
|
||||
# frame 100 residual_std2.6 mm)
|
||||
distance_thresh_mm: 8.0
|
||||
max_iterations: 200
|
||||
min_inlier_ratio: 0.15 # inlier
|
||||
sample_stride: 4 # xyz_map ( 44 1 RANSAC )
|
||||
morph_close_kernel_px: 9 # mask +
|
||||
min_inlier_ratio: 0.15
|
||||
sample_stride: 4
|
||||
morph_close_kernel_px: 9
|
||||
|
||||
# ---------- (SVD on foam mask) ----------
|
||||
# ---------- plane ----------
|
||||
plane:
|
||||
max_residual_std_mm: 15.0
|
||||
max_normal_to_axis_deg: 60
|
||||
outlier_rejection_iterations: 5
|
||||
outlier_mad_k: 2.5
|
||||
|
||||
# ---------- ----------
|
||||
# plane fit bolt extract bolt 3D
|
||||
# inlier OBB, OBB margin_mm WARN
|
||||
# margin_mm bolt.expected_diameter_mm,
|
||||
# /
|
||||
# ---------- support gate ----------
|
||||
support_gate:
|
||||
enabled: true
|
||||
margin_mm: 10.0
|
||||
|
||||
# ---------- ----------
|
||||
# (run_pipeline / c_api) bolt bbox_projection h_est,
|
||||
# extract height max(h_est 1.3, h_est + 20 mm),
|
||||
# validate_measurements |measured - h_est| < bolt.height_tolerance_mm
|
||||
# max_height_mm / extract_height_filter_mm fallback
|
||||
# bbox_projection h_est
|
||||
# (expected_diameter_mm),
|
||||
# ---------- bolt ----------
|
||||
bolt:
|
||||
min_height_mm: 5.0
|
||||
max_height_mm: 250.0 # fallback ceiling (used only when h_est is unavailable)
|
||||
extract_height_filter_mm: 200.0 # fallback filter (same condition)
|
||||
height_tolerance_mm: 60.0 # |measured - h_est| ; validate_measurements
|
||||
max_height_mm: 250.0
|
||||
extract_height_filter_mm: 200.0
|
||||
height_tolerance_mm: 60.0
|
||||
expected_diameter_mm: 16.0
|
||||
min_points_per_bolt: 50
|
||||
max_axis_plane_angle_deg: 30
|
||||
extract_fallback: "bbox_projection" # 'none' | 'bbox_projection'; YOLO bbox + , SGBM /
|
||||
extract_fallback: "bbox_projection"
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- measurement ----------
|
||||
measurement:
|
||||
top_extraction_method: "percentile_on_axis"
|
||||
top_percentile: 0.99
|
||||
foot_rim_correction: false # 0621 决定: 关 rim(圆顶无领圈杆上 rim 修正会过冲)
|
||||
height_from_plane: false
|
||||
plane_use_sgbm: true
|
||||
plane_sgbm_scale: 0.5
|
||||
plane_max_samples: 40000
|
||||
|
||||
# ---------- Diagnostics ----------
|
||||
# ---------- diagnostics ----------
|
||||
diagnostics:
|
||||
enabled: true
|
||||
blind_strip_warn_ratio: 0.25
|
||||
min_roi_pointcloud_coverage_ratio: 0.001
|
||||
|
||||
# ---------- YOLO ----------
|
||||
# C++ ONNX Python best_v4_finetune.pt .onnx
|
||||
# dilate (50/30),
|
||||
# scene_runtime.cpp pixels_per_mm(= f / Z_repr),
|
||||
# /
|
||||
# ---------- YOLO ----------
|
||||
yolo:
|
||||
enabled: true
|
||||
# 统一模型: 精测(sb_process_bolt_module_*)与测距(sb_range_bolt_binned)共用 weights/best.rknn。
|
||||
# 当前交付模型为 960 输入；文件名保持稳定，模型更新时只替换 weights/best.rknn。
|
||||
model_path: "weights/best.rknn"
|
||||
backend: "rknn"
|
||||
imgsz: 960
|
||||
task: "auto"
|
||||
imgsz: 1024
|
||||
conf: 0.5
|
||||
dead_zone_min_valid_pts: 50
|
||||
dead_zone_bbox_dilate_mm: 24.0 # = expected_diameter_mm 1.5; valid_xyz bbox ,/
|
||||
foam_bbox_dilate_mm: 16.0 # = expected_diameter_mm 1.0; foam_mask YOLO bbox
|
||||
|
||||
# Experimental: keep sparse-global YOLO bolts only when right YOLO + local LR check pass.
|
||||
dead_zone_bbox_dilate_mm: 24.0
|
||||
foam_bbox_dilate_mm: 16.0
|
||||
local_stereo_fallback:
|
||||
enabled: true
|
||||
min_valid_points: 50
|
||||
|
||||
# ---------- working distance (physical, rig-level) ----------
|
||||
# 0621 新装配 B=482mm: 精测视差带从 WD + 标定自推导 (disp = f*B/Z), 换基线无需重调像素。
|
||||
# 旧固定 sgbm 像素带(288/736)是 200mm 装配的, 对 482mm 会 NEAR-clip 近处螺柱。
|
||||
# 注意: 需 .so 含视差带解耦(commit dc696d8 起); 旧 .so 不读此块仍用固定带。
|
||||
working_distance:
|
||||
z_min_mm: 1200
|
||||
z_max_mm: 2800
|
||||
|
||||
# ---------- ranging (binned) ----------
|
||||
# 测距视差带也按 0621 rig 的 WD; 物理 LRC 门(mm)随距离自紧。
|
||||
ranging:
|
||||
z_min_mm: 1300
|
||||
z_max_mm: 3600
|
||||
z_min_mm: 900
|
||||
z_max_mm: 4000
|
||||
lrc_max_mm: 2.5
|
||||
lrc_trusted_mm: 1.2
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- evaluation ----------
|
||||
evaluation:
|
||||
height_max_mm: 2.0
|
||||
height_p95_mm: 1.5
|
||||
@ -226,24 +187,23 @@ evaluation:
|
||||
repeatability_std_max_mm: 1.0
|
||||
matching_max_distance_mm: 50.0
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- pipeline ----------
|
||||
pipeline:
|
||||
fail_fast: true
|
||||
resume_from_checkpoint: true
|
||||
parallel_frames: false
|
||||
save_intermediate: false
|
||||
|
||||
# ---------- ----------
|
||||
# ---------- logging ----------
|
||||
logging:
|
||||
level: "INFO"
|
||||
log_to_file: true
|
||||
log_file: "outputs/logs/pipeline.log"
|
||||
|
||||
# ---------- ----------
|
||||
# dataset/ , Python
|
||||
# ---------- paths ----------
|
||||
paths:
|
||||
calibration_dir: "calib"
|
||||
test_dir: "dataset/test"
|
||||
groundtruth_csv: "dataset/groundtruth.csv"
|
||||
output_dir: "outputs_macro257"
|
||||
stereo_params_yaml: "outputs_macro257/stereo_params.yaml"
|
||||
output_dir: "outputs"
|
||||
stereo_params_yaml: "outputs/stereo_params.yaml"
|
||||
|
||||
@ -1,21 +1,20 @@
|
||||
# Minimal downstream build: link the prebuilt libstereo_bolt.so via c_api.h only.
|
||||
# No OpenCV / RKNN headers needed here — the C ABI hides all C++/OpenCV types.
|
||||
# Minimal downstream build — links the prebuilt libstereo_bolt.so.
|
||||
# bolt_demo (main.c) -> sb_create + sb_process_bolt_module_buffers
|
||||
#
|
||||
# OpenCV here is NOT required by the demo — it uses only C ABI + raw Mono8
|
||||
# buffers. OpenCV is a transitive runtime dep of libstereo_bolt.so only.
|
||||
cmake_minimum_required(VERSION 3.16)
|
||||
project(bolt_demo LANGUAGES C)
|
||||
|
||||
# Point at the unpacked delivery dir (contains include/ and lib/).
|
||||
set(SB_ROOT "${CMAKE_CURRENT_LIST_DIR}/.." CACHE PATH "unpacked libstereo_bolt delivery root")
|
||||
|
||||
add_executable(bolt_demo main.c)
|
||||
target_include_directories(bolt_demo PRIVATE "${SB_ROOT}/include")
|
||||
target_link_directories(bolt_demo PRIVATE "${SB_ROOT}/lib")
|
||||
target_link_libraries(bolt_demo PRIVATE stereo_bolt)
|
||||
target_link_options(bolt_demo PRIVATE "LINKER:--allow-shlib-undefined")
|
||||
|
||||
# libstereo_bolt.so pulls in OpenCV + librknnrt transitively. You do NOT need
|
||||
# those at LINK time — defer their resolution to runtime so you can link with
|
||||
# just -lstereo_bolt. (Without this, ld follows the NEEDED chain and fails with
|
||||
# "undefined reference to rknn_*/cv::*".)
|
||||
target_link_options(bolt_demo PRIVATE "LINKER:--allow-shlib-undefined")
|
||||
|
||||
# Runtime: LD_LIBRARY_PATH must include the dirs holding
|
||||
# libstereo_bolt.so + libopencv_*.so (matching ABI_FINGERPRINT.txt) + librknnrt.so
|
||||
# Runtime: LD_LIBRARY_PATH must include ../lib (holds libstereo_bolt.so +
|
||||
# OpenCV 4.5.0 + librknnrt.so). Example:
|
||||
# LD_LIBRARY_PATH=../lib ./build/bolt_demo \
|
||||
# ../config/config.rk3588.12mp.yaml L.raw R.raw 4096 3000 8
|
||||
|
||||
@ -184,7 +184,7 @@ typedef struct {
|
||||
double wd_z_max_mm;
|
||||
double sgbm_min_disparity; /* fixed pixel band (used when wd_* unset) */
|
||||
double sgbm_num_disparities;
|
||||
int foot_rim_correction; /* -1 = built-in default, 0 = off, 1 = on */
|
||||
int foot_rim_correction; /* -1 = built-in default (off), 0 = off, 1 = on */
|
||||
|
||||
/* --- binned ranging path (sb_range_bolt_binned) --- */
|
||||
double rng_z_min_mm;
|
||||
@ -259,16 +259,16 @@ typedef struct {
|
||||
double distance_mm; /* straight-line distance, left optical centre -> bolt */
|
||||
int left_x; /* bbox centre in the rectified-left (binned) image */
|
||||
int left_y;
|
||||
int right_x; /* NCC correspondence in the rectified-right (binned) image */
|
||||
int right_y; /* -> the "same bolt" evidence; mark to verify */
|
||||
double ncc_score; /* match score */
|
||||
double lrc_px; /* left-right consistency residual (px); small == same point */
|
||||
int right_x; /* matched point in the rectified-right (binned) image */
|
||||
int right_y; /* OBB-axis route: right OBB axis point; NCC fallback: correspondence */
|
||||
double ncc_score; /* detector/match score; ABI name kept for compatibility */
|
||||
double lrc_px; /* OBB disparity stddev or NCC LRC residual; smaller is better */
|
||||
int confidence; /* 0 = trusted (strong + self-consistent), 1 = suspect */
|
||||
} StereoBoltRangeBoltC;
|
||||
|
||||
typedef struct {
|
||||
int found; /* 1 if >= 1 bolt was detected and NCC/LRC-verified */
|
||||
double distance_mm; /* MEDIAN straight-line distance over visible bolts */
|
||||
int found; /* 1 if >= 1 bolt was detected and paired/matched */
|
||||
double distance_mm; /* representative straight-line distance over visible bolts */
|
||||
int bolt_count; /* total visible bolts (may exceed the number written to bolts[]) */
|
||||
char status[32]; /* "ok" | "no_detection" | "no_valid_match" (why found==0) */
|
||||
} StereoBoltRangeSummaryC;
|
||||
@ -281,7 +281,7 @@ typedef struct {
|
||||
* - The binned size may be ANY clean downscale of the calibrated size
|
||||
* (config image.width/height); the binned intrinsics are derived internally
|
||||
* (no separate binned calibration needed). 2x2 binning is the intended case.
|
||||
* - out : summary (found / median distance / visible count). Required.
|
||||
* - out : summary (found / representative distance / visible count). Required.
|
||||
* - bolts : optional caller-allocated array (capacity max_bolts); filled with
|
||||
* per-bolt detail (distance + left/right match points), near -> far.
|
||||
* Pass NULL / max_bolts=0 to skip. The caller owns it; nothing to free.
|
||||
|
||||
Binary file not shown.
Binary file not shown.
@ -4,17 +4,53 @@
|
||||
TEMPLATE = subdirs
|
||||
|
||||
# SDK（需要先编译）
|
||||
SUBDIRS += ../SDK/Device/EpicEye/EpicEyeSDK.pro
|
||||
isEmpty(TARGET_APP) {
|
||||
SUBDIRS += ../SDK/Device/EpicEye/EpicEyeSDK.pro
|
||||
|
||||
SUBDIRS += \
|
||||
VrEyeDevice/VrEyeDevice.pro \
|
||||
EpicEyeDevice/EpicEyeDevice.pro \
|
||||
GalaxyDevice/GalaxyDevice.pro \
|
||||
HikDevice/HikDevice.pro \
|
||||
MvsDevice/MvsDevice.pro \
|
||||
GlLineLaserDevice/GlLineLaserDevice.pro
|
||||
SUBDIRS += \
|
||||
VrEyeDevice/VrEyeDevice.pro \
|
||||
EpicEyeDevice/EpicEyeDevice.pro \
|
||||
GalaxyDevice/GalaxyDevice.pro \
|
||||
HikDevice/HikDevice.pro \
|
||||
MvsDevice/MvsDevice.pro \
|
||||
GlLineLaserDevice/GlLineLaserDevice.pro
|
||||
} else {
|
||||
!equals(TARGET_APP, "BeltTearing") {
|
||||
SUBDIRS += VrEyeDevice/VrEyeDevice.pro
|
||||
}
|
||||
|
||||
contains(TARGET_APP, "^(WorkpiecePosition|WorkpieceProject)$") {
|
||||
SUBDIRS += ../SDK/Device/EpicEye/EpicEyeSDK.pro
|
||||
SUBDIRS += EpicEyeDevice/EpicEyeDevice.pro
|
||||
SUBDIRS += VrEyeDevice/VrEyeDevice.pro
|
||||
}
|
||||
|
||||
equals(TARGET_APP, "BinocularMark") {
|
||||
SUBDIRS += GalaxyDevice/GalaxyDevice.pro
|
||||
}
|
||||
|
||||
contains(TARGET_APP, "^(DroneScrewServer|DroneScrewbolt)$") {
|
||||
SUBDIRS += MvsDevice/MvsDevice.pro
|
||||
}
|
||||
|
||||
equals(TARGET_APP, "BagThreadPosition") {
|
||||
SUBDIRS += VrEyeDevice/VrEyeDevice.pro
|
||||
SUBDIRS += GlLineLaserDevice/GlLineLaserDevice.pro
|
||||
}
|
||||
|
||||
equals(TARGET_APP, "TunnelChannel") {
|
||||
SUBDIRS += VrEyeDevice/VrEyeDevice.pro
|
||||
SUBDIRS += HikDevice/HikDevice.pro
|
||||
}
|
||||
|
||||
contains(TARGET_APP, "^(BeltTearing|WorkpieceSplice|GrabBag|LapWeld|Workpiece|ParticleSize|ScrewPosition|WorkpieceHole|DiscHolePose|TireHolePose|StatorPosition|RodAndBarPosition|RodWeldSeam|HoleDetection|HolePitPosition|WheelMeasure)$") {
|
||||
SUBDIRS += VrEyeDevice/VrEyeDevice.pro
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
win32-msvc {
|
||||
SUBDIRS += RsLidarDevice/RsLidarDevice.pro
|
||||
}
|
||||
|
||||
SUBDIRS = $$unique(SUBDIRS)
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user