finish SORT Tracker V0.1, czc
Signed-off-by: CZC-123 <73985910+CZC-123@users.noreply.github.com>
This commit is contained in:
CZC-123
parent
ae3509f836
commit
0e539348d9
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@ -8,7 +8,7 @@ add_definitions(-DAPI_EXPORTS)
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set(CMAKE_BUILD_TYPE "Release")
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## JETSON, X86_CUDA, X86_INTEL
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## JETSON, X86_CUDA
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message(STATUS "System:${CMAKE_HOST_SYSTEM_PROCESSOR}")
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if(NOT DEFINED PLATFORM)
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message(FATAL_ERROR "PLATFORM NOT SPECIFIED!")
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@ -53,6 +53,7 @@ endif()
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add_definitions(-DWITH_OCV470)
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find_package(OpenCV 4.7 REQUIRED)
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find_package(Eigen3 REQUIRED)
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message(STATUS "OpenCV library status:")
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message(STATUS " version: ${OpenCV_VERSION}")
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message(STATUS " libraries: ${OpenCV_LIBS}")
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@ -60,6 +61,7 @@ message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}")
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include_directories(${CMAKE_CURRENT_SOURCE_DIR}/include)
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include_directories(${EIGEN3_INCLUDE_DIRS})
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include_directories(
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${CMAKE_CURRENT_SOURCE_DIR}/gimbal_ctrl/IOs/serial/include
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${CMAKE_CURRENT_SOURCE_DIR}/gimbal_ctrl/driver/src/FIFO
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@ -185,7 +187,7 @@ list(APPEND spirecv_SRCS ${ALG_SRC_FILES})
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endif()
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if(USE_CUDA) # PLATFORM_X86_CUDA & PLATFORM_JETSON
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if(USE_CUDA)
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# CUDA
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include_directories(/usr/local/cuda/include)
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link_directories(/usr/local/cuda/lib64)
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@ -197,11 +199,24 @@ if(USE_CUDA) # PLATFORM_X86_CUDA & PLATFORM_JETSON
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target_link_libraries(sv_yoloplugins nvinfer cudart)
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cuda_add_library(sv_world SHARED ${spirecv_SRCS})
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if(USE_GSTREAMER)
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target_link_libraries(
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sv_world ${OpenCV_LIBS}
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sv_yoloplugins sv_gimbal
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nvinfer cudart
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gstrtspserver-1.0
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)
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else()
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target_link_libraries(
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sv_world ${OpenCV_LIBS}
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sv_yoloplugins sv_gimbal
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nvinfer cudart
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)
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endif()
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if(USE_FFMPEG)
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target_link_libraries(sv_world ${FFMPEG_LIBS} fmt)
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endif()
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set(
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YOLO_SRCS
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@ -217,21 +232,19 @@ if(USE_CUDA) # PLATFORM_X86_CUDA & PLATFORM_JETSON
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cuda_add_executable(SpireCVSeg samples/SpireCVSeg.cpp ${YOLO_SRCS})
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target_link_libraries(SpireCVSeg sv_world)
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elseif(PLATFORM STREQUAL "X86_INTEL") # Links to Intel-OpenVINO libraries here
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elseif(PLATFORM STREQUAL "X86_INTEL")
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add_library(sv_world SHARED ${spirecv_SRCS})
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target_link_libraries(
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sv_world ${OpenCV_LIBS}
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sv_gimbal
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)
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endif()
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if(USE_GSTREAMER)
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target_link_libraries(sv_world gstrtspserver-1.0)
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endif()
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if(USE_FFMPEG)
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target_link_libraries(sv_world ${FFMPEG_LIBS} fmt)
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endif()
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endif()
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#demo
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add_executable(ArucoDetection samples/demo/aruco_detection.cpp)
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@ -268,6 +281,9 @@ target_link_libraries(GimbalUdpDetectionInfoSender sv_world)
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add_executable(EvalFpsOnVideo samples/test/eval_fps_on_video.cpp)
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target_link_libraries(EvalFpsOnVideo sv_world)
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add_executable(SortTracker samples/demo/common_object_tracking_SORT.cpp samples/demo/SORT_2.cpp)
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target_link_libraries(SortTracker sv_world)
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include_directories(${CMAKE_CURRENT_SOURCE_DIR}/samples/calib)
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add_executable(CameraCalibrarion samples/calib/calibrate_camera_charuco.cpp)
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target_link_libraries(CameraCalibrarion ${OpenCV_LIBS})
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@ -0,0 +1,354 @@
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#include "SORT_2.h"
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#include <cmath>
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using namespace std;
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using namespace Eigen;
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/*
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void SORT::update(vector<VectorXd> detections) {
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//allocate the memory for the vector in advance
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int numDetections = detections.size();
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detections.reserve(numDetections);
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if (! tracklets_.size() || ! detections.size()){
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for (int i = 0; i < detections.size(); i++)
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{
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//if(find(matches.begin(), matches.end(),make_pair(-1, i)) == matches.end())
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if (detections[i](4) == -1) {
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Tracklet tracklet;
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tracklet.id = nextTrackletId_++;//
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tracklet.bbox.segment<4>(0) = detections[i].segment<4>(0);
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tracklet.age = 0;
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tracklet.hits = 1;
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tracklet.misses = 0;
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//initate the motion
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//pair<VectorXd,MatrixXd> motion = kf.initiate(bbox_xywh_to_wyah(detect_mat[i]));
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tracklets_.push_back(tracklet);
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}
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}
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}
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else{
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// create new tracklets for unmatched detections
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for (int i = 0; i < detections.size(); i++)
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{
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if (detections[i](4)== -1) {
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Tracklet tracklet;
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tracklet.id = nextTrackletId_++;//
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tracklet.bbox.segment<4>(0) = detections[i].segment<4>(0);
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tracklet.age = 0;
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tracklet.hits = 1;
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tracklet.misses = 0;
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tracklets_.push_back(tracklet);
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}
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}
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}
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}*/
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KalmanFilter::KalmanFilter(){
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chi2inv95_ << 3.8415, 5.9915, 7.8147, 9.4877, 11.070, 12.592, 14.067, 15.507, 16.919;
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/*
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F_ << 1, 0, 0, 0, 1, 0, 0, 0,
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0, 1, 0, 0, 0, 1, 0, 0,
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0, 0, 1, 0, 0, 0, 1, 0,
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0, 0, 0, 1, 0, 0, 0, 1,
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0, 0, 0, 0, 1, 0, 0, 0,
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0, 0, 0, 0, 0, 1, 0, 0,
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0, 0, 0, 0, 0, 0, 1, 0,
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0, 0, 0, 0, 0, 0, 0, 1;
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H_ << 1, 0, 0, 0, 0, 0, 0, 0,
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0, 1, 0, 0, 0, 0, 0, 0,
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0, 0, 1, 0, 0, 0, 0, 0,
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0, 0, 0, 1, 0, 0, 0, 0;
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*/
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F_ = MatrixXd::Identity(8, 8);
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for (int i = 0; i < 4; i++) {
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F_(i, i + 4) = 1;
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}
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H_ = MatrixXd::Identity(4, 8);
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std_weight_position = 1. / 20;
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std_weight_vel = 1. / 160;
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}
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pair<Matrix<double,8,1>,Matrix<double,8,8>> KalmanFilter::initiate(Vector4d & bbox){
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Matrix<double,8,1> mean;
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mean << bbox(0), bbox(1), bbox(2)/bbox(3), bbox(3), 0, 0, 0, 0;
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//cout<<"the a is:"<<bbox(2)/bbox(3)<<endl;
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VectorXd stds(8);
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stds << 2 * std_weight_position * mean(3), 2 * std_weight_position * mean(3), 0.01, 2 * std_weight_position * mean(3), 10 * std_weight_vel * mean(3), 10 * std_weight_vel * mean(3), 1e-5, 10 * std_weight_vel * mean(3);
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MatrixXd squared = stds.array().square();
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Matrix<double, 8,8> covariances;
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covariances = squared.asDiagonal();
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return make_pair(mean, covariances);
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}
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pair<Matrix<double,8,1>,Matrix<double,8,8>> KalmanFilter::update(Matrix<double, 8, 1> mean, Matrix<double, 8, 8> covariances, sv::Box & box) {
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MatrixXd R_;
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Vector4d stds;
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stds << std_weight_position * mean(3), std_weight_position* mean(3), 0.1, std_weight_position* mean(3);
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MatrixXd squared = stds.array().square();
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R_ = squared.asDiagonal();
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MatrixXd S = H_ * covariances * H_.transpose()+R_;
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MatrixXd Kalman_gain = covariances * H_.transpose() * S.inverse();
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VectorXd measurement(4);
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measurement << box.x1, box.y1, (box.x2-box.x1)/(box.y2-box.y1), box.y2-box.y1;
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Matrix<double, 8, 1> new_mean = mean + Kalman_gain * (measurement - H_ * mean);
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Matrix<double, 8, 8> new_covariances = (MatrixXd::Identity(8, 8) - Kalman_gain * H_) * covariances;
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return make_pair(new_mean, new_covariances);
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}
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pair<Matrix<double, 8, 1>, Matrix<double, 8, 8>> KalmanFilter::predict(Matrix<double, 8, 1>mean, Matrix<double, 8, 8>covariances) {
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VectorXd stds(8);
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stds << std_weight_position * mean(3), std_weight_position* mean(3), 0.01, std_weight_position* mean(3), std_weight_vel* mean(3), std_weight_vel* mean(3), 1e-5, std_weight_vel* mean(3);
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MatrixXd squared = stds.array().square();
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MatrixXd Q_ = squared.asDiagonal();
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Matrix<double,8,1> pre_mean = F_ * mean;
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Matrix<double,8,8> pre_cov = F_ * covariances * F_.transpose()+Q_;
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return make_pair(pre_mean, pre_cov);
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}
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void SORT::update(sv::TargetsInFrame & tgts){
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KalmanFilter kf;
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// if (! tracklets_.size() || ! tgts.targets.size())
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if (! tracklets_.size())
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{
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Vector4d bbox;
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for (int i = 0; i <tgts.targets.size(); i++)
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{
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//if(find(matches.begin(), matches.end(),make_pair(-1, i)) == matches.end())
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//if (tgts.targets[i].tracked_id == 0) {
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sv::Box box;
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tgts.targets[i].getBox(box);
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Tracklet tracklet;
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tracklet.id = ++nextTrackletId_;//
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cout<<tracklet.id<<endl;
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tgts.targets[i].tracked_id = nextTrackletId_;
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//bbox << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1;
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tracklet.bbox << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1;//x,y,w,h
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tracklet.age = 0;
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tracklet.hits = 1;
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tracklet.misses = 0;
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//initate the motion
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pair<Matrix<double,8,1>,Matrix<double,8,8>> motion = kf.initiate(tracklet.bbox);
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//cout<<"mean:"<<motion.first<<endl;
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//cout<<"mean:"<<tracklet.mean<<endl;
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tracklet.mean=motion.first;
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tracklet.covariance = motion.second;
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tracklets_.push_back(tracklet);
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//}
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}
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}
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else{
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for (int i = 0; i < tgts.targets.size(); i++)
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{
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tgts.targets[i].tracked_id = 0;
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}
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// vector<int> match_det(100,-1);
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array<int,100> match_det;
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match_det.fill(-1);
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//predict the next state of each tracklet
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for (auto& tracklet : tracklets_) {
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tracklet.age++;
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pair<Matrix<double, 8, 1>, Matrix<double, 8, 8>> motion = kf.predict(tracklet.mean, tracklet.covariance);
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tracklet.bbox << motion.first(0),motion.first(1),motion.first(2)*motion.first(3),motion.first(3);
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tracklet.mean = motion.first;
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tracklet.covariance = motion.second;
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}
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//Match the detections to the existing tracklets
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cout<<"the num of targets: "<<tgts.targets.size()<<endl;
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cout<<"the num of tracklets: "<<tracklets_.size()<<endl;
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vector<vector<double>> iouMatrix(tracklets_.size(), vector<double> (tgts.targets.size(), 0)); //
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for (int i = 0; i <tracklets_.size(); i++) {
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for (int j = 0; j < tgts.targets.size(); j++) {
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sv::Box box;
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tgts.targets[j].getBox(box);
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iouMatrix[i][j] = iou(tracklets_[i], box);
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}
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}
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vector<pair<int,int>> matches = hungarian(iouMatrix);
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for (auto& match : matches) {
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int trackletIndex = match.first;
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int detectionIndex = match.second;
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// cout<<"trackletIndex:"<<match.first<<endl;
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// cout<<"detectionIndex:"<<match.second<<endl;
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// cout<<"iou_eles:"<<iouMatrix[match.first][match.second]<<endl;
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if (trackletIndex>=0 && detectionIndex>=0) {
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if(iouMatrix[match.first][match.second]>=0) {
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sv::Box box;
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tgts.targets[detectionIndex].getBox(box);
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tracklets_[trackletIndex].age = 0;
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tracklets_[trackletIndex].hits++;
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tracklets_[trackletIndex].bbox << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1;
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auto[mean,covariance]=kf.update(tracklets_[trackletIndex].mean,tracklets_[trackletIndex].covariance, box);
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tracklets_[trackletIndex].mean = mean;
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tracklets_[trackletIndex].covariance = covariance;
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tgts.targets[detectionIndex].tracked_id = tracklets_[trackletIndex].id;
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match_det[detectionIndex]=detectionIndex;
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}
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}
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}
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// create new tracklets for unmatched detections
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for (int i = 0; i < tgts.targets.size(); i++)
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{
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if (match_det[i]==-1) {
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sv::Box box;
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tgts.targets[i].getBox(box);
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Tracklet tracklet;
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tracklet.id = ++nextTrackletId_;//
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//Vector4d bbox;
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//bbox << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1;
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//tracklet.bboxes.push_back(bbox);
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tracklet.bbox << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1;
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tracklet.age = 0;
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tracklet.hits = 1;
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tracklet.misses = 0;
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auto [new_mean,new_covariance] = kf.initiate(tracklet.bbox);
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tracklet.mean = new_mean;
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tracklet.covariance = new_covariance;
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tgts.targets[i].tracked_id = nextTrackletId_;
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tracklets_.push_back(tracklet);
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}
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}
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}
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/*
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vector<Tracklet> newTracklets;
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for (auto& tracklet : tracklets_) {
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if (tracklet.age < maxAge_ || tracklet.hits >= minHits_) {
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newTracklets.push_back(tracklet);
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}
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}
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tracklets_ = newTracklets;
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*/
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}
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vector<Tracklet> SORT::getTracklets() const{
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return tracklets_;
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}
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double SORT::iou(Tracklet & tracklet, sv::Box & box) {
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double trackletX1 = tracklet.bbox(0);
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double trackletY1 = tracklet.bbox(1);
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double trackletX2 = tracklet.bbox(0)+tracklet.bbox(2);
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double trackletY2 = tracklet.bbox(1)+tracklet.bbox(3);
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/*
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double trackletX1 = tracklet.bboxes.back()(0);
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double trackletY1 = tracklet.bboxes.back()(1);
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double trackletX2 = tracklet.bboxes.back()(0)+tracklet.bboxes.back()(2);
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double trackletY2 = tracklet.bboxes.back()(1)+tracklet.bboxes.back()(3);
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double trackletX1 = tracklet.x;
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double trackletY1 = tracklet.y;
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double trackletX2 = tracklet.x+tracklet.w;
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double trackletY2 = tracklet.y+tracklet.h;
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*/
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double detectionX1 = box.x1;
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double detectionY1 = box.y1;
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double detectionX2 = box.x2;
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double detectionY2 = box.y2;
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double intersectionX1 = max(trackletX1, detectionX1);
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double intersectionY1 = max(trackletY1, detectionY1);
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double intersectionX2 = min(trackletX2, detectionX2);
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double intersectionY2 = min(trackletY2, detectionY2);
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//double intersectionArea = max(intersectionX2-intersectionX1, 0.0) * max(intersectionY2-intersectionY1, 0.0);
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double w = (intersectionX2-intersectionX1>0.0) ? (intersectionX2-intersectionX1):0.0;
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double h = (intersectionY2-intersectionY1>0.0) ? (intersectionY2-intersectionY1):0.0;
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double intersectionArea = w*h;
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double trackletArea = tracklet.bbox(2)*tracklet.bbox(3);
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//double trackletArea = tracklet.w*tracklet.h;
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double detectionArea = (box.x2-box.x1)*(box.y2-box.y1);
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double unionArea = trackletArea + detectionArea - intersectionArea;
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double iou = (1-intersectionArea / unionArea*1.0);
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return iou;
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}
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vector<pair<int, int>> SORT::hungarian(vector<vector<double>> costMatrix) {
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// vector<pair<int, int>> SORT::hungarian(array<array<double>> costMatrix) {
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int numRows = costMatrix.size();
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int numCols = costMatrix[0].size();
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const bool transposed = numCols > numRows;
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// transpose the matrix if necessary
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if (transposed) {
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vector<vector<double>> transposedMatrix(numCols, vector<double>(numRows));
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for (int i = 0; i < numRows; i++) {
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for (int j = 0; j < numCols; j++) {
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transposedMatrix[j][i] = costMatrix[i][j];
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}
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}
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costMatrix = transposedMatrix;
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swap(numRows, numCols);
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}
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vector<double>rowMin (numRows, numeric_limits<double>::infinity());
|
||||
vector<double>colMin(numCols, numeric_limits<double>::infinity());
|
||||
vector<int>rowMatch(numRows, -1);
|
||||
vector<int>colMatch(numCols, -1);
|
||||
vector<pair<int, int>> matches;
|
||||
//step1: Subtract the row minimums from each row
|
||||
for (int i = 0; i < numRows; i++) {
|
||||
for (int j = 0; j < numCols; j++) {
|
||||
rowMin[i] = min(rowMin[i], costMatrix[i][j]);
|
||||
}
|
||||
for (int j = 0; j < numCols; j++) {
|
||||
costMatrix[i][j] -= rowMin[i];
|
||||
}
|
||||
}
|
||||
//step2: substract the colcum minimums from each column
|
||||
for (int j = 0; j < numCols; j++) {
|
||||
for (int i = 0; i < numRows; i++) {
|
||||
colMin[j] = min(colMin[j], costMatrix[i][j]);
|
||||
}
|
||||
for (int i = 0; i < numRows; i++) {
|
||||
costMatrix[i][j] -= colMin[j];
|
||||
}
|
||||
}
|
||||
//step3: find a maximal matching
|
||||
for (int i = 0; i < numRows; i++) {
|
||||
vector<bool> visited(numCols, false);
|
||||
Augment(costMatrix, i, rowMatch, colMatch, visited);
|
||||
}
|
||||
//step4: calculate the matches
|
||||
matches.clear();
|
||||
for (int j = 0; j < numCols; j++) {
|
||||
matches.push_back(make_pair(colMatch[j], j));
|
||||
}
|
||||
if (transposed) {
|
||||
//vector<pair<int,int>> transposedMatches;
|
||||
for (auto& match : matches) {
|
||||
//transposedMatches.push_back(make_pair(match.second, match.first));
|
||||
swap(match.first,match.second);
|
||||
}
|
||||
//matches = transposedMatches;
|
||||
}
|
||||
return matches;
|
||||
}
|
||||
|
||||
bool SORT::Augment(const vector<vector<double>>& costMatrix, int row, vector<int>& rowMatch, vector<int>& colMatch, vector<bool>& visited)
|
||||
// bool SORT::Augment(const array<array<double>& costMatrix, int row, vector<int>& rowMatch, vector<int>& colMatch, vector<bool>& visited)
|
||||
{
|
||||
int numCols = costMatrix[0].size();
|
||||
for (int j = 0; j < numCols; j++) {
|
||||
if (costMatrix[row][j] == 0 && !visited[j]) {
|
||||
visited[j] = true;
|
||||
if (colMatch[j] == -1 || Augment(costMatrix, colMatch[j], rowMatch, colMatch, visited)) {
|
||||
rowMatch[row] = j;
|
||||
colMatch[j] = row;
|
||||
return true;
|
||||
}
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
|
@ -0,0 +1,62 @@
|
|||
#ifndef SORT_2_H
|
||||
#define SORT_2_H
|
||||
|
||||
#include <Eigen/Dense>
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <opencv2/opencv.hpp>
|
||||
#include <sv_world.h>
|
||||
#include <array>
|
||||
|
||||
|
||||
|
||||
//define the tracklet struct to store the tracked objects
|
||||
|
||||
struct Tracklet {
|
||||
public:
|
||||
//Eigen::VectorXd bbox = Eigen::VectorXd::Zero(4);//x1,y1,w,h
|
||||
//std::vector<Eigen::Vector4d> bboxes;
|
||||
Eigen::Vector4d bbox;
|
||||
//double x, y, w, h;
|
||||
int id=0;
|
||||
int age;
|
||||
int hits;
|
||||
int misses;
|
||||
std::vector<double> features;
|
||||
Eigen::Matrix<double,8,1> mean;
|
||||
Eigen::Matrix<double,8,8> covariance;
|
||||
};
|
||||
|
||||
class KalmanFilter {
|
||||
public:
|
||||
KalmanFilter();
|
||||
std::pair<Eigen::Matrix<double,8,1>,Eigen::Matrix<double,8,8>> initiate(Eigen::Vector4d &bbox);
|
||||
std::pair<Eigen::Matrix<double,8,1>,Eigen::Matrix<double,8,8>> update(Eigen::Matrix<double,8,1> mean,Eigen::Matrix<double,8,8> covariances,sv::Box & box);
|
||||
std::pair<Eigen::Matrix<double,8,1>,Eigen::Matrix<double,8,8>> predict(Eigen::Matrix<double,8,1>mean,Eigen::Matrix<double,8,8>covariances);
|
||||
private:
|
||||
Eigen::Matrix<double,8,8> F_;
|
||||
Eigen::Matrix<double,4,8> H_;
|
||||
Eigen::Matrix<double,9,1> chi2inv95_;
|
||||
double std_weight_position;
|
||||
double std_weight_vel;
|
||||
};
|
||||
|
||||
class SORT {
|
||||
public:
|
||||
SORT(double iouThreshold, int maxAge, int minHits): iouThreshold_(iouThreshold), maxAge_(maxAge), minHits_(minHits), nextTrackletId_(0) {};
|
||||
//void update(std::vector<Eigen::VectorXd> detections);
|
||||
void update(sv::TargetsInFrame & tgts);
|
||||
std::vector<Tracklet> getTracklets() const;
|
||||
private:
|
||||
double iou(Tracklet & tracklet, sv::Box & box);
|
||||
std::vector<std::pair<int, int>> hungarian(std::vector<std::vector<double>> costMatrix);
|
||||
bool Augment(const std::vector<std::vector<double>>& costMatrix, int row, std::vector<int>& rowMatch, std::vector<int>& colMatch, std::vector<bool>& visited);
|
||||
private:
|
||||
double iouThreshold_;
|
||||
int maxAge_;
|
||||
int minHits_;
|
||||
int nextTrackletId_;
|
||||
std::vector <Tracklet> tracklets_;
|
||||
};
|
||||
|
||||
#endif
|
||||
|
|
@ -0,0 +1,188 @@
|
|||
#include <iostream>
|
||||
#include <string>
|
||||
// 包含SpireVision SDK头文件
|
||||
#include <sv_world.h>
|
||||
#include <NvInfer.h>
|
||||
#include <cuda_runtime_api.h>
|
||||
#include "logging.h"
|
||||
|
||||
// #include <opencv2/opencv.hpp>
|
||||
#include "SORT_2.h"
|
||||
|
||||
#define TRTCHECK(status) \
|
||||
do \
|
||||
{ \
|
||||
auto ret = (status); \
|
||||
if (ret != 0) \
|
||||
{ \
|
||||
std::cerr << "Cuda failure: " << ret << std::endl; \
|
||||
abort(); \
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
using namespace std;
|
||||
using namespace nvinfer1;
|
||||
static Logger g_nvlogger;
|
||||
|
||||
// using namespace cv;
|
||||
using namespace Eigen;
|
||||
|
||||
// nvinfer1::IExecutionContext *g_trt_context;
|
||||
// int g_input_index;
|
||||
// int g_output_index;
|
||||
// void *g_p_buffers[2];
|
||||
// cudaStream_t g_cu_stream;
|
||||
// float *g_p_data;
|
||||
// float *g_p_prob;
|
||||
|
||||
|
||||
// void tensorrt_model_init()
|
||||
// {
|
||||
// std::string trt_model_fn = "/home/amov/SpireVision/models/resnet_reid.engine";
|
||||
// char *trt_model_stream{nullptr};
|
||||
// size_t trt_model_size{0};
|
||||
// try
|
||||
// {
|
||||
// std::ifstream file(trt_model_fn, std::ios::binary);
|
||||
// file.seekg(0, file.end);
|
||||
// trt_model_size = file.tellg();
|
||||
// file.seekg(0, file.beg);
|
||||
// trt_model_stream = new char[trt_model_size];
|
||||
// assert(trt_model_stream);
|
||||
// file.read(trt_model_stream, trt_model_size);
|
||||
// file.close();
|
||||
// }
|
||||
// catch (const std::runtime_error &e)
|
||||
// {
|
||||
// throw std::runtime_error("Error loading the TensorRT model!");
|
||||
// }
|
||||
|
||||
// // TensorRT
|
||||
// IRuntime *runtime = nvinfer1::createInferRuntime(g_nvlogger);
|
||||
// assert(runtime != nullptr);
|
||||
// ICudaEngine *p_cu_engine = runtime->deserializeCudaEngine(trt_model_stream, trt_model_size);
|
||||
// assert(p_cu_engine != nullptr);
|
||||
// g_trt_context = p_cu_engine->createExecutionContext();
|
||||
// assert(g_trt_context != nullptr);
|
||||
// delete[] trt_model_stream;
|
||||
// const ICudaEngine &cu_engine = g_trt_context->getEngine();
|
||||
// assert(cu_engine.getNbBindings() == 2);
|
||||
|
||||
// g_input_index = cu_engine.getBindingIndex("input");
|
||||
// g_output_index = cu_engine.getBindingIndex("output");
|
||||
// TRTCHECK(cudaMalloc(&g_p_buffers[g_input_index], 1 * 3 * 32 * 32 * sizeof(float)));
|
||||
// TRTCHECK(cudaMalloc(&g_p_buffers[g_output_index], 1 * 11 * sizeof(float)));
|
||||
// TRTCHECK(cudaStreamCreate(&g_cu_stream));
|
||||
|
||||
// g_p_data = new float[1 * 3 * 32 * 32];
|
||||
// g_p_prob = new float[1 * 11];
|
||||
// // Input
|
||||
// TRTCHECK(cudaMemcpyAsync(g_p_buffers[g_input_index], g_p_data, 1 * 3 * 32 * 32 * sizeof(float), cudaMemcpyHostToDevice, g_cu_stream));
|
||||
// g_trt_context->enqueue(1, g_p_buffers, g_cu_stream, nullptr);
|
||||
// // Output
|
||||
// TRTCHECK(cudaMemcpyAsync(g_p_prob, g_p_buffers[g_output_index], 1 * 11 * sizeof(float), cudaMemcpyDeviceToHost, g_cu_stream));
|
||||
// cudaStreamSynchronize(g_cu_stream);
|
||||
// }
|
||||
|
||||
int main(int argc, char *argv[]) {
|
||||
// 实例化 通用目标 检测器类
|
||||
sv::CommonObjectDetector cod;
|
||||
// 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
|
||||
cod.loadCameraParams(sv::get_home() + "/SpireVision/calib_webcam_640x480.yaml");
|
||||
|
||||
// 打开摄像头
|
||||
// sv::Camera cap;
|
||||
// cap.open(sv::CameraType::WEBCAM, 0);
|
||||
cv::VideoCapture cap;
|
||||
cap.open("/home/amov/SpireVision/video/predestrian/MOT17-01.mp4");
|
||||
// cap.open("/home/amov/SpireVision/video/vehicle/vehicle_02.mp4");
|
||||
// 实例化OpenCV的Mat类，用于内存单帧图像
|
||||
cv::Mat img;
|
||||
int frame_id = 0;
|
||||
SORT tracker(0.5, 10, 3);
|
||||
while (1)
|
||||
{
|
||||
// 实例化SpireVision的 单帧检测结果 接口类 TargetsInFrame
|
||||
sv::TargetsInFrame tgts(frame_id++);
|
||||
// 读取一帧图像到img
|
||||
cap.read(img);
|
||||
cv::resize(img, img, cv::Size(cod.image_width, cod.image_height));
|
||||
|
||||
// 执行通用目标检测
|
||||
cod.detect(img, tgts);
|
||||
tracker.update(tgts);
|
||||
//vector<VectorXd> detections;
|
||||
// 可视化检测结果，叠加到img上
|
||||
// sv::drawTargetsInFrame(img, tgts);
|
||||
/*
|
||||
for (int i=0; i<tgts.targets.size(); i++)
|
||||
{
|
||||
sv::Box box;
|
||||
tgts.targets[i].getBox(box);
|
||||
cv::Mat roi = img(cv::Rect(box.x1, box.y1, box.x2-box.x1, box.y2-box.y1)).clone();
|
||||
VectorXd detect(5);
|
||||
detect.fill(-1.0);
|
||||
detect << box.x1,box.y1,box.x2-box.x1,box.y2-box.y1,-1.0;
|
||||
detections.push_back(detect);
|
||||
}
|
||||
tracker.update(detections);
|
||||
|
||||
|
||||
// Input
|
||||
TRTCHECK(cudaMemcpyAsync(g_p_buffers[g_input_index], g_p_data, 1 * 3 * 32 * 32 * sizeof(float), cudaMemcpyHostToDevice, g_cu_stream));
|
||||
g_trt_context->enqueue(1, g_p_buffers, g_cu_stream, nullptr);
|
||||
// Output
|
||||
TRTCHECK(cudaMemcpyAsync(g_p_prob, g_p_buffers[g_output_index], 1 * 11 * sizeof(float), cudaMemcpyDeviceToHost, g_cu_stream));
|
||||
cudaStreamSynchronize(g_cu_stream);
|
||||
|
||||
// Find max index
|
||||
double max = 0;
|
||||
int label = 0;
|
||||
for (int i = 0; i < 11; ++i)
|
||||
{
|
||||
if (max < g_p_prob[i])
|
||||
{
|
||||
max = g_p_prob[i];
|
||||
label = i;
|
||||
}
|
||||
}
|
||||
*/
|
||||
//cv::imshow("roi", roi);
|
||||
// cv::waitKey(10);
|
||||
//tracker.update(detections);
|
||||
//vector<Detection>().swap(detections);
|
||||
|
||||
// 可视化检测结果，叠加到img上
|
||||
sv::drawTargetsInFrame(img, tgts);
|
||||
// 控制台打印通用目标检测结果
|
||||
printf("Frame-[%d]\n", frame_id);
|
||||
// 打印当前检测的FPS
|
||||
printf(" FPS = %.2f\n", tgts.fps);
|
||||
// 打印当前相机的视场角（degree）
|
||||
printf(" FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
|
||||
for (int i=0; i<tgts.targets.size(); i++)
|
||||
{
|
||||
printf("Frame-[%d], Object-[%d]\n", frame_id, i);
|
||||
// 打印每个目标的中心位置，cx，cy的值域为[0, 1]
|
||||
printf(" Object Center (cx, cy) = (%.3f, %.3f)\n", tgts.targets[i].cx, tgts.targets[i].cy);
|
||||
// 打印每个目标的外接矩形框的宽度、高度，w，h的值域为(0, 1]
|
||||
printf(" Object Size (w, h) = (%.3f, %.3f)\n", tgts.targets[i].w, tgts.targets[i].h);
|
||||
// 打印每个目标的置信度
|
||||
printf(" Object Score = %.3f\n", tgts.targets[i].score);
|
||||
// 打印每个目标的类别，字符串类型
|
||||
printf(" Object Category = %s, Category ID = [%d]\n", tgts.targets[i].category.c_str(), tgts.targets[i].category_id);
|
||||
// 打印每个目标的视线角，跟相机视场相关
|
||||
printf(" Object Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
|
||||
// 打印每个目标的3D位置（在相机坐标系下），跟目标实际长宽、相机参数相关
|
||||
printf(" Object Position = (x, y, z) = (%.3f, %.3f, %.3f)\n", tgts.targets[i].px, tgts.targets[i].py, tgts.targets[i].pz);
|
||||
// print tracked_id
|
||||
printf(" Object tracked_id = %d\n", tgts.targets[i].tracked_id);
|
||||
}
|
||||
|
||||
// 显示检测结果img
|
||||
cv::imshow("img", img);
|
||||
cv::waitKey(10);
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
|
@ -0,0 +1,504 @@
|
|||
/*
|
||||
* Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
#ifndef TENSORRT_LOGGING_H
|
||||
#define TENSORRT_LOGGING_H
|
||||
|
||||
#include "NvInferRuntimeCommon.h"
|
||||
#include <cassert>
|
||||
#include <ctime>
|
||||
#include <iomanip>
|
||||
#include <iostream>
|
||||
#include <ostream>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
#include "macros.h"
|
||||
|
||||
using Severity = nvinfer1::ILogger::Severity;
|
||||
|
||||
class LogStreamConsumerBuffer : public std::stringbuf
|
||||
{
|
||||
public:
|
||||
LogStreamConsumerBuffer(std::ostream& stream, const std::string& prefix, bool shouldLog)
|
||||
: mOutput(stream)
|
||||
, mPrefix(prefix)
|
||||
, mShouldLog(shouldLog)
|
||||
{
|
||||
}
|
||||
|
||||
LogStreamConsumerBuffer(LogStreamConsumerBuffer&& other)
|
||||
: mOutput(other.mOutput)
|
||||
{
|
||||
}
|
||||
|
||||
~LogStreamConsumerBuffer()
|
||||
{
|
||||
// std::streambuf::pbase() gives a pointer to the beginning of the buffered part of the output sequence
|
||||
// std::streambuf::pptr() gives a pointer to the current position of the output sequence
|
||||
// if the pointer to the beginning is not equal to the pointer to the current position,
|
||||
// call putOutput() to log the output to the stream
|
||||
if (pbase() != pptr())
|
||||
{
|
||||
putOutput();
|
||||
}
|
||||
}
|
||||
|
||||
// synchronizes the stream buffer and returns 0 on success
|
||||
// synchronizing the stream buffer consists of inserting the buffer contents into the stream,
|
||||
// resetting the buffer and flushing the stream
|
||||
virtual int sync()
|
||||
{
|
||||
putOutput();
|
||||
return 0;
|
||||
}
|
||||
|
||||
void putOutput()
|
||||
{
|
||||
if (mShouldLog)
|
||||
{
|
||||
// prepend timestamp
|
||||
std::time_t timestamp = std::time(nullptr);
|
||||
tm* tm_local = std::localtime(×tamp);
|
||||
std::cout << "[";
|
||||
std::cout << std::setw(2) << std::setfill('0') << 1 + tm_local->tm_mon << "/";
|
||||
std::cout << std::setw(2) << std::setfill('0') << tm_local->tm_mday << "/";
|
||||
std::cout << std::setw(4) << std::setfill('0') << 1900 + tm_local->tm_year << "-";
|
||||
std::cout << std::setw(2) << std::setfill('0') << tm_local->tm_hour << ":";
|
||||
std::cout << std::setw(2) << std::setfill('0') << tm_local->tm_min << ":";
|
||||
std::cout << std::setw(2) << std::setfill('0') << tm_local->tm_sec << "] ";
|
||||
// std::stringbuf::str() gets the string contents of the buffer
|
||||
// insert the buffer contents pre-appended by the appropriate prefix into the stream
|
||||
mOutput << mPrefix << str();
|
||||
// set the buffer to empty
|
||||
str("");
|
||||
// flush the stream
|
||||
mOutput.flush();
|
||||
}
|
||||
}
|
||||
|
||||
void setShouldLog(bool shouldLog)
|
||||
{
|
||||
mShouldLog = shouldLog;
|
||||
}
|
||||
|
||||
private:
|
||||
std::ostream& mOutput;
|
||||
std::string mPrefix;
|
||||
bool mShouldLog;
|
||||
};
|
||||
|
||||
//!
|
||||
//! \class LogStreamConsumerBase
|
||||
//! \brief Convenience object used to initialize LogStreamConsumerBuffer before std::ostream in LogStreamConsumer
|
||||
//!
|
||||
class LogStreamConsumerBase
|
||||
{
|
||||
public:
|
||||
LogStreamConsumerBase(std::ostream& stream, const std::string& prefix, bool shouldLog)
|
||||
: mBuffer(stream, prefix, shouldLog)
|
||||
{
|
||||
}
|
||||
|
||||
protected:
|
||||
LogStreamConsumerBuffer mBuffer;
|
||||
};
|
||||
|
||||
//!
|
||||
//! \class LogStreamConsumer
|
||||
//! \brief Convenience object used to facilitate use of C++ stream syntax when logging messages.
|
||||
//! Order of base classes is LogStreamConsumerBase and then std::ostream.
|
||||
//! This is because the LogStreamConsumerBase class is used to initialize the LogStreamConsumerBuffer member field
|
||||
//! in LogStreamConsumer and then the address of the buffer is passed to std::ostream.
|
||||
//! This is necessary to prevent the address of an uninitialized buffer from being passed to std::ostream.
|
||||
//! Please do not change the order of the parent classes.
|
||||
//!
|
||||
class LogStreamConsumer : protected LogStreamConsumerBase, public std::ostream
|
||||
{
|
||||
public:
|
||||
//! \brief Creates a LogStreamConsumer which logs messages with level severity.
|
||||
//! Reportable severity determines if the messages are severe enough to be logged.
|
||||
LogStreamConsumer(Severity reportableSeverity, Severity severity)
|
||||
: LogStreamConsumerBase(severityOstream(severity), severityPrefix(severity), severity <= reportableSeverity)
|
||||
, std::ostream(&mBuffer) // links the stream buffer with the stream
|
||||
, mShouldLog(severity <= reportableSeverity)
|
||||
, mSeverity(severity)
|
||||
{
|
||||
}
|
||||
|
||||
LogStreamConsumer(LogStreamConsumer&& other)
|
||||
: LogStreamConsumerBase(severityOstream(other.mSeverity), severityPrefix(other.mSeverity), other.mShouldLog)
|
||||
, std::ostream(&mBuffer) // links the stream buffer with the stream
|
||||
, mShouldLog(other.mShouldLog)
|
||||
, mSeverity(other.mSeverity)
|
||||
{
|
||||
}
|
||||
|
||||
void setReportableSeverity(Severity reportableSeverity)
|
||||
{
|
||||
mShouldLog = mSeverity <= reportableSeverity;
|
||||
mBuffer.setShouldLog(mShouldLog);
|
||||
}
|
||||
|
||||
private:
|
||||
static std::ostream& severityOstream(Severity severity)
|
||||
{
|
||||
return severity >= Severity::kINFO ? std::cout : std::cerr;
|
||||
}
|
||||
|
||||
static std::string severityPrefix(Severity severity)
|
||||
{
|
||||
switch (severity)
|
||||
{
|
||||
case Severity::kINTERNAL_ERROR: return "[F] ";
|
||||
case Severity::kERROR: return "[E] ";
|
||||
case Severity::kWARNING: return "[W] ";
|
||||
case Severity::kINFO: return "[I] ";
|
||||
case Severity::kVERBOSE: return "[V] ";
|
||||
default: assert(0); return "";
|
||||
}
|
||||
}
|
||||
|
||||
bool mShouldLog;
|
||||
Severity mSeverity;
|
||||
};
|
||||
|
||||
//! \class Logger
|
||||
//!
|
||||
//! \brief Class which manages logging of TensorRT tools and samples
|
||||
//!
|
||||
//! \details This class provides a common interface for TensorRT tools and samples to log information to the console,
|
||||
//! and supports logging two types of messages:
|
||||
//!
|
||||
//! - Debugging messages with an associated severity (info, warning, error, or internal error/fatal)
|
||||
//! - Test pass/fail messages
|
||||
//!
|
||||
//! The advantage of having all samples use this class for logging as opposed to emitting directly to stdout/stderr is
|
||||
//! that the logic for controlling the verbosity and formatting of sample output is centralized in one location.
|
||||
//!
|
||||
//! In the future, this class could be extended to support dumping test results to a file in some standard format
|
||||
//! (for example, JUnit XML), and providing additional metadata (e.g. timing the duration of a test run).
|
||||
//!
|
||||
//! TODO: For backwards compatibility with existing samples, this class inherits directly from the nvinfer1::ILogger
|
||||
//! interface, which is problematic since there isn't a clean separation between messages coming from the TensorRT
|
||||
//! library and messages coming from the sample.
|
||||
//!
|
||||
//! In the future (once all samples are updated to use Logger::getTRTLogger() to access the ILogger) we can refactor the
|
||||
//! class to eliminate the inheritance and instead make the nvinfer1::ILogger implementation a member of the Logger
|
||||
//! object.
|
||||
|
||||
class Logger : public nvinfer1::ILogger
|
||||
{
|
||||
public:
|
||||
Logger(Severity severity = Severity::kWARNING)
|
||||
: mReportableSeverity(severity)
|
||||
{
|
||||
}
|
||||
|
||||
//!
|
||||
//! \enum TestResult
|
||||
//! \brief Represents the state of a given test
|
||||
//!
|
||||
enum class TestResult
|
||||
{
|
||||
kRUNNING, //!< The test is running
|
||||
kPASSED, //!< The test passed
|
||||
kFAILED, //!< The test failed
|
||||
kWAIVED //!< The test was waived
|
||||
};
|
||||
|
||||
//!
|
||||
//! \brief Forward-compatible method for retrieving the nvinfer::ILogger associated with this Logger
|
||||
//! \return The nvinfer1::ILogger associated with this Logger
|
||||
//!
|
||||
//! TODO Once all samples are updated to use this method to register the logger with TensorRT,
|
||||
//! we can eliminate the inheritance of Logger from ILogger
|
||||
//!
|
||||
nvinfer1::ILogger& getTRTLogger()
|
||||
{
|
||||
return *this;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief Implementation of the nvinfer1::ILogger::log() virtual method
|
||||
//!
|
||||
//! Note samples should not be calling this function directly; it will eventually go away once we eliminate the
|
||||
//! inheritance from nvinfer1::ILogger
|
||||
//!
|
||||
void log(Severity severity, const char* msg) TRT_NOEXCEPT override
|
||||
{
|
||||
LogStreamConsumer(mReportableSeverity, severity) << "[TRT] " << std::string(msg) << std::endl;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief Method for controlling the verbosity of logging output
|
||||
//!
|
||||
//! \param severity The logger will only emit messages that have severity of this level or higher.
|
||||
//!
|
||||
void setReportableSeverity(Severity severity)
|
||||
{
|
||||
mReportableSeverity = severity;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief Opaque handle that holds logging information for a particular test
|
||||
//!
|
||||
//! This object is an opaque handle to information used by the Logger to print test results.
|
||||
//! The sample must call Logger::defineTest() in order to obtain a TestAtom that can be used
|
||||
//! with Logger::reportTest{Start,End}().
|
||||
//!
|
||||
class TestAtom
|
||||
{
|
||||
public:
|
||||
TestAtom(TestAtom&&) = default;
|
||||
|
||||
private:
|
||||
friend class Logger;
|
||||
|
||||
TestAtom(bool started, const std::string& name, const std::string& cmdline)
|
||||
: mStarted(started)
|
||||
, mName(name)
|
||||
, mCmdline(cmdline)
|
||||
{
|
||||
}
|
||||
|
||||
bool mStarted;
|
||||
std::string mName;
|
||||
std::string mCmdline;
|
||||
};
|
||||
|
||||
//!
|
||||
//! \brief Define a test for logging
|
||||
//!
|
||||
//! \param[in] name The name of the test. This should be a string starting with
|
||||
//! "TensorRT" and containing dot-separated strings containing
|
||||
//! the characters [A-Za-z0-9_].
|
||||
//! For example, "TensorRT.sample_googlenet"
|
||||
//! \param[in] cmdline The command line used to reproduce the test
|
||||
//
|
||||
//! \return a TestAtom that can be used in Logger::reportTest{Start,End}().
|
||||
//!
|
||||
static TestAtom defineTest(const std::string& name, const std::string& cmdline)
|
||||
{
|
||||
return TestAtom(false, name, cmdline);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief A convenience overloaded version of defineTest() that accepts an array of command-line arguments
|
||||
//! as input
|
||||
//!
|
||||
//! \param[in] name The name of the test
|
||||
//! \param[in] argc The number of command-line arguments
|
||||
//! \param[in] argv The array of command-line arguments (given as C strings)
|
||||
//!
|
||||
//! \return a TestAtom that can be used in Logger::reportTest{Start,End}().
|
||||
static TestAtom defineTest(const std::string& name, int argc, char const* const* argv)
|
||||
{
|
||||
auto cmdline = genCmdlineString(argc, argv);
|
||||
return defineTest(name, cmdline);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief Report that a test has started.
|
||||
//!
|
||||
//! \pre reportTestStart() has not been called yet for the given testAtom
|
||||
//!
|
||||
//! \param[in] testAtom The handle to the test that has started
|
||||
//!
|
||||
static void reportTestStart(TestAtom& testAtom)
|
||||
{
|
||||
reportTestResult(testAtom, TestResult::kRUNNING);
|
||||
assert(!testAtom.mStarted);
|
||||
testAtom.mStarted = true;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief Report that a test has ended.
|
||||
//!
|
||||
//! \pre reportTestStart() has been called for the given testAtom
|
||||
//!
|
||||
//! \param[in] testAtom The handle to the test that has ended
|
||||
//! \param[in] result The result of the test. Should be one of TestResult::kPASSED,
|
||||
//! TestResult::kFAILED, TestResult::kWAIVED
|
||||
//!
|
||||
static void reportTestEnd(const TestAtom& testAtom, TestResult result)
|
||||
{
|
||||
assert(result != TestResult::kRUNNING);
|
||||
assert(testAtom.mStarted);
|
||||
reportTestResult(testAtom, result);
|
||||
}
|
||||
|
||||
static int reportPass(const TestAtom& testAtom)
|
||||
{
|
||||
reportTestEnd(testAtom, TestResult::kPASSED);
|
||||
return EXIT_SUCCESS;
|
||||
}
|
||||
|
||||
static int reportFail(const TestAtom& testAtom)
|
||||
{
|
||||
reportTestEnd(testAtom, TestResult::kFAILED);
|
||||
return EXIT_FAILURE;
|
||||
}
|
||||
|
||||
static int reportWaive(const TestAtom& testAtom)
|
||||
{
|
||||
reportTestEnd(testAtom, TestResult::kWAIVED);
|
||||
return EXIT_SUCCESS;
|
||||
}
|
||||
|
||||
static int reportTest(const TestAtom& testAtom, bool pass)
|
||||
{
|
||||
return pass ? reportPass(testAtom) : reportFail(testAtom);
|
||||
}
|
||||
|
||||
Severity getReportableSeverity() const
|
||||
{
|
||||
return mReportableSeverity;
|
||||
}
|
||||
|
||||
private:
|
||||
//!
|
||||
//! \brief returns an appropriate string for prefixing a log message with the given severity
|
||||
//!
|
||||
static const char* severityPrefix(Severity severity)
|
||||
{
|
||||
switch (severity)
|
||||
{
|
||||
case Severity::kINTERNAL_ERROR: return "[F] ";
|
||||
case Severity::kERROR: return "[E] ";
|
||||
case Severity::kWARNING: return "[W] ";
|
||||
case Severity::kINFO: return "[I] ";
|
||||
case Severity::kVERBOSE: return "[V] ";
|
||||
default: assert(0); return "";
|
||||
}
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief returns an appropriate string for prefixing a test result message with the given result
|
||||
//!
|
||||
static const char* testResultString(TestResult result)
|
||||
{
|
||||
switch (result)
|
||||
{
|
||||
case TestResult::kRUNNING: return "RUNNING";
|
||||
case TestResult::kPASSED: return "PASSED";
|
||||
case TestResult::kFAILED: return "FAILED";
|
||||
case TestResult::kWAIVED: return "WAIVED";
|
||||
default: assert(0); return "";
|
||||
}
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief returns an appropriate output stream (cout or cerr) to use with the given severity
|
||||
//!
|
||||
static std::ostream& severityOstream(Severity severity)
|
||||
{
|
||||
return severity >= Severity::kINFO ? std::cout : std::cerr;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief method that implements logging test results
|
||||
//!
|
||||
static void reportTestResult(const TestAtom& testAtom, TestResult result)
|
||||
{
|
||||
severityOstream(Severity::kINFO) << "&&&& " << testResultString(result) << " " << testAtom.mName << " # "
|
||||
<< testAtom.mCmdline << std::endl;
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief generate a command line string from the given (argc, argv) values
|
||||
//!
|
||||
static std::string genCmdlineString(int argc, char const* const* argv)
|
||||
{
|
||||
std::stringstream ss;
|
||||
for (int i = 0; i < argc; i++)
|
||||
{
|
||||
if (i > 0)
|
||||
ss << " ";
|
||||
ss << argv[i];
|
||||
}
|
||||
return ss.str();
|
||||
}
|
||||
|
||||
Severity mReportableSeverity;
|
||||
};
|
||||
|
||||
namespace
|
||||
{
|
||||
|
||||
//!
|
||||
//! \brief produces a LogStreamConsumer object that can be used to log messages of severity kVERBOSE
|
||||
//!
|
||||
//! Example usage:
|
||||
//!
|
||||
//! LOG_VERBOSE(logger) << "hello world" << std::endl;
|
||||
//!
|
||||
inline LogStreamConsumer LOG_VERBOSE(const Logger& logger)
|
||||
{
|
||||
return LogStreamConsumer(logger.getReportableSeverity(), Severity::kVERBOSE);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief produces a LogStreamConsumer object that can be used to log messages of severity kINFO
|
||||
//!
|
||||
//! Example usage:
|
||||
//!
|
||||
//! LOG_INFO(logger) << "hello world" << std::endl;
|
||||
//!
|
||||
inline LogStreamConsumer LOG_INFO(const Logger& logger)
|
||||
{
|
||||
return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINFO);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief produces a LogStreamConsumer object that can be used to log messages of severity kWARNING
|
||||
//!
|
||||
//! Example usage:
|
||||
//!
|
||||
//! LOG_WARN(logger) << "hello world" << std::endl;
|
||||
//!
|
||||
inline LogStreamConsumer LOG_WARN(const Logger& logger)
|
||||
{
|
||||
return LogStreamConsumer(logger.getReportableSeverity(), Severity::kWARNING);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief produces a LogStreamConsumer object that can be used to log messages of severity kERROR
|
||||
//!
|
||||
//! Example usage:
|
||||
//!
|
||||
//! LOG_ERROR(logger) << "hello world" << std::endl;
|
||||
//!
|
||||
inline LogStreamConsumer LOG_ERROR(const Logger& logger)
|
||||
{
|
||||
return LogStreamConsumer(logger.getReportableSeverity(), Severity::kERROR);
|
||||
}
|
||||
|
||||
//!
|
||||
//! \brief produces a LogStreamConsumer object that can be used to log messages of severity kINTERNAL_ERROR
|
||||
// ("fatal" severity)
|
||||
//!
|
||||
//! Example usage:
|
||||
//!
|
||||
//! LOG_FATAL(logger) << "hello world" << std::endl;
|
||||
//!
|
||||
inline LogStreamConsumer LOG_FATAL(const Logger& logger)
|
||||
{
|
||||
return LogStreamConsumer(logger.getReportableSeverity(), Severity::kINTERNAL_ERROR);
|
||||
}
|
||||
|
||||
} // anonymous namespace
|
||||
|
||||
#endif // TENSORRT_LOGGING_H
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
#ifndef __MACROS_H
|
||||
#define __MACROS_H
|
||||
|
||||
#include <NvInfer.h>
|
||||
|
||||
#ifdef API_EXPORTS
|
||||
#if defined(_MSC_VER)
|
||||
#define API __declspec(dllexport)
|
||||
#else
|
||||
#define API __attribute__((visibility("default")))
|
||||
#endif
|
||||
#else
|
||||
|
||||
#if defined(_MSC_VER)
|
||||
#define API __declspec(dllimport)
|
||||
#else
|
||||
#define API
|
||||
#endif
|
||||
#endif // API_EXPORTS
|
||||
|
||||
#if NV_TENSORRT_MAJOR >= 8
|
||||
#define TRT_NOEXCEPT noexcept
|
||||
#define TRT_CONST_ENQUEUE const
|
||||
#else
|
||||
#define TRT_NOEXCEPT
|
||||
#define TRT_CONST_ENQUEUE
|
||||
#endif
|
||||
|
||||
#endif // __MACROS_H
|
||||
Loading…
Reference in New Issue