Init: Update Intrusion-detection source code
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407904cd65
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0d7bba41a1
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@ -1,24 +1,40 @@
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# Build artifacts
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build/
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# Prerequisites
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*.d
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# Compiled Object files
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*.slo
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*.lo
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*.o
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*.a
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*.so
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*.obj
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# Precompiled Headers
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*.gch
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*.pch
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# Compiled Dynamic libraries
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*.dylib
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*.dll
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# Fortran module files
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*.mod
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*.smod
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# Compiled Static libraries
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*.lai
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*.la
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*.a
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*.lib
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# Executables
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*.exe
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*.out
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*.app
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# IDE and editor files
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.vscode/
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.idea/
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*.suo
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*.ntvs*
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*.njsproj
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*.sln
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*.swp
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*.mp4
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/build
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/install
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/.vscode
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# Log files
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*.log
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# Dependency directories
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vendor/
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node_modules/
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*.png
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*.jpg
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*.mp4
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@ -0,0 +1,17 @@
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cmake_minimum_required(VERSION 3.4.1)
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set(CMAKE_CXX_STANDARD 14)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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# 定义整个大项目的名称
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project(EdgeProxyPlatform)
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# 打印一条消息，方便调试，确认是顶层CMake在运行
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message(STATUS "Running Top-Level CMake for ${PROJECT_NAME}")
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# 使用 add_subdirectory() 命令将 services 目录下的项目包含进来
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# CMake 会自动寻找 services/intrusion-detection/CMakeLists.txt 并执行它
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add_subdirectory(services/intrusion-detection)
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# 当你未来添加了车辆识别项目后，只需在这里加一行即可
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# add_subdirectory(services/vehicle-recognition)
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@ -0,0 +1 @@
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librknnrt.so
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Binary file not shown.
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@ -1,61 +1,61 @@
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# CMake 最低版本要求
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cmake_minimum_required(VERSION 3.4.1)
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project(rknn_yolov5_demo)
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# 项目名称
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project(IntrusionDetectionService CXX)
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# 设置 C++ 标准和编译选项
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set(CMAKE_CXX_STANDARD 14)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CMAKE_CXX_FLAGS "-pthread")
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# skip 3rd-party lib dependencies
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set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Wl,--allow-shlib-undefined")
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# --- 1. 定义并查找公共库 (RKNN) ---
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# 使用相对路径找到顶层目录下的 libs 文件夹
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set(COMMON_LIB_DIR ${CMAKE_SOURCE_DIR}/libs)
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find_library(RKNNRT_LIBRARY rknnrt HINTS ${COMMON_LIB_DIR})
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find_library(RKNNAPI_LIBRARY rknn_api HINTS ${COMMON_LIB_DIR})
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# install target and libraries
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set(CMAKE_INSTALL_PREFIX ${CMAKE_SOURCE_DIR}/install/rknn_yolov5_demo_${CMAKE_SYSTEM_NAME})
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if(NOT RKNNRT_LIBRARY OR NOT RKNNAPI_LIBRARY)
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message(FATAL_ERROR "Could not find RKNN libraries in ${COMMON_LIB_DIR}")
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else()
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message(STATUS "Found rknnrt: ${RKNNRT_LIBRARY}")
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message(STATUS "Found rknn_api: ${RKNNAPI_LIBRARY}")
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endif()
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set(CMAKE_SKIP_INSTALL_RPATH FALSE)
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set(CMAKE_BUILD_WITH_INSTALL_RPATH TRUE)
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set(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib")
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# rknn api
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set(RKNN_API_PATH ${CMAKE_SOURCE_DIR}/../../runtime/RK3588/${CMAKE_SYSTEM_NAME}/librknn_api)
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set(LIB_ARCH aarch64)
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set(RKNN_RT_LIB ${CMAKE_SOURCE_DIR}/include/librknnrt.so)
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#rga
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set(RGA_PATH ${CMAKE_SOURCE_DIR}/include/3rdparty/rga/RK3588)
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set(RGA_LIB ${RGA_PATH}/lib/Linux//${LIB_ARCH}/librga.so)
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include_directories(${RKNN_API_PATH}/include)
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include_directories(${CMAKE_SOURCE_DIR}/include/3rdparty)
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include_directories(${RGA_PATH}/include)
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# opencv
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# --- 2. 定义并查找其他依赖 (OpenCV, RGA) ---
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find_package(OpenCV REQUIRED)
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set(CMAKE_INSTALL_RPATH "lib")
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# rga 库的路径，根据您的截图，它位于 include/3rdparty
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set(RGA_PATH ${CMAKE_CURRENT_SOURCE_DIR}/include/3rdparty/rga/RK3588)
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set(RGA_LIB ${RGA_PATH}/lib/Linux/aarch64/librga.so)
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if(NOT EXISTS ${RGA_LIB})
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message(FATAL_ERROR "RGA library not found at ${RGA_LIB}")
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endif()
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# rknn_yolov5_demo
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include_directories( ${CMAKE_SOURCE_DIR}/include)
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add_executable(rknn_yolov5_demo
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# --- 3. 生成可执行文件 ---
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# (修改点) 根据截图，所有源文件都在 src 目录下，为其添加 "src/" 前缀
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add_executable(intrusion_detection_service
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src/main.cc
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src/postprocess.cc
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src/preprocess.cc
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src/rkYolov5s.cc
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)
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target_link_libraries(rknn_yolov5_demo
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${RKNN_RT_LIB}
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${OpenCV_LIBS}
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${RGA_LIB}
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# --- 4. 为目标指定头文件搜索路径 ---
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# (修改点) 根据截图，所有头文件都在 include 目录下
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target_include_directories(intrusion_detection_service PUBLIC
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${CMAKE_CURRENT_SOURCE_DIR}/include # <-- 关键修改
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${OpenCV_INCLUDE_DIRS}
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${RGA_PATH}/include
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# 如果有公共头文件，也需要添加路径，例如: ${CMAKE_SOURCE_DIR}/include
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)
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# --- 5. 链接所有库到可执行文件 ---
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target_link_libraries(intrusion_detection_service
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${RKNNRT_LIBRARY}
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${RKNNAPI_LIBRARY}
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${RGA_LIB}
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${OpenCV_LIBS}
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)
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# install target and libraries
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set(CMAKE_INSTALL_PREFIX ${CMAKE_SOURCE_DIR}/install/rknn_yolov5_demo_${CMAKE_SYSTEM_NAME})
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install(TARGETS rknn_yolov5_demo DESTINATION ./)
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install(PROGRAMS ${RKNN_RT_LIB} DESTINATION lib)
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install(PROGRAMS ${RGA_LIB} DESTINATION lib)
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install(DIRECTORY model DESTINATION ./)
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message(STATUS "Configuration for IntrusionDetectionService is complete.")
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BIN
services/intrusion-detection/include/3rdparty/rga/RK3588/lib/Linux/aarch64/librga.so
vendored
Normal file
BIN
services/intrusion-detection/include/3rdparty/rga/RK3588/lib/Linux/aarch64/librga.so
vendored
Normal file
Binary file not shown.
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@ -11,16 +11,9 @@ int main(int argc, char **argv)
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{
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char *model_name = NULL;
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const char* model_path = "/home/forlinx/rknn-cpp-Multithreading-main/model/RK3588/yolov5s-640-640.rknn";
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// if (argc != 3)
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// {
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// printf("Usage: %s <rknn model> <jpg> \n", argv[0]);
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// return -1;
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// }
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// 参数二，模型所在路径/The path where the model is located
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// model_name = (char *)argv[1];
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// 参数三, 视频/摄像头
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// char *video_name = argv[2];
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// 初始化rknn线程池/Initialize the rknn thread pool
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int threadNum = 3;
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@ -31,9 +24,14 @@ int main(int argc, char **argv)
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return -1;
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}
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const char* WINDOW_NAME = "RTSP Fullscreen Display";
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cv::namedWindow(WINDOW_NAME, cv::WINDOW_NORMAL);
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cv::setWindowProperty(WINDOW_NAME, cv::WND_PROP_FULLSCREEN, cv::WINDOW_FULLSCREEN);
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// const char *video_name = "/home/forlinx/Videos/test_video.mp4";
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// cv::VideoCapture capture;
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// if (strlen(video_name) == 1)
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// capture.open((int)(video_name[0] - '0'));
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// else
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// capture.open(video_name);
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setenv("OPENCV_FFMPEG_CAPTURE_OPTIONS", "rtsp_transport;tcp", 1);
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printf("Set RTSP transport protocol to TCP\n");
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std::string rtsp_url = "rtsp://admin:hzx12345@192.168.1.10:554/Streaming/Channels/1301";
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cv::VideoCapture capture(rtsp_url, cv::CAP_FFMPEG);
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@ -43,11 +41,14 @@ int main(int argc, char **argv)
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return -1;
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}
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printf("RTSP stream opened successfully!\n");
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// cv::VideoCapture capture;
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// if (strlen(video_name) == 1)
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// capture.open((int)(video_name[0] - '0'));
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// else
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// capture.open(video_name);
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const char* WINDOW_NAME = "RTSP Fullscreen Display";
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cv::namedWindow(WINDOW_NAME, cv::WINDOW_NORMAL);
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cv::setWindowProperty(WINDOW_NAME, cv::WND_PROP_FULLSCREEN, cv::WINDOW_FULLSCREEN);
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struct timeval time;
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gettimeofday(&time, nullptr);
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@ -343,29 +343,18 @@ int post_process(int8_t *input0, int8_t *input1, int8_t *input2, int model_in_h,
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int id = classId[n];
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float obj_conf = objProbs[i];
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if (id == 0)
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{
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group->results[last_count].box.left = (int)(clamp(x1, 0, model_in_w) / scale_w);
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group->results[last_count].box.top = (int)(clamp(y1, 0, model_in_h) / scale_h);
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group->results[last_count].box.right = (int)(clamp(x2, 0, model_in_w) / scale_w);
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group->results[last_count].box.bottom = (int)(clamp(y2, 0, model_in_h) / scale_h);
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group->results[last_count].prop = obj_conf;
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char *label = labels[id];
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strncpy(group->results[last_count].name, label, OBJ_NAME_MAX_SIZE);
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group->results[last_count].box.left = (int)(clamp(x1, 0, model_in_w) / scale_w);
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group->results[last_count].box.top = (int)(clamp(y1, 0, model_in_h) / scale_h);
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group->results[last_count].box.right = (int)(clamp(x2, 0, model_in_w) / scale_w);
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group->results[last_count].box.bottom = (int)(clamp(y2, 0, model_in_h) / scale_h);
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group->results[last_count].prop = obj_conf;
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char *label = labels[id];
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strncpy(group->results[last_count].name, label, OBJ_NAME_MAX_SIZE);
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// printf("result %2d: (%4d, %4d, %4d, %4d), %s\n", i, group->results[last_count].box.left,
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// group->results[last_count].box.top,
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// group->results[last_count].box.right, group->results[last_count].box.bottom, label);
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last_count++;
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}
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// group->results[last_count].box.left = (int)(clamp(x1, 0, model_in_w) / scale_w);
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// group->results[last_count].box.top = (int)(clamp(y1, 0, model_in_h) / scale_h);
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// group->results[last_count].box.right = (int)(clamp(x2, 0, model_in_w) / scale_w);
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// group->results[last_count].box.bottom = (int)(clamp(y2, 0, model_in_h) / scale_h);
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// group->results[last_count].prop = obj_conf;
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// char *label = labels[id];
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// strncpy(group->results[last_count].name, label, OBJ_NAME_MAX_SIZE);
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// last_count++;
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// printf("result %2d: (%4d, %4d, %4d, %4d), %s\n", i, group->results[last_count].box.left,
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// group->results[last_count].box.top,
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// group->results[last_count].box.right, group->results[last_count].box.bottom, label);
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last_count++;
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}
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group->count = last_count;
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@ -281,16 +281,23 @@ cv::Mat rkYolov5s::infer(cv::Mat &orig_img)
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for (int i = 0; i < detect_result_group.count; i++)
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{
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detect_result_t *det_result = &(detect_result_group.results[i]);
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sprintf(text, "%s %.1f%%", det_result->name, det_result->prop * 100);
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// 打印预测物体的信息/Prints information about the predicted object
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// printf("%s @ (%d %d %d %d) %f\n", det_result->name, det_result->box.left, det_result->box.top,
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// det_result->box.right, det_result->box.bottom, det_result->prop);
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int x1 = det_result->box.left;
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int y1 = det_result->box.top;
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int x2 = det_result->box.right;
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int y2 = det_result->box.bottom;
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rectangle(orig_img, cv::Point(x1, y1), cv::Point(x2, y2), cv::Scalar(256, 0, 0, 256), 3);
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putText(orig_img, text, cv::Point(x1, y1 + 12), cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(255, 255, 255));
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// ========================== 修改开始 ==========================
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// 增加一个判断，只处理标签名称为 "person" 的结果
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if (strcmp(det_result->name, "person") == 0)
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{
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sprintf(text, "%s %.1f%%", det_result->name, det_result->prop * 100);
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// 打印预测物体的信息/Prints information about the predicted object
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// printf("%s @ (%d %d %d %d) %f\n", det_result->name, det_result->box.left, det_result->box.top,
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// det_result->box.right, det_result->box.bottom, det_result->prop);
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int x1 = det_result->box.left;
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int y1 = det_result->box.top;
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int x2 = det_result->box.right;
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int y2 = det_result->box.bottom;
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rectangle(orig_img, cv::Point(x1, y1), cv::Point(x2, y2), cv::Scalar(256, 0, 0, 256), 3);
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putText(orig_img, text, cv::Point(x1, y1 + 12), cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(255, 255, 255));
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}
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// ========================== 修改结束 ==========================
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}
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ret = rknn_outputs_release(ctx, io_num.n_output, outputs);
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