踩坑RV1106板端部署rknn模型

1、交叉编译

官方给的一个流程: RKNN 模型推理测试为了避免踩坑在开头提出来

按照官方的流程可以跑通，他自己提供的yolov5s.rknn（640*640）的模型，但是跑自己的模型的时候加载就会出错E RKNN: failed to decode config data!Segmentation fault (core dumped)，应该是这个地址的链接版本太老了，并且给出来的demo预处理也没有使用librga做硬件加速，直接跳过，官方也给出来了说这个github链接不在维护（https://github.com/rockchip-linux/rknpu2）

官方最新地址: rknn-toolkit2
所有实例程序就都在这里了
工具包库: rknn_model_zoo
下载下来

交叉编译需要先安装 LuckFox Pico SDK

git clone https://gitee.com/LuckfoxTECH/luckfox-pico.git
Pico SDK：https://github.com/LuckfoxTECH/luckfox-pico/

在 rknn_model_zoo目录下我们现在对这些例程进行交叉编译，编译例程前需要设置如下环境变量：

export RK_RV1106_TOOLCHAIN=<SDK目录>/tools/linux/toolchain/arm-rockchip830-linux-uclibcgnueabihf/bin/arm-rockchip830-linux-uclibcgnueabihf

# 这个SDK目录目录就是你刚才Pico SDK放的地址

cmake要求必须大于3.15，不满足自行百度解决

chmod a+x ./build-linux.sh
./build-linux.sh -t rv1106 -a armv7l -d yolov5

-t : target (rk356x/rk3588/rv1106)
-a : arch (aarch64/armhf)
-d : demo name
-b : build_type(Debug/Release)
-m : enable address sanitizer, build_type need set to Debug

编译完成之后会在当前目录下生成一个install目录进入里面就可以找到编译出来的程序和库和模型文件

2、板上跑通

通过adb，将库和model下的文件文件都推上去

# 跑通官方模型
./rknn_yolov5_demo ./model/exp415_best.onnx_sim_new1.rknn ./model/car_1012.jpg

# 通过adb将图片从板子上取出来
adb pull /root/yolov5/out.jpg .

可以看到没有任何问题，但是这就是最大的问题

3、验证自己模型

如果直接拿自己的模型不修改代码，直接推理，会出现这种报错，就是类别没有对上

从原本80修改成实际类别数，还有板上model目录下的coco_80_labels_list.txt文件也需要修改成你的类别名

进行推理

# 我的模型输出
model input height=224, width=384, channel=3

推理出来的结果就是这样子了，矩形框都是错乱的

这个文件就是源码里面埋了很大一个坑，取反了，模型输入要求是NHWC，但是他将h取到w上面了，所以出现错乱，为什么官方自己的模型没问题推理是正常的，因为官方的是640*640，高宽尺寸是一致的，所以没有出现这个bug

修改之后再次验证正常了

4、编译使用

将示例程序封装成so动态库，嵌入到其他地方使用

cmake文件，任使用官方给的脚本进行调用./build-linux.sh -t rv1106 -a armv7l -d yolov5

cmake_minimum_required(VERSION 3.10)

project(rknn_yolov5_demo)

if (ENABLE_ASAN)
	message(STATUS "BUILD WITH ADDRESS SANITIZER")
	set (CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
	set (CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
	set (CMAKE_LINKER_FLAGS_DEBUG "${CMAKE_LINKER_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
endif ()

set(rknpu2_yolov5_file rknpu2/yolov5.cc)
if (TARGET_SOC STREQUAL "rv1106" OR TARGET_SOC STREQUAL "rv1103")
    add_definitions(-DRV1106_1103)
    set(rknpu2_yolov5_file rknpu2/yolov5_rv1106_1103.cc)
    #dma
    #include_directories(/root/anaconda3/envs/RKNN/rknn-toolkit2/rknpu2/runtime/Linux/librknn_api/include)
    include_directories(${CMAKE_CURRENT_SOURCE_DIR}/../../../3rdparty/allocator/dma)
endif()

add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/../../../3rdparty/ 3rdparty.out)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/../../../utils/ utils.out)

set(CMAKE_INSTALL_RPATH "$ORIGIN/lib")

file(GLOB SRCS ${CMAKE_CURRENT_SOURCE_DIR}/*.cc)

# 为 utils.out 生成位置无关代码
set_target_properties(imageutils PROPERTIES POSITION_INDEPENDENT_CODE ON)
set_target_properties(fileutils PROPERTIES POSITION_INDEPENDENT_CODE ON)
set_target_properties(imagedrawing PROPERTIES POSITION_INDEPENDENT_CODE ON)

add_library(${PROJECT_NAME} SHARED
    main.cc
    postprocess.cc
    ${rknpu2_yolov5_file}
)

target_link_libraries(${PROJECT_NAME}
    imageutils
    fileutils
    imagedrawing    
    ${LIBRKNNRT}
)

if (CMAKE_SYSTEM_NAME STREQUAL "Android")
    target_link_libraries(${PROJECT_NAME}
    log
)
endif()

if (CMAKE_SYSTEM_NAME STREQUAL "Linux")
    set(THREADS_PREFER_PTHREAD_FLAG ON)
    find_package(Threads REQUIRED)
    target_link_libraries(${PROJECT_NAME} Threads::Threads)
endif()

target_include_directories(${PROJECT_NAME} PRIVATE
    ${CMAKE_CURRENT_SOURCE_DIR}
    ${LIBRKNNRT_INCLUDES}
)

install(TARGETS ${PROJECT_NAME} DESTINATION .)
install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/../model/bus.jpg DESTINATION ./model)
install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/../model/coco_80_labels_list.txt DESTINATION ./model)
file(GLOB RKNN_FILES "${CMAKE_CURRENT_SOURCE_DIR}/../model/*.rknn")
install(FILES ${RKNN_FILES} DESTINATION model)

编写cpp进行调用封装的库，进行推理cmake文件

cmake_minimum_required(VERSION 3.10)

project(rknn_yolov5_test)

if (ENABLE_ASAN)
	message(STATUS "BUILD WITH ADDRESS SANITIZER")
	set (CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
	set (CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
	set (CMAKE_LINKER_FLAGS_DEBUG "${CMAKE_LINKER_FLAGS_DEBUG} -fno-omit-frame-pointer -fsanitize=address")
endif ()

set(rknpu2_yolov5_file rknpu2/yolov5.cc)
if (TARGET_SOC STREQUAL "rv1106" OR TARGET_SOC STREQUAL "rv1103")
    add_definitions(-DRV1106_1103)
    set(rknpu2_yolov5_file rknpu2/yolov5_rv1106_1103.cc)
    #dma
    #include_directories(/root/anaconda3/envs/RKNN/rknn-toolkit2/rknpu2/runtime/Linux/librknn_api/include)
    include_directories(${CMAKE_CURRENT_SOURCE_DIR}/../../../3rdparty/allocator/dma)
endif()

add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/../../../3rdparty/ 3rdparty.out)
add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/../../../utils/ utils.out)

set(CMAKE_INSTALL_RPATH "$ORIGIN/lib")

link_directories(/root/anaconda3/envs/RKNN/rknn_model_zoo/build/build_rknn_yolov5_demo_rv1106_linux_armv7l_Release)

file(GLOB SRCS ${CMAKE_CURRENT_SOURCE_DIR}/*.cc)


add_executable(${PROJECT_NAME}
    main.cpp
)

target_link_libraries(${PROJECT_NAME}
    rknn_yolov5_demo
    imageutils
    fileutils
    imagedrawing    
    ${LIBRKNNRT}
)

if (CMAKE_SYSTEM_NAME STREQUAL "Android")
    target_link_libraries(${PROJECT_NAME}
    log
)
endif()

if (CMAKE_SYSTEM_NAME STREQUAL "Linux")
    set(THREADS_PREFER_PTHREAD_FLAG ON)
    find_package(Threads REQUIRED)
    target_link_libraries(${PROJECT_NAME} Threads::Threads)
endif()

target_include_directories(${PROJECT_NAME} PRIVATE
    ${CMAKE_CURRENT_SOURCE_DIR}
    ${LIBRKNNRT_INCLUDES}
)

install(TARGETS ${PROJECT_NAME} DESTINATION .)
install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/../model/bus.jpg DESTINATION ./model)
install(FILES ${CMAKE_CURRENT_SOURCE_DIR}/../model/coco_80_labels_list.txt DESTINATION ./model)
file(GLOB RKNN_FILES "${CMAKE_CURRENT_SOURCE_DIR}/../model/*.rknn")
install(FILES ${RKNN_FILES} DESTINATION model)

5、opencv安装测试

cd opencv
mkdir build
cd build

// 编译
cmake -D CMAKE_BUILD_TYPE=Release -D OPENCV_GENERATE_PKGCONFIG=YES ..

make -j4

sudo make install

默认安装路径为：
/usr/local/bin - executable files
/usr/local/lib - libraries (.so)
/usr/local/cmake/opencv4 - cmake package
/usr/local/include/opencv4 - headers
/usr/local/share/opencv4 - other files (e.g. trained cascades in XML format)

// 环境配置
sudo find / -iname opencv4.pc

vim ~/.bashrc
export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:$PKG_CONFIG_PATH

source ~/.bashrc

// 查看
pkg-config --libs opencv4

// 配置动态库
sudo vim /etc/ld.so.conf.d/opencv4.conf
/usr/local/lib
sudo ldconfig

cd opencv/samples/cpp/example_cmake目录下，依次执行以下命令：
cmake .
make
./opencv_example

测试main.cpp

#include 
#include 
#include 
using namespace cv;
using namespace std;
int main(int argc, char** argv )
{

    if ( argc != 2 )
    {
        cout<<"usage: DisplayImage.out \n";
        return -1;
    }
    Mat image;
    image = imread( argv[1], 1 );
    if ( !image.data )
    {
        cout<<"No image data \n";
        return -1;
    }
    namedWindow("Display Image", WINDOW_AUTOSIZE );
    imshow("Display Image", image);
    waitKey(0);
    return 0;
}

touch CMakeLists.txt

# cmake needs this line
cmake_minimum_required(VERSION 3.1)

# Define project name
project(img)

# Find OpenCV, you may need to set OpenCV_DIR variable
# to the absolute path to the directory containing OpenCVConfig.cmake file
# via the command line or GUI
find_package(OpenCV REQUIRED)

# Enable C++11
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED TRUE)

# Declare the executable target built from your sources
add_executable(img main.cpp)

# Link your application with OpenCV libraries
target_link_libraries(img PRIVATE ${OpenCV_LIBS})

测试使用

cmake .
make
./img 1.jpg