网站移动端是什么问题,优质网站排名公司,一条视频可以多平台发布吗,做网站点击挣钱不文章目录 一. yolov5 v6.0训练模型二.训练好的yolov5模型转tensorrt引擎 一. yolov5 v6.0训练模型 官网下载yolov5 v6.0代码 下载官方预训练好的模型 安装yolov5所需要的库文件#xff0c;requirements.txt在下载好的yolov5源代码中有 pip install -r C:\Users\10001540… 文章目录 一. yolov5 v6.0训练模型二.训练好的yolov5模型转tensorrt引擎 一. yolov5 v6.0训练模型 官网下载yolov5 v6.0代码 下载官方预训练好的模型 安装yolov5所需要的库文件requirements.txt在下载好的yolov5源代码中有 pip install -r C:\Users\10001540\Downloads\yolov5-6.0\requirements.txt打开yolov5源代码中的detect.py文件修改模型的位置 运行后可能出现各种错误可以去参考网上的教程
二.训练好的yolov5模型转tensorrt引擎 去tensorrtx官网下载代码 将tensorrtx下的yolov5中的gen_wts.py复制到yolov5源代码文件夹中 参考yolov5官方说明将yolov5模型文件yolov5s.pt转换为yolov5s.wts文件 python gen_wts.py -w weights/yolov5s.pt -o yolov5s.wts进入tensorrtx下的yolov5文件夹修改里面的CMakeList.txt如下 cmake_minimum_required(VERSION 2.6)project(yolov5) #1
set(OpenCV_DIR D:\\Program Files\\opencv\\build) #2
set(OpenCV_INCLUDE_DIRS ${OpenCV_DIR}\\include) #3
set(OpenCV_LIB_DIRS ${OpenCV_DIR}\\x64\\vc15\\lib) #4
set(OpenCV_Debug_LIBS opencv_world454d.lib) #5
set(OpenCV_Release_LIBS opencv_world454.lib) #6
set(TRT_DIR C:\\Program Files\\NVIDIA GPU Computing Toolkit\\TensorRT-8.2.3.0) #7
set(TRT_INCLUDE_DIRS ${TRT_DIR}\\include) #8
set(TRT_LIB_DIRS ${TRT_DIR}\\lib) #9
set(Dirent_INCLUDE_DIRS Z:\\code\\dirent-master\\include) #10add_definitions(-stdc11)
add_definitions(-DAPI_EXPORTS)option(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_BUILD_TYPE Debug)set(THREADS_PREFER_PTHREAD_FLAG ON)
find_package(Threads)# setup CUDA
find_package(CUDA REQUIRED)
message(STATUS libraries: ${CUDA_LIBRARIES})
message(STATUS include path: ${CUDA_INCLUDE_DIRS})include_directories(${CUDA_INCLUDE_DIRS})####
enable_language(CUDA) # add this line, then no need to setup cuda path in vs
####
include_directories(${PROJECT_SOURCE_DIR}/include) #11
include_directories(${TRT_INCLUDE_DIRS}) #12
link_directories(${TRT_LIB_DIRS}) #13
include_directories(${OpenCV_INCLUDE_DIRS}) #14
link_directories(${OpenCV_LIB_DIRS}) #15
include_directories(${Dirent_INCLUDE_DIRS}) #16# -D_MWAITXINTRIN_H_INCLUDED for solving error: identifier __builtin_ia32_mwaitx is undefined
set(CMAKE_CXX_FLAGS ${CMAKE_CXX_FLAGS} -stdc11 -Wall -Ofast -D_MWAITXINTRIN_H_INCLUDED)# setup opencv
find_package(OpenCV QUIETNO_MODULENO_DEFAULT_PATHNO_CMAKE_PATHNO_CMAKE_ENVIRONMENT_PATHNO_SYSTEM_ENVIRONMENT_PATHNO_CMAKE_PACKAGE_REGISTRYNO_CMAKE_BUILDS_PATHNO_CMAKE_SYSTEM_PATHNO_CMAKE_SYSTEM_PACKAGE_REGISTRY
)message(STATUS OpenCV library status:)
message(STATUS version: ${OpenCV_VERSION})
message(STATUS lib path: ${OpenCV_LIB_DIRS})
message(STATUS Debug libraries: ${OpenCV_Debug_LIBS})
message(STATUS Release libraries: ${OpenCV_Release_LIBS})
message(STATUS include path: ${OpenCV_INCLUDE_DIRS})add_executable(yolov5 ${PROJECT_SOURCE_DIR}/yolov5.cpp ${PROJECT_SOURCE_DIR}/common.hpp ${PROJECT_SOURCE_DIR}/yololayer.cu ${PROJECT_SOURCE_DIR}/yololayer.h ${PROJECT_SOURCE_DIR}/preprocess.cu ${PROJECT_SOURCE_DIR}/preprocess.h) #17target_link_libraries(yolov5 nvinfer nvinfer_plugin) #18
target_link_libraries(yolov5 debug ${OpenCV_Debug_LIBS}) #19
target_link_libraries(yolov5 optimized ${OpenCV_Release_LIBS}) #20
target_link_libraries(yolov5 ${CUDA_LIBRARIES}) #21
target_link_libraries(yolov5 Threads::Threads) if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
set(CMAKE_CUDA_ARCHITECTURES 70 75 80 86)
endif(NOT DEFINED CMAKE_CUDA_ARCHITECTURES) 这里需要注意 在tensorrtx下的yolov5文件夹中打开cmd输入以下代码 mkdir build
cd build
cmake ..进入build文件夹用vs打开yolov5.sln文件然后点击生成生成解决方案 出现以下这说明生成成功 设置yolov5为启动项 进入yolov5属性页调试选项设置如下 设置完成运行程序 运行可能需要花费一定的时间出现以下这说明模型转换成功 测试生成的模型在属性页面中设置如下 出现以下内容这说明运行成功
