Improve YOLOv8 ONNX Runtime c++ example for all OS with `CmakeList.txt` support (#4274)
Signed-off-by: Onuralp SEZER <thunderbirdtr@fedoraproject.org> Signed-off-by: Onuralp SEZER <thunderbirdtr@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>single_channel
Onuralp SEZER
1 year ago
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GitHub
parent
c9be1f3cce
commit
22474e9ad5
@ -0,0 +1,71 @@
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cmake_minimum_required(VERSION 3.5)
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set(PROJECT_NAME Yolov8OnnxRuntimeCPPInference)
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project(${PROJECT_NAME} VERSION 0.0.1 LANGUAGES CXX)
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# -------------- Support C++17 for using filesystem ------------------#
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set(CMAKE_CXX_STANDARD 17)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CMAKE_CXX_EXTENSIONS ON)
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set(CMAKE_INCLUDE_CURRENT_DIR ON)
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# OpenCV
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find_package(OpenCV REQUIRED)
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include_directories(${OpenCV_INCLUDE_DIRS})
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# ONNXRUNTIME
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# Set ONNXRUNTIME_VERSION
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set(ONNXRUNTIME_VERSION 1.15.1)
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if(WIN32)
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# CPU
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# set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-win-x64-${ONNXRUNTIME_VERSION}")
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# GPU
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set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-win-x64-gpu-${ONNXRUNTIME_VERSION}")
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elseif(LINUX)
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# CPU
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# set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}")
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# GPU
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set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-linux-x64-gpu-${ONNXRUNTIME_VERSION}")
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elseif(APPLE)
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set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-osx-arm64-${ONNXRUNTIME_VERSION}")
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# Apple X64 binary
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# set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-osx-x64-${ONNXRUNTIME_VERSION}")
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# Apple Universal binary
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# set(ONNXRUNTIME_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/onnxruntime-osx-universal2-${ONNXRUNTIME_VERSION}")
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endif()
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include_directories(${PROJECT_NAME} ${ONNXRUNTIME_ROOT}/include)
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set(PROJECT_SOURCES
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main.cpp
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inference.h
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inference.cpp
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)
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add_executable(${PROJECT_NAME} ${PROJECT_SOURCES})
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if(WIN32)
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target_link_libraries(${PROJECT_NAME} ${OpenCV_LIBS} ${ONNXRUNTIME_ROOT}/lib/onnxruntime.lib)
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elseif(LINUX)
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target_link_libraries(${PROJECT_NAME} ${OpenCV_LIBS} ${ONNXRUNTIME_ROOT}/lib/libonnxruntime.so)
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elseif(APPLE)
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target_link_libraries(${PROJECT_NAME} ${OpenCV_LIBS} ${ONNXRUNTIME_ROOT}/lib/libonnxruntime.dylib)
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endif()
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# For windows system, copy onnxruntime.dll to the same folder of the executable file
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if(WIN32)
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add_custom_command(TARGET ${PROJECT_NAME} POST_BUILD
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COMMAND ${CMAKE_COMMAND} -E copy_if_different
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"${ONNXRUNTIME_ROOT}/lib/onnxruntime.dll"
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$<TARGET_FILE_DIR:${PROJECT_NAME}>)
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endif()
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# Download https://raw.githubusercontent.com/ultralytics/ultralytics/main/ultralytics/cfg/datasets/coco.yaml
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# and put it in the same folder of the executable file
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configure_file(coco.yaml ${CMAKE_CURRENT_BINARY_DIR}/coco.yaml COPYONLY)
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@ -1,44 +1,94 @@
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#include <iostream>
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#include <stdio.h>
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#include "inference.h"
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#include <filesystem>
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#include <fstream>
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void file_iterator(DCSP_CORE*& p)
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{
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std::filesystem::path img_path = R"(E:\project\Project_C++\DCPS_ONNX\TEST_ORIGIN)";
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int k = 0;
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for (auto& i : std::filesystem::directory_iterator(img_path))
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std::filesystem::path current_path = std::filesystem::current_path();
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std::filesystem::path imgs_path = current_path/"images";
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for (auto& i : std::filesystem::directory_iterator(imgs_path))
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{
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if (i.path().extension() == ".jpg")
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if (i.path().extension() == ".jpg" || i.path().extension() == ".png")
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{
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std::string img_path = i.path().string();
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//std::cout << img_path << std::endl;
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cv::Mat img = cv::imread(img_path);
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std::vector<DCSP_RESULT> res;
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char* ret = p->RunSession(img, res);
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for (int i = 0; i < res.size(); i++)
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p->RunSession(img, res);
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for (auto & re : res)
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{
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cv::rectangle(img, res.at(i).box, cv::Scalar(125, 123, 0), 3);
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cv::rectangle(img, re.box, cv::Scalar(0, 0 , 255), 3);
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std::string label = p->classes[re.classId];
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cv::putText(
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img,
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label,
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cv::Point(re.box.x, re.box.y - 5),
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cv::FONT_HERSHEY_SIMPLEX,
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0.75,
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cv::Scalar(255, 255, 0),
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2
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);
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}
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k++;
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cv::imshow("TEST_ORIGIN", img);
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cv::imshow("Result", img);
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cv::waitKey(0);
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cv::destroyAllWindows();
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//cv::imwrite("E:\\output\\" + std::to_string(k) + ".png", img);
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}
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}
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}
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int read_coco_yaml(DCSP_CORE*& p)
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{
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// Open the YAML file
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std::ifstream file("coco.yaml");
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if (!file.is_open()) {
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std::cerr << "Failed to open file" << std::endl;
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return 1;
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}
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// Read the file line by line
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std::string line;
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std::vector<std::string> lines;
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while (std::getline(file, line)) {
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lines.push_back(line);
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}
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// Find the start and end of the names section
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std::size_t start = 0;
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std::size_t end = 0;
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for (std::size_t i = 0; i < lines.size(); i++) {
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if (lines[i].find("names:") != std::string::npos) {
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start = i + 1;
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} else if (start > 0 && lines[i].find(':') == std::string::npos) {
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end = i;
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break;
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}
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}
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// Extract the names
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std::vector<std::string> names;
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for (std::size_t i = start; i < end; i++) {
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std::stringstream ss(lines[i]);
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std::string name;
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std::getline(ss, name, ':'); // Extract the number before the delimiter
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std::getline(ss, name); // Extract the string after the delimiter
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names.push_back(name);
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}
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p->classes = names;
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return 0;
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}
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int main()
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{
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DCSP_CORE* p1 = new DCSP_CORE;
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std::string model_path = "yolov8n.onnx";
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DCSP_INIT_PARAM params{ model_path, YOLO_ORIGIN_V8, {640, 640}, 80, 0.1, 0.5, false };
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char* ret = p1->CreateSession(params);
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read_coco_yaml(p1);
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// GPU inference
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DCSP_INIT_PARAM params{ model_path, YOLO_ORIGIN_V8, {640, 640}, 0.1, 0.5, true };
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// CPU inference
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// DCSP_INIT_PARAM params{ model_path, YOLO_ORIGIN_V8, {640, 640}, 0.1, 0.5, false };
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p1->CreateSession(params);
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file_iterator(p1);
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}
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