From a3b4b6b134bf6b9347108ecb4129ec8fd89c7aca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E7=86=8A=E7=BB=A7=E6=B7=99?= Date: Thu, 25 Apr 2024 10:38:37 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=20'Code/TestTRTInterDll/Test?= =?UTF-8?q?TRTInterDll.cpp'?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Code/TestTRTInterDll/TestTRTInterDll.cpp | 265 ----------------------- 1 file changed, 265 deletions(-) delete mode 100644 Code/TestTRTInterDll/TestTRTInterDll.cpp diff --git a/Code/TestTRTInterDll/TestTRTInterDll.cpp b/Code/TestTRTInterDll/TestTRTInterDll.cpp deleted file mode 100644 index e86b2af..0000000 --- a/Code/TestTRTInterDll/TestTRTInterDll.cpp +++ /dev/null @@ -1,265 +0,0 @@ -// TestTRTInterDll.cpp : 此文件包含 "main" 函数。程序执行将在此处开始并结束。 -// - -#include -#include -#include -#include -#include "utils.h" -#include "MI_Interface.h" -#include - - -namespace fs = std::filesystem; - -bool buffer2Mat(const MN_VisionImage::MS_ImageParam& _inImg, cv::Mat& _mat); - -void test01() -{ - std::vector imagePath; - imagePath.emplace_back("./imageDatas/daisy.jpg"); - imagePath.emplace_back("./imageDatas/dandelion.jpg"); - imagePath.emplace_back("./imageDatas/sunflower.jpg"); - imagePath.emplace_back("./imageDatas/tulip.jpg"); - - std::vector matImgs; - for (auto _var : imagePath) - { - matImgs.emplace_back(cv::imread(_var, 1)); - } - - utils::InitParameter params; - params.m_modelType = utils::ME_ModelType::E_RESNET34; - params.class_names = utils::dataSets::flower_labels; - //initParameters.class_names = utils::dataSets::voc20; - params.num_class = 5; // for flower_labels - //initParameters.num_class = 20; // for voc2012 - params.batch_size = 1; - params.dst_h = 224; - params.dst_w = 224; - memcpy(¶ms.mImage.m_data, matImgs[0].data, sizeof(matImgs[0].rows * matImgs[0].cols * matImgs[0].channels())); - params.mImage.m_height = matImgs[0].rows; - params.mImage.m_width = matImgs[0].cols; - params.mImage.m_channels = 3; - params.input_output_names = { "input", "output" }; - params.conf_thresh = 0.25f; - params.iou_thresh = 0.45f; - params.save_path = "./imageDatas"; - params.meanVec = { 0.406, 0.456, 0.485 }; - params.stdVec = { 0.225, 0.224, 0.229 }; - MI_VisionInterface* resnet34Ptr = getInterfacePtr(params); - if (!resnet34Ptr) - { - return; - } - - utils::InitParameter params1; - params1.m_modelType = utils::ME_ModelType::E_RESNET50; - params1.class_names = utils::dataSets::flower_labels; - //initParameters.class_names = utils::dataSets::voc20; - params1.num_class = 5; // for flower_labels - //initParameters.num_class = 20; // for voc2012 - params1.batch_size = 1; - params1.dst_h = 224; - params1.dst_w = 224; - memcpy(¶ms1.mImage.m_data, matImgs[0].data, sizeof(matImgs[0].rows * matImgs[0].cols * matImgs[0].channels())); - params1.mImage.m_height = matImgs[0].rows; - params1.mImage.m_width = matImgs[0].cols; - params1.mImage.m_channels = 3; - params1.input_output_names = { "input", "output" }; - params1.conf_thresh = 0.25f; - params1.iou_thresh = 0.45f; - params1.save_path = "./imageDatas"; - params1.meanVec = { 0.406, 0.456, 0.485 }; - params1.stdVec = { 0.225, 0.224, 0.229 }; - MI_VisionInterface* resnet50Ptr = getInterfacePtr(params1); - if (!resnet50Ptr) - { - return; - } - - // 线程测试，初始化在一个线程，推理在另外一个线程内 - std::string onnxFile = "./imageDatas/resnet34_0407.onnx"; - std::string onnxFile1 = "./imageDatas/resnet50.onnx"; - -#if 0 - bool bRet = false; - bRet = resnetPtr->initEngine(onnxFile); - if (!bRet) - { - return; - } - - bRet = resnetPtr->check(); - if (!bRet) - { - return; - } - - std::vector detectResVec; - bRet = resnetPtr->doTRTInfer(matImgs, &detectResVec, nullptr); - if (!bRet) - { - return; - } -#endif // 0 - - // 初始化线程 - auto initRes = std::async(std::launch::async, [&] { - - bool bRet = false; - // 加载第一个模型初始化并推理 - bRet = resnet34Ptr->initEngine(onnxFile); - if (!bRet) - { - return false; - } - - // 加载第二个模型初始化并推理 - bRet = resnet50Ptr->initEngine(onnxFile1); - if (!bRet) - { - return false; - } - - return true; - }); - initRes.wait(); - - auto initRes1 = std::async(std::launch::async, [&] { - - bool bRet = false; - bRet = resnet34Ptr->check(); - if (!bRet) - { - return false; - } - - std::vector detectResVec1; - bRet = resnet34Ptr->doTRTInfer(matImgs, &detectResVec1, nullptr); - if (!bRet) - { - return false; - } - - bRet = resnet50Ptr->check(); - if (!bRet) - { - return false; - } - - std::vector detectResVec2; - bRet = resnet50Ptr->doTRTInfer(matImgs, &detectResVec2, nullptr); - if (!bRet) - { - return false; - } - - return true; - - }); - - //initRes1.wait(); - - auto initRes2 = std::async(std::launch::async, [&] { - - bool bRet = false; - bRet = resnet34Ptr->check(); - if (!bRet) - { - return false; - } - - std::vector detectResVec1; - bRet = resnet34Ptr->doTRTInfer(matImgs, &detectResVec1, nullptr); - if (!bRet) - { - return false; - } - - bRet = resnet50Ptr->check(); - if (!bRet) - { - return false; - } - - std::vector detectResVec2; - bRet = resnet50Ptr->doTRTInfer(matImgs, &detectResVec2, nullptr); - if (!bRet) - { - return false; - } - - return true; - }); - - //initRes2.wait(); - -} - -void test02() -{ - cv::Mat img = cv::imread("./imageDatas/daisy.jpg", 1); - MN_VisionImage::MS_ImageParam bufImg((uchar*)img.data, img.cols, img.rows, MN_VisionImage::ME_ImageType::E_RGB); - - cv::Mat convertImg; - bool bRet = buffer2Mat(bufImg, convertImg); - cv::imshow("src", img); - cv::imshow("image", convertImg); - cv::waitKey(0); -} - -int main() -{ - - test01(); - - system("pause"); - return 0; -} - -// 运行程序: Ctrl + F5 或调试 >“开始执行(不调试)”菜单 -// 调试程序: F5 或调试 >“开始调试”菜单 - -bool buffer2Mat(const MN_VisionImage::MS_ImageParam& _inImg, cv::Mat& _mat) -{ - uchar* pBuf = _inImg.m_data.get(); //获取图像数据首地址 - int nW = _inImg.m_width; - int nH = _inImg.m_height; - int nChannel = _inImg.m_channels; - - if (pBuf == nullptr || nW <= 1 || nH <= 1) - { - // LOG_ERROR("convert buffer to mat, input image error. \n"); - return false; - } - - if (_inImg.mImgType == MN_VisionImage::ME_ImageType::E_GRAY) - { - _mat = cv::Mat(nH, nW, CV_8UC1, pBuf); - } - else if (_inImg.mImgType == MN_VisionImage::ME_ImageType::E_RGBA) - { - _mat = cv::Mat(nH, nW, CV_8UC4, pBuf); - } - else - { - _mat = cv::Mat(nH, nW, CV_8UC3, pBuf); - } - - if (_mat.data == nullptr || _mat.cols <= 1 || _mat.rows <= 1) - { - // LOG_ERROR("convert buffer to mat, convert image failed. \n"); - return false; - } - - return true; -} - - -// 0.3 * 0.3 - 12寸晶圆， 一次性识别9颗 -- 测试推理时间 -/* -1. 芯片分类：正常，边缘，蓝膜 -2. 对于正常的芯片进行检测--针对划痕和脏污分两个模型/或者一个模型； -3. 针对针测点检测 -- 传统算法； -*/ \ No newline at end of file