Walter
GitHub
commit
7afad4517d
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@ -1,4 +1,5 @@
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project(clas_system CXX C)
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cmake_minimum_required(VERSION 3.14)
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option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON)
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option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." OFF)
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@ -13,7 +14,6 @@ SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
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set(DEMO_NAME "clas_system")
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macro(safe_set_static_flag)
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foreach(flag_var
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CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
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@ -198,6 +198,10 @@ endif()
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set(DEPS ${DEPS} ${OpenCV_LIBS})
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include(FetchContent)
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include(external-cmake/auto-log.cmake)
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include_directories(${FETCHCONTENT_BASE_DIR}/extern_autolog-src)
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AUX_SOURCE_DIRECTORY(./src SRCS)
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add_executable(${DEMO_NAME} ${SRCS})
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@ -0,0 +1,12 @@
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find_package(Git REQUIRED)
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include(FetchContent)
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set(FETCHCONTENT_BASE_DIR "${CMAKE_CURRENT_BINARY_DIR}/third-party")
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FetchContent_Declare(
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extern_Autolog
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PREFIX autolog
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GIT_REPOSITORY https://github.com/LDOUBLEV/AutoLog.git
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GIT_TAG main
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)
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FetchContent_MakeAvailable(extern_Autolog)
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@ -61,7 +61,7 @@ public:
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void LoadModel(const std::string &model_path, const std::string ¶ms_path);
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// Run predictor
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double Run(cv::Mat &img);
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double Run(cv::Mat &img, std::vector<double> *times);
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private:
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std::shared_ptr<Predictor> predictor_;
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@ -1,4 +1,4 @@
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// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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@ -36,8 +36,7 @@ public:
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this->gpu_mem = stoi(config_map_["gpu_mem"]);
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this->cpu_math_library_num_threads =
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stoi(config_map_["cpu_math_library_num_threads"]);
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this->cpu_threads = stoi(config_map_["cpu_threads"]);
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this->use_mkldnn = bool(stoi(config_map_["use_mkldnn"]));
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@ -51,6 +50,8 @@ public:
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this->resize_short_size = stoi(config_map_["resize_short_size"]);
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this->crop_size = stoi(config_map_["crop_size"]);
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this->benchmark = bool(stoi(config_map_["benchmark"]));
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}
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bool use_gpu = false;
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@ -59,12 +60,13 @@ public:
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int gpu_mem = 4000;
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int cpu_math_library_num_threads = 1;
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int cpu_threads = 1;
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bool use_mkldnn = false;
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bool use_tensorrt = false;
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bool use_fp16 = false;
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bool benchmark = false;
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std::string cls_model_path;
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@ -12,7 +12,6 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <chrono>
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#include <include/cls.h>
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namespace PaddleClas {
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@ -53,11 +52,12 @@ void Classifier::LoadModel(const std::string &model_path,
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this->predictor_ = CreatePredictor(config);
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}
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double Classifier::Run(cv::Mat &img) {
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double Classifier::Run(cv::Mat &img, std::vector<double> *times) {
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cv::Mat srcimg;
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cv::Mat resize_img;
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img.copyTo(srcimg);
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auto preprocess_start = std::chrono::system_clock::now();
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this->resize_op_.Run(img, resize_img, this->resize_short_size_);
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this->crop_op_.Run(resize_img, this->crop_size_);
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@ -70,7 +70,9 @@ double Classifier::Run(cv::Mat &img) {
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auto input_names = this->predictor_->GetInputNames();
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auto input_t = this->predictor_->GetInputHandle(input_names[0]);
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input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
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auto start = std::chrono::system_clock::now();
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auto preprocess_end = std::chrono::system_clock::now();
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auto infer_start = std::chrono::system_clock::now();
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input_t->CopyFromCpu(input.data());
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this->predictor_->Run();
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@ -83,21 +85,29 @@ double Classifier::Run(cv::Mat &img) {
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out_data.resize(out_num);
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output_t->CopyToCpu(out_data.data());
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auto end = std::chrono::system_clock::now();
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auto duration =
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std::chrono::duration_cast<std::chrono::microseconds>(end - start);
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double cost_time = double(duration.count()) *
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std::chrono::microseconds::period::num /
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std::chrono::microseconds::period::den;
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auto infer_end = std::chrono::system_clock::now();
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auto postprocess_start = std::chrono::system_clock::now();
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int maxPosition =
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max_element(out_data.begin(), out_data.end()) - out_data.begin();
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auto postprocess_end = std::chrono::system_clock::now();
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std::chrono::duration<float> preprocess_diff =
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preprocess_end - preprocess_start;
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times->push_back(double(preprocess_diff.count() * 1000));
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std::chrono::duration<float> inference_diff = infer_end - infer_start;
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double inference_cost_time = double(inference_diff.count() * 1000);
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times->push_back(inference_cost_time);
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std::chrono::duration<float> postprocess_diff =
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postprocess_end - postprocess_start;
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times->push_back(double(postprocess_diff.count() * 1000));
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std::cout << "result: " << std::endl;
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std::cout << "\tclass id: " << maxPosition << std::endl;
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std::cout << std::fixed << std::setprecision(10)
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<< "\tscore: " << double(out_data[maxPosition]) << std::endl;
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return cost_time;
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return inference_cost_time;
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}
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} // namespace PaddleClas
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@ -1,4 +1,4 @@
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// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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@ -26,6 +26,7 @@
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#include <fstream>
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#include <numeric>
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#include <auto_log/autolog.h>
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#include <include/cls.h>
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#include <include/cls_config.h>
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@ -61,11 +62,12 @@ int main(int argc, char **argv) {
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Classifier classifier(config.cls_model_path, config.cls_params_path,
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config.use_gpu, config.gpu_id, config.gpu_mem,
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config.cpu_math_library_num_threads, config.use_mkldnn,
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config.cpu_threads, config.use_mkldnn,
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config.use_tensorrt, config.use_fp16,
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config.resize_short_size, config.crop_size);
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double elapsed_time = 0.0;
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std::vector<double> cls_times;
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int warmup_iter = img_files_list.size() > 5 ? 5 : 0;
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for (int idx = 0; idx < img_files_list.size(); ++idx) {
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std::string img_path = img_files_list[idx];
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@ -78,7 +80,7 @@ int main(int argc, char **argv) {
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cv::cvtColor(srcimg, srcimg, cv::COLOR_BGR2RGB);
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double run_time = classifier.Run(srcimg);
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double run_time = classifier.Run(srcimg, &cls_times);
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if (idx >= warmup_iter) {
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elapsed_time += run_time;
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std::cout << "Current image path: " << img_path << std::endl;
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@ -90,5 +92,16 @@ int main(int argc, char **argv) {
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}
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}
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std::string presion = "fp32";
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if (config.use_fp16)
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presion = "fp16";
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if (config.benchmark) {
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AutoLogger autolog("Classification", config.use_gpu, config.use_tensorrt,
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config.use_mkldnn, config.cpu_threads, 1,
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"1, 3, 224, 224", presion, cls_times,
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img_files_list.size());
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autolog.report();
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}
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return 0;
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}
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@ -1,5 +1,5 @@
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OPENCV_DIR=/PaddleClas/opencv-3.4.7/opencv3/
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LIB_DIR=/PaddleClas/fluid_inference/
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OPENCV_DIR=/work/project/project/cpp_infer/opencv-3.4.7/opencv3
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LIB_DIR=/work/project/project/cpp_infer/paddle_inference/
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CUDA_LIB_DIR=/usr/local/cuda/lib64
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CUDNN_LIB_DIR=/usr/lib/x86_64-linux-gnu/
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@ -2,7 +2,7 @@
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use_gpu 0
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gpu_id 0
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gpu_mem 4000
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cpu_math_library_num_threads 10
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cpu_threads 10
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use_mkldnn 1
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use_tensorrt 0
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use_fp16 0
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@ -12,3 +12,6 @@ cls_model_path /PaddleClas/inference/cls_infer.pdmodel
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cls_params_path /PaddleClas/inference/cls_infer.pdiparams
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resize_short_size 256
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crop_size 224
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# for log env info
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benchmark 0
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@ -49,3 +49,10 @@ inference:python/predict_cls.py -c configs/inference_cls.yaml
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-o Global.save_log_path:null
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-o Global.benchmark:True
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null:null
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null:null
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===========================cpp_infer_params===========================
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use_gpu:0|1
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cpu_threads:1|6
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use_mkldnn:0|1
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use_tensorrt:0|1
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use_fp16:0|1
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@ -0,0 +1,19 @@
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# model load config
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gpu_id 0
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gpu_mem 2000
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# whole chain test will add following config
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# use_gpu 0
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# cpu_threads 10
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# use_mkldnn 1
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# use_tensorrt 0
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# use_fp16 0
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# cls config
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cls_model_path ../inference/inference.pdmodel
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cls_params_path ../inference/inference.pdiparams
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resize_short_size 256
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crop_size 224
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# for log env info
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benchmark 1
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@ -33,7 +33,7 @@ if [ ${MODE} = "lite_train_infer" ] || [ ${MODE} = "whole_infer" ];then
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mv train.txt train_list.txt
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mv val.txt val_list.txt
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cd ../../
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elif [ ${MODE} = "infer" ];then
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elif [ ${MODE} = "infer" ] || [ ${MODE} = "cpp_infer" ];then
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# download data
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cd dataset
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rm -rf ILSVRC2012
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@ -58,3 +58,63 @@ elif [ ${MODE} = "whole_train_infer" ];then
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mv val.txt val_list.txt
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cd ../../
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fi
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if [ ${MODE} = "cpp_infer" ];then
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cd deploy/cpp
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echo "################### build opencv ###################"
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rm -rf 3.4.7.tar.gz opencv-3.4.7/
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wget https://github.com/opencv/opencv/archive/3.4.7.tar.gz
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tar -xf 3.4.7.tar.gz
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install_path=$(pwd)/opencv-3.4.7/opencv3
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cd opencv-3.4.7/
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rm -rf build
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mkdir build
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cd build
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cmake .. \
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-DCMAKE_INSTALL_PREFIX=${install_path} \
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-DCMAKE_BUILD_TYPE=Release \
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-DBUILD_SHARED_LIBS=OFF \
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-DWITH_IPP=OFF \
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-DBUILD_IPP_IW=OFF \
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-DWITH_LAPACK=OFF \
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-DWITH_EIGEN=OFF \
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-DCMAKE_INSTALL_LIBDIR=lib64 \
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-DWITH_ZLIB=ON \
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-DBUILD_ZLIB=ON \
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-DWITH_JPEG=ON \
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-DBUILD_JPEG=ON \
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-DWITH_PNG=ON \
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-DBUILD_PNG=ON \
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-DWITH_TIFF=ON \
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-DBUILD_TIFF=ON
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make -j
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make install
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cd ../../
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echo "################### build opencv finished ###################"
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echo "################### build PaddleClas demo ####################"
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OPENCV_DIR=$(pwd)/opencv-3.4.7/opencv3/
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LIB_DIR=$(pwd)/Paddle/build/paddle_inference_install_dir/
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CUDA_LIB_DIR=$(dirname `find /usr -name libcudart.so`)
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CUDNN_LIB_DIR=$(dirname `find /usr -name libcudnn.so`)
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BUILD_DIR=build
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rm -rf ${BUILD_DIR}
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mkdir ${BUILD_DIR}
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cd ${BUILD_DIR}
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cmake .. \
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-DPADDLE_LIB=${LIB_DIR} \
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-DWITH_MKL=ON \
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-DDEMO_NAME=clas_system \
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-DWITH_GPU=OFF \
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-DWITH_STATIC_LIB=OFF \
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-DWITH_TENSORRT=OFF \
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-DTENSORRT_DIR=${TENSORRT_DIR} \
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-DOPENCV_DIR=${OPENCV_DIR} \
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-DCUDNN_LIB=${CUDNN_LIB_DIR} \
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-DCUDA_LIB=${CUDA_LIB_DIR} \
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make -j
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echo "################### build PaddleClas demo finished ###################"
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fi
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@ -1,6 +1,6 @@
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#!/bin/bash
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FILENAME=$1
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# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer']
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# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer', 'cpp_infer']
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MODE=$2
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dataline=$(cat ${FILENAME})
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@ -145,10 +145,80 @@ benchmark_value=$(func_parser_value "${lines[49]}")
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infer_key1=$(func_parser_key "${lines[50]}")
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infer_value1=$(func_parser_value "${lines[50]}")
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if [ ${MODE} = "cpp_infer" ]; then
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cpp_use_gpu_key=$(func_parser_key "${lines[53]}")
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cpp_use_gpu_list=$(func_parser_value "${lines[53]}")
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cpp_cpu_threads_key=$(func_parser_key "${lines[54]}")
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cpp_cpu_threads_list=$(func_parser_value "${lines[54]}")
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cpp_use_mkldnn_key=$(func_parser_key "${lines[55]}")
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cpp_use_mkldnn_list=$(func_parser_value "${lines[55]}")
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cpp_use_tensorrt_key=$(func_parser_key "${lines[56]}")
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cpp_use_tensorrt_list=$(func_parser_value "${lines[56]}")
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cpp_use_fp16_key=$(func_parser_key "${lines[57]}")
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cpp_use_fp16_list=$(func_parser_value "${lines[57]}")
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fi
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LOG_PATH="./tests/output"
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mkdir -p ${LOG_PATH}
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status_log="${LOG_PATH}/results.log"
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function func_cpp_inference(){
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IFS='|'
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_script=$1
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_log_path=$2
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_img_dir=$3
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# inference
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for use_gpu in ${cpp_use_gpu_list[*]}; do
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if [ ${use_gpu} = "0" ] || [ ${use_gpu} = "cpu" ]; then
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for use_mkldnn in ${cpp_use_mkldnn_list[*]}; do
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if [ ${use_mkldnn} = "0" ] && [ ${_flag_quant} = "True" ]; then
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continue
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fi
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for threads in ${cpp_cpu_threads_list[*]}; do
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_save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}.log"
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set_infer_data=$(func_set_params "${cpp_image_dir_key}" "${_img_dir}")
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cp ../tests/config/cpp_config.txt cpp_config.txt
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echo "${cpp_use_gpu_key} ${use_gpu}" >> cpp_config.txt
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echo "${cpp_cpu_threads_key} ${threads}" >> cpp_config.txt
|
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echo "${cpp_use_mkldnn_key} ${use_mkldnn}" >> cpp_config.txt
|
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echo "${cpp_use_tensorrt_key} 0" >> cpp_config.txt
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echo "${cpp_use_fp16_key} 0" >> cpp_config.txt
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command="${_script} cpp_config.txt ${_img_dir} > ${_save_log_path} 2>&1 "
|
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eval $command
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last_status=${PIPESTATUS[0]}
|
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eval "cat ${_save_log_path}"
|
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status_check $last_status "${command}" "${status_log}"
|
||||
done
|
||||
done
|
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elif [ ${use_gpu} = "1" ] || [ ${use_gpu} = "gpu" ]; then
|
||||
for use_trt in ${cpp_use_tensorrt_list[*]}; do
|
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for precision in ${cpp_use_fp16_list[*]}; do
|
||||
if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
|
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continue
|
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fi
|
||||
if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then
|
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continue
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||||
fi
|
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_save_log_path="${_log_path}/cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
|
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cp ../tests/config/cpp_config.txt cpp_config.txt
|
||||
echo "${cpp_use_gpu_key} ${use_gpu}" >> cpp_config.txt
|
||||
echo "${cpp_cpu_threads_key} ${threads}" >> cpp_config.txt
|
||||
echo "${cpp_use_mkldnn_key} ${use_mkldnn}" >> cpp_config.txt
|
||||
echo "${cpp_use_tensorrt_key} ${use_trt}" >> cpp_config.txt
|
||||
echo "${cpp_use_fp16_key} ${precision}" >> cpp_config.txt
|
||||
command="${_script} cpp_config.txt ${_img_dir} > ${_save_log_path} 2>&1 "
|
||||
eval $command
|
||||
last_status=${PIPESTATUS[0]}
|
||||
eval "cat ${_save_log_path}"
|
||||
status_check $last_status "${command}" "${status_log}"
|
||||
|
||||
done
|
||||
done
|
||||
else
|
||||
echo "Does not support hardware other than CPU and GPU Currently!"
|
||||
fi
|
||||
done
|
||||
}
|
||||
|
||||
function func_inference(){
|
||||
IFS='|'
|
||||
|
|
@ -247,6 +317,10 @@ if [ ${MODE} = "infer" ]; then
|
|||
Count=$(($Count + 1))
|
||||
done
|
||||
cd ..
|
||||
elif [ ${MODE} = "cpp_infer" ]; then
|
||||
cd deploy
|
||||
func_cpp_inference "./cpp/build/clas_system" "../${LOG_PATH}" "${infer_img_dir}"
|
||||
cd ..
|
||||
|
||||
else
|
||||
IFS="|"
|
||||
|
|
|
|||
Loading…
Reference in New Issue