// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "fastdeploy/vision.h" #ifdef WIN32 const char sep = '\\'; #else const char sep = '/'; #endif void InitAndInfer(const std::string& model_dir, const std::string& image_file, const fastdeploy::RuntimeOption& option) { auto model_file = model_dir + sep + "model.pdmodel"; auto params_file = model_dir + sep + "model.pdiparams"; auto model = fastdeploy::vision::detection::YOLOv6( model_file, params_file, option, fastdeploy::ModelFormat::PADDLE); assert(model.Initialized()); auto im = cv::imread(image_file); fastdeploy::vision::DetectionResult res; if (!model.Predict(&im, &res)) { std::cerr << "Failed to predict." << std::endl; return; } std::cout << res.Str() << std::endl; auto vis_im = fastdeploy::vision::VisDetection(im, res); cv::imwrite("vis_result.jpg", vis_im); std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl; } int main(int argc, char* argv[]) { if (argc < 4) { std::cout << "Usage: infer_demo path/to/quant_model " "path/to/image " "run_option, " "e.g ./infer_demo ./yolov6s_quant ./000000014439.jpg 0" << std::endl; std::cout << "The data type of run_option is int, 0: run on cpu with ORT " "backend; 1: run " "on cpu with Paddle backend ; 2: run with gpu and use " "TensorRT backend." << std::endl; return -1; } fastdeploy::RuntimeOption option; int flag = std::atoi(argv[3]); if (flag == 0) { option.UseCpu(); option.UseOrtBackend(); } else if (flag == 1) { option.UseGpu(); option.UseTrtBackend(); } else if (flag == 2) { option.UseGpu(); option.UseTrtBackend(); option.EnablePaddleToTrt(); } std::string model_dir = argv[1]; std::string test_image = argv[2]; InitAndInfer(model_dir, test_image, option); return 0; }