// Copyright (c) 2021 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 "model_deploy/paddlex/include/x_preprocess.h" namespace PaddleDeploy { bool XPreprocess::Init(const YAML::Node& yaml_config) { model_type_ = yaml_config["model_type"].as(); model_name_ = yaml_config["model_name"].as(); if (model_type_ == "segmenter") { return seg_preprocess.Init(yaml_config); } else if (model_type_ == "classifier") { return clas_preprocess.Init(yaml_config); } else if (model_type_ == "detector") { return det_preprocess.Init(yaml_config); } else { std::cerr << "[ERROR] Unexpected model_type: '" << model_type_ << "' in preprocess Init" << std::endl; return false; } return true; } bool XPreprocess::Run(std::vector* imgs, std::vector* inputs, std::vector* shape_infos, int thread_num) { if (model_type_ == "segmenter") { return seg_preprocess.Run(imgs, inputs, shape_infos, thread_num); } else if (model_type_ == "classifier") { return clas_preprocess.Run(imgs, inputs, shape_infos, thread_num); } else if (model_type_ == "detector") { return det_preprocess.Run(imgs, inputs, shape_infos, thread_num); } else { std::cerr << "[ERROR] Unexpected model_type: '" << model_type_ << "' in preprocess" << std::endl; return false; } return true; } } // namespace PaddleDeploy