text: //   Copyright (c) 2020 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 <glog/logging.h>
  
  #include <fstream>
  #include <iostream>
  #include <string>
  #include <vector>
  
  #include "include/paddlex/paddlex.h"
  #include "include/paddlex/visualize.h"
  
  DEFINE_string(model_dir, "", "Path of inference model");
  DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
  DEFINE_bool(use_trt, false, "Infering with TensorRT");
  DEFINE_int32(gpu_id, 0, "GPU card id");
  DEFINE_string(image, "", "Path of test image file");
  DEFINE_string(image_list, "", "Path of test image list file");
  DEFINE_string(save_dir, "output", "Path to save visualized image");
  
  int main(int argc, char** argv) {
    // 解析命令行参数
    google::ParseCommandLineFlags(&argc, &argv, true);
  
    if (FLAGS_model_dir == "") {
      std::cerr << "--model_dir need to be defined" << std::endl;
      return -1;
    }
    if (FLAGS_image == "" & FLAGS_image_list == "") {
      std::cerr << "--image or --image_list need to be defined" << std::endl;
      return -1;
    }
  
    // 加载模型
    PaddleX::Model model;
    model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id);
  
    auto colormap = PaddleX::GenerateColorMap(model.labels.size());
    // 进行预测
    if (FLAGS_image_list != "") {
      std::ifstream inf(FLAGS_image_list);
      if (!inf) {
        std::cerr << "Fail to open file " << FLAGS_image_list << std::endl;
        return -1;
      }
      std::string image_path;
      while (getline(inf, image_path)) {
        PaddleX::SegResult result;
        cv::Mat im = cv::imread(image_path, 1);
        model.predict(im, &result);
        // 可视化
        cv::Mat vis_img =
            PaddleX::VisualizeSeg(im, result, model.labels, colormap);
        std::string save_path =
            PaddleX::generate_save_path(FLAGS_save_dir, image_path);
        cv::imwrite(save_path, vis_img);
        result.clear();
        std::cout << "Visualized output saved as " << save_path << std::endl;
      }
    } else {
      PaddleX::SegResult result;
      cv::Mat im = cv::imread(FLAGS_image, 1);
      model.predict(im, &result);
      // 可视化
      cv::Mat vis_img = PaddleX::VisualizeSeg(im, result, model.labels, colormap);
      std::string save_path =
          PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
      cv::imwrite(save_path, vis_img);
      result.clear();
      std::cout << "Visualized output saved as " << save_path << std::endl;
    }
  
    return 0;
  }
  