// 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 #include #include #include // NOLINT #include #include #include #include #include #include "include/paddlex/paddlex.h" #include "include/paddlex/visualize.h" #if defined(__arm__) || defined(__aarch64__) #include #endif using namespace std::chrono; // NOLINT 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_bool(use_camera, false, "Infering with Camera"); DEFINE_int32(camera_id, 0, "Camera id"); DEFINE_string(video_path, "", "Path of input video"); DEFINE_bool(show_result, false, "show the result of each frame with a window"); DEFINE_bool(save_result, true, "save the result of each frame to a video"); DEFINE_string(key, "", "key of encryption"); DEFINE_string(save_dir, "output", "Path to save visualized image"); DEFINE_double(threshold, 0.5, "The minimum scores of target boxes which are shown"); 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_video_path == "" & FLAGS_use_camera == false) { std::cerr << "--video_path or --use_camera 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, FLAGS_key); // 打开视频流 cv::VideoCapture capture; if (FLAGS_use_camera) { capture.open(FLAGS_camera_id); if (!capture.isOpened()) { std::cout << "Can not open the camera " << FLAGS_camera_id << "." << std::endl; return -1; } } else { capture.open(FLAGS_video_path); if (!capture.isOpened()) { std::cout << "Can not open the video " << FLAGS_video_path << "." << std::endl; return -1; } } // 创建VideoWriter cv::VideoWriter video_out; std::string video_out_path; if (FLAGS_save_result) { // 获取视频流信息: 分辨率, 帧率 int video_width = static_cast(capture.get(CV_CAP_PROP_FRAME_WIDTH)); int video_height = static_cast(capture.get(CV_CAP_PROP_FRAME_HEIGHT)); int video_fps = static_cast(capture.get(CV_CAP_PROP_FPS)); int video_fourcc; if (FLAGS_use_camera) { video_fourcc = 828601953; } else { video_fourcc = static_cast(capture.get(CV_CAP_PROP_FOURCC)); } if (FLAGS_use_camera) { time_t now = time(0); video_out_path = PaddleX::generate_save_path(FLAGS_save_dir, std::to_string(now) + ".mp4"); } else { video_out_path = PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_video_path); } video_out.open(video_out_path.c_str(), video_fourcc, video_fps, cv::Size(video_width, video_height), true); if (!video_out.isOpened()) { std::cout << "Create video writer failed!" << std::endl; return -1; } } PaddleX::DetResult result; cv::Mat frame; int key; while (capture.read(frame)) { if (FLAGS_show_result || FLAGS_use_camera) { key = cv::waitKey(1); // 按下ESC退出整个程序,保存视频文件到磁盘 if (key == 27) { break; } } else if (frame.empty()) { break; } model.predict(frame, &result); // 可视化 cv::Mat vis_img = PaddleX::Visualize(frame, result, model.labels, FLAGS_threshold); if (FLAGS_show_result || FLAGS_use_camera) { cv::imshow("human_seg", vis_img); } if (FLAGS_save_result) { video_out.write(vis_img); } result.clear(); } capture.release(); if (FLAGS_save_result) { std::cout << "Visualized output saved as " << video_out_path << std::endl; video_out.release(); } if (FLAGS_show_result || FLAGS_use_camera) { cv::destroyAllWindows(); } return 0; }