#include "../nodes/vp_file_src_node.h"
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#include "../nodes/vp_rtsp_src_node.h"
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#include "../nodes/vp_rtsp_ffmpeg_src_node.h"
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#include "../nodes/vp_split_node.h"
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#include "../nodes/infers/vp_trt_vehicle_detector.h"
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#include "../nodes/infers/vp_trt_vehicle_plate_detector.h"
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#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
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#include "../nodes/infers/vp_yolo_detector_node.h"
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#include "../nodes/osd/vp_osd_node.h"
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#include "../nodes/vp_sync_node.h"
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#include "../nodes/track/vp_sort_track_node.h"
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#include "../nodes/ba/vp_ba_jam_node.h"
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#include "../nodes/ba/vp_ba_stop_node.h"
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#include "../nodes/osd/vp_ba_stop_osd_node.h"
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#include "../nodes/broker/vp_json_kafka_broker_node.h"
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#include "../nodes/record/vp_record_node.h"
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#include "../nodes/vp_screen_des_node.h"
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#include "../nodes/vp_fake_des_node.h"
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#include "../nodes/vp_placeholder_node.h"
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#include "../utils/analysis_board/vp_analysis_board.h"
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/*
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* ## firesmoke_detect_sample ##
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* detect firesmoke using yolo.
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*/
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int main(int argc, char* argv[]) {
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VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
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VP_LOGGER_INIT();
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std::vector<std::string> args(argv + 1, argv + argc);
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// 默认的命令行参数
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std::string rtsp_path = "rtsp://127.0.0.1:8554/demo";
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std::string kafka_server_point = "127.0.0.1:9092";
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float resize_ratio = 0.4;
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int skip_interval = 3;
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int channel_index = 21;
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bool usegpu = false; // 新增参数，默认值为 false
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// 如果提供了至少 6 个参数，则覆盖默认值
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if (args.size() >= 6) {
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rtsp_path = args[0];
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resize_ratio = std::stof(args[1]);
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kafka_server_point = args[2];
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skip_interval = std::stoi(args[3]);
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channel_index = std::stoi(args[4]);
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std::string usegpu_arg = args[5];
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// 将字符串转换为布尔值，支持 true/false 或 1/0
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std::transform(usegpu_arg.begin(), usegpu_arg.end(), usegpu_arg.begin(), ::tolower);
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if (usegpu_arg == "true" || usegpu_arg == "1") {
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usegpu = true;
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} else if (usegpu_arg == "false" || usegpu_arg == "0") {
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usegpu = false;
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} else {
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std::cerr << "Invalid value for <usegpu>. Please use 'true', 'false', '1', or '0'.\n";
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return -1;
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}
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} else {
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std::cout << "Usage: " << argv[0] << " <rtsp_path> <resize_ratio> <kafka_server_point> <skip_interval> <channel_index> <usegpu>\n";
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std::cout << "Example: " << argv[0] << " rtsp://127.0.0.1:8554/demo 0.4 127.0.0.1:9092 5 21 true\n";
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return -1;
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}
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// create nodes
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//auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, rtsp_path, resize_ratio);
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//auto file_src_0 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_1", 0, rtsp_path, resize_ratio, "avdec_h264", skip_interval);
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auto file_src_0 = std::make_shared<vp_nodes::vp_rtsp_ffmpeg_src_node>("rtsp_src_1", channel_index, rtsp_path, resize_ratio, skip_interval, usegpu);
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//auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/falldown.mp4", 0.5);
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//auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true); // split by deep-copy not by channel!
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//branch 0
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//auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_detection.trt");
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auto vehicle_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("vehicle_detector", "./vp_data/models/det_cls/yolov3-tiny-2022-0721_best.weights", "./vp_data/models/det_cls/yolov3-tiny-2022-0721.cfg", "./vp_data/models/det_cls/yolov3_tiny_5classes.txt");
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auto trt_vehicle_plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector>("vehicle_plate_detector", "./vp_data/models/trt/plate/vehicle_plate_box_detection.trt", "./vp_data/models/trt/plate/vehicle_plate_text_recognition.trt");
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auto trt_vehicle_color_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("color_cls", "./vp_data/models/trt/vehicle/vehicle_color_detection.trt", std::vector<int>{0, 1, 2});
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auto tracker = std::make_shared<vp_nodes::vp_sort_track_node>("sort_tracker");
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// define a region in frame for every channel (value MUST in the scope of frame'size)
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std::map<int, std::vector<vp_objects::vp_point>> regions = {
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{channel_index, std::vector<vp_objects::vp_point>{vp_objects::vp_point(280, 30), vp_objects::vp_point(340, 30), vp_objects::vp_point(600, 330), vp_objects::vp_point(30, 350)}}, // channel0 -> region
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{1, std::vector<vp_objects::vp_point>{vp_objects::vp_point(280, 30), vp_objects::vp_point(340, 30), vp_objects::vp_point(600, 330), vp_objects::vp_point(30, 350)}} // channel1 -> region
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};
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auto ba_jam = std::make_shared<vp_nodes::vp_ba_jam_node>("ba_jam", regions);
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auto ba_stop = std::make_shared<vp_nodes::vp_ba_stop_node>("ba_stop", regions);
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auto json_kafka_broker_0 = std::make_shared<vp_nodes::vp_json_kafka_broker_node>("json_kafka_broker_0", kafka_server_point, "vp_ba_result", vp_nodes::vp_broke_for::BARESULT);
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auto osd_0 = std::make_shared<vp_nodes::vp_ba_stop_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
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auto recorder = std::make_shared<vp_nodes::vp_record_node>("recorder", "./record", "./record");
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// for testing. USING fake_des node in production
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auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
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auto fake_des_0 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_0", 0);
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// construct pipeline
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vehicle_detector->attach_to({file_src_0});
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trt_vehicle_plate_detector->attach_to({vehicle_detector});
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trt_vehicle_color_classifier->attach_to({trt_vehicle_plate_detector});
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tracker->attach_to({trt_vehicle_color_classifier});
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ba_jam->attach_to({tracker});
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ba_stop->attach_to({ba_jam});
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json_kafka_broker_0->attach_to({ba_stop});
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osd_0->attach_to({json_kafka_broker_0});
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recorder->attach_to({osd_0});
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fake_des_0->attach_to({recorder});
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file_src_0->start();
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// for debug purpose
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// vp_utils::vp_analysis_board board({file_src_0});
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// board.display(1, false);
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std::string wait;
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std::getline(std::cin, wait);
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file_src_0->detach_recursively();
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}
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