#include "../nodes/vp_file_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/ba/vp_ba_wrong_direction_node.h"
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#include "../nodes/ba/vp_ba_person_gathering_node.h"
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#include "../nodes/ba/vp_ba_person_falldown_node.h"
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#include "../nodes/ba/vp_ba_report_detect_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 video_path = "./vp_data/test_video/all_in_one.mp4";
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float resize_ratio = 0.5;
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// 如果提供了第一个和第二个参数，则覆盖默认的路径
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if (args.size() >= 1) {
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video_path = args[0];
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if (args.size() >= 2){
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resize_ratio = std::stof(args[1]);
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}
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} else {
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std::cout << "Usage: " << argv[0] << " <video_path> [resize_ratio]\n";
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std::cout << "Example: " << argv[0] << " ./vp_data/test_video/all_in_one.mp4 0.5\n";
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return -1;
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}
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// create nodes bool cycle = true, std::string gst_decoder_name = "avdec_h264", int skip_interval = 0
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auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, video_path, resize_ratio, true, "avdec_h264",3);
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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) (224,74),(346,64),(486,342),(9,342) vp_point(450, 100), vp_objects::vp_point(792, 80), vp_objects::vp_point(1100, 684), vp_objects::vp_point(18, 682)
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std::map<int, std::vector<vp_objects::vp_point>> regions = {
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{0, std::vector<vp_objects::vp_point>{vp_objects::vp_point(int(616*resize_ratio), int(13*resize_ratio)),
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vp_objects::vp_point(int(670*resize_ratio), int(11*resize_ratio)),
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vp_objects::vp_point(int(1100*resize_ratio), int(684*resize_ratio)),
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vp_objects::vp_point(int(18*resize_ratio), int(610*resize_ratio))}}, // channel0 -> 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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// define a line in frame for every channel (value MUST in the scope of frame'size)
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vp_objects::vp_point left_start(10, 10); // change to proper value
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vp_objects::vp_point left_end(10, 20); // change to proper value
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vp_objects::vp_point right_start(10, 20); // change to proper value
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vp_objects::vp_point right_end(10, 10); // change to proper value
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std::map<int, std::vector<vp_objects::vp_point>> left_lines = {{0, {left_start, left_end}}}; // channel0 -> point vector
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std::map<int, std::vector<vp_objects::vp_point>> right_lines = {{0, {right_start, right_end}}}; // channel0 -> point vector
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int half_screen_width = 640;
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auto ba_wrong_direction = std::make_shared<vp_nodes::vp_ba_wrong_direction_node>("vp_ba_wrong_direction_node", left_lines,right_lines,half_screen_width,true,true);
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int min_gathering_count = 2;
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auto ba_person_gathering = std::make_shared<vp_nodes::vp_ba_person_gathering_node>("vp_ba_person_gathering_node", min_gathering_count,true,true);
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auto ba_person_falldown = std::make_shared<vp_nodes::vp_ba_person_falldown_node>("vp_ba_person_falldown_node", true,true);
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auto firesmoke_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("firesmoke_detector", "./vp_data/models/det_cls/firesmoke_yolov5s.onnx", "", "./vp_data/models/det_cls/firesmoke_3classes.txt", 640, 384,1,1000,0.8,0.8);
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auto ba_report_detect = std::make_shared<vp_nodes::vp_ba_report_detect_node>("ba_report_detect_node","fire_smoke",std::vector<int>{1000,1001,1002}, true,true);
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auto json_kafka_broker_0 = std::make_shared<vp_nodes::vp_json_kafka_broker_node>("json_kafka_broker_0", "172.18.0.247:9092", "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");
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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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ba_wrong_direction->attach_to({ba_stop});
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ba_person_gathering->attach_to({ba_wrong_direction});
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ba_person_falldown->attach_to({ba_person_gathering});
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firesmoke_detector->attach_to({ba_person_falldown});
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ba_report_detect->attach_to({firesmoke_detector});
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json_kafka_broker_0->attach_to({ba_report_detect});
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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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screen_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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