add sample

wangrong

2025-01-23 02819b5c047bb354b0ef2374e7c6a6ac4bbd5bba

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#include "../nodes/vp_file_src_node.h" 
#include "../nodes/vp_split_node.h" 
#include "../nodes/infers/vp_trt_vehicle_detector.h" 
#include "../nodes/infers/vp_trt_vehicle_plate_detector.h" 
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h" 
#include "../nodes/infers/vp_yolo_detector_node.h" 
 
#include "../nodes/osd/vp_osd_node.h" 
#include "../nodes/vp_sync_node.h" 
#include "../nodes/track/vp_sort_track_node.h" 
#include "../nodes/ba/vp_ba_jam_node.h" 
#include "../nodes/ba/vp_ba_stop_node.h" 
#include "../nodes/ba/vp_ba_wrong_direction_node.h" 
#include "../nodes/ba/vp_ba_person_gathering_node.h" 
#include "../nodes/ba/vp_ba_person_falldown_node.h" 
#include "../nodes/ba/vp_ba_report_detect_node.h" 
 
#include "../nodes/osd/vp_ba_stop_osd_node.h" 
#include "../nodes/broker/vp_json_kafka_broker_node.h" 
#include "../nodes/record/vp_record_node.h" 
#include "../nodes/vp_screen_des_node.h" 
#include "../nodes/vp_fake_des_node.h" 
#include "../nodes/vp_placeholder_node.h" 
 
#include "../utils/analysis_board/vp_analysis_board.h" 
 
/* 
* ## firesmoke_detect_sample ## 
* detect firesmoke using yolo. 
*/ 
 
int main(int argc, char* argv[]) { 
    VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO); 
    VP_LOGGER_INIT(); 
 
    std::vector<std::string> args(argv + 1, argv + argc); 
    // 默认的命令行参数 
    std::string video_path = "./vp_data/test_video/all_in_one.mp4"; 
 
    float resize_ratio = 0.5; 
 
    // 如果提供了第一个和第二个参数，则覆盖默认的路径 
    if (args.size() >= 1) { 
        video_path = args[0]; 
        if (args.size() >= 2){ 
            resize_ratio = std::stof(args[1]); 
        } 
    } else { 
        std::cout << "Usage: " << argv[0] << " <video_path> [resize_ratio]\n"; 
        std::cout << "Example: " << argv[0] << " ./vp_data/test_video/all_in_one.mp4 0.5\n"; 
        return -1; 
    } 
 
    // create nodes 
    auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, video_path, resize_ratio); 
    //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); 
    //auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true);  // split by deep-copy not by channel! 
     
    //branch 0 
    //auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_detection.trt"); 
    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"); 
    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"); 
    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}); 
     
    auto tracker = std::make_shared<vp_nodes::vp_sort_track_node>("sort_tracker"); 
     
    // define a region in frame for every channel (value MUST in the scope of frame'size) 
    std::map<int, std::vector<vp_objects::vp_point>> regions = { 
        {0, std::vector<vp_objects::vp_point>{vp_objects::vp_point(20, 30), vp_objects::vp_point(600, 40), vp_objects::vp_point(600, 300), vp_objects::vp_point(10, 300)}},  // channel0 -> region 
        {1, std::vector<vp_objects::vp_point>{vp_objects::vp_point(20, 30), vp_objects::vp_point(1000, 40), vp_objects::vp_point(1000, 600), vp_objects::vp_point(10, 600)}}   // channel1 -> region 
    }; 
    auto ba_jam = std::make_shared<vp_nodes::vp_ba_jam_node>("ba_jam", regions); 
    auto ba_stop = std::make_shared<vp_nodes::vp_ba_stop_node>("ba_stop", regions); 
     
    // define a line in frame for every channel (value MUST in the scope of frame'size) 
    vp_objects::vp_point left_start(10, 10);  // change to proper value 
    vp_objects::vp_point left_end(10, 20);  // change to proper value 
    vp_objects::vp_point right_start(10, 20);  // change to proper value 
    vp_objects::vp_point right_end(10, 10);  // change to proper value 
    std::map<int, std::vector<vp_objects::vp_point>> left_lines = {{0, {left_start, left_end}}};  // channel0 -> point vector 
    std::map<int, std::vector<vp_objects::vp_point>> right_lines = {{0, {right_start, right_end}}};  // channel0 -> point vector 
    int half_screen_width = 384; 
    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); 
        
    int min_gathering_count = 2; 
    auto ba_person_gathering = std::make_shared<vp_nodes::vp_ba_person_gathering_node>("vp_ba_person_gathering_node", min_gathering_count,true,true); 
    auto ba_person_falldown = std::make_shared<vp_nodes::vp_ba_person_falldown_node>("vp_ba_person_falldown_node", true,true); 
   
    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); 
    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); 
 
 
    auto json_kafka_broker_0 = std::make_shared<vp_nodes::vp_json_kafka_broker_node>("json_kafka_broker_0", "192.168.0.85:9092", "vp_ba_vehicle", vp_nodes::vp_broke_for::BARESULT); 
    auto osd_0 = std::make_shared<vp_nodes::vp_ba_stop_osd_node>("osd_0"); 
    auto recorder = std::make_shared<vp_nodes::vp_record_node>("recorder", "./record", "./record"); 
     
    // for testing. USING fake_des node in production  
    auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);     
    auto fake_des_0 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_0", 0); 
 
    // construct pipeline 
    vehicle_detector->attach_to({file_src_0}); 
    trt_vehicle_plate_detector->attach_to({vehicle_detector}); 
    trt_vehicle_color_classifier->attach_to({trt_vehicle_plate_detector}); 
    tracker->attach_to({trt_vehicle_color_classifier}); 
    ba_jam->attach_to({tracker}); 
    ba_stop->attach_to({ba_jam}); 
    ba_wrong_direction->attach_to({ba_stop}); 
    ba_person_gathering->attach_to({ba_wrong_direction}); 
    ba_person_falldown->attach_to({ba_person_gathering}); 
    firesmoke_detector->attach_to({ba_person_falldown}); 
    ba_report_detect->attach_to({firesmoke_detector}); 
    json_kafka_broker_0->attach_to({ba_report_detect}); 
    osd_0->attach_to({json_kafka_broker_0}); 
 
    recorder->attach_to({osd_0}); 
    screen_des_0->attach_to({recorder}); 
 
    file_src_0->start(); 
 
    // for debug purpose 
    vp_utils::vp_analysis_board board({file_src_0}); 
    board.display(1, false); 
 
    std::string wait; 
    std::getline(std::cin, wait); 
    file_src_0->detach_recursively(); 
    
}