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陈赣
2026-06-03 12:43:14 +08:00
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42
samples/1-1-1_sample.cpp Normal file
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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-1-1 sample ##
* 1 video input, 1 infer task, and 1 output.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
screen_des_0->attach_to({osd_0});
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();
}

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samples/1-1-N_sample.cpp Normal file
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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-1-N sample ##
* 1 video input, 1 infer task, and 2 outputs.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.8);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000");
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
// auto split
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
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();
}

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samples/1-N-1_sample.cpp Normal file
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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_type_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_feature_encoder.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/vp_sync_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-N-1_sample_sample ##
* 1 input video, detect vehicles first，classify by colors and types in parallel, then sync data and output on screen.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes for 1-N-1 pipeline
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.6);
auto trt_vehicle_detector_0 = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_detector_0", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true); // split by deep-copy not by channel!
auto trt_vehicle_color_classifier_0 = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("trt_color_cls_0", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto trt_vehicle_type_classifier_0 = std::make_shared<vp_nodes::vp_trt_vehicle_type_classifier>("trt_type_cls_0", "./vp_data/models/trt/vehicle/vehicle_type_v8.5.trt", std::vector<int>{0, 1, 2});
auto sync = std::make_shared<vp_nodes::vp_sync_node>("sync", vp_nodes::vp_sync_mode::UPDATE, 160);
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct 1-N-1 pipeline
trt_vehicle_detector_0->attach_to({file_src_0});
split->attach_to({trt_vehicle_detector_0});
trt_vehicle_color_classifier_0->attach_to({split});
trt_vehicle_type_classifier_0->attach_to({split});
sync->attach_to({trt_vehicle_color_classifier_0, trt_vehicle_type_classifier_0});
osd_0->attach_to({sync});
screen_des_0->attach_to({osd_0});
/*
the format of pipeline:
/ trt_vehicle_color_classifier_0 \
file_src_0 -> trt_vehicle_detector_0 -> split -> -> sync -> osd_0 -> screen_des_0
\ trt_vehicle_type_classifier_0 /
*/
// start 1-N-1 pipeline
file_src_0->start();
// visualize pipelines for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_type_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_feature_encoder.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/vp_sync_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-N-1_sample_sample ##
* 1 input video, detect vehicles first，classify by colors and tracking vehicles in parallel, then sync data and output on screen.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::DEBUG);
VP_SET_LOG_KEYWORDS_FOR_DEBUG({"sync"}); // only write debug log for sync node
VP_LOGGER_INIT();
// create nodes for 1-N-1 pipeline
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/jam2.mp4");
auto trt_vehicle_detector_0 = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_detector_0", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true); // split by deep-copy not by channel!
auto trt_vehicle_color_classifier_0 = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("trt_color_cls_0", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto track_0 = std::make_shared<vp_nodes::vp_sort_track_node>("track_0");
auto sync = std::make_shared<vp_nodes::vp_sync_node>("sync", vp_nodes::vp_sync_mode::UPDATE, 160);
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct 1-N-1 pipeline
trt_vehicle_detector_0->attach_to({file_src_0});
split->attach_to({trt_vehicle_detector_0});
trt_vehicle_color_classifier_0->attach_to({split});
track_0->attach_to({split});
sync->attach_to({trt_vehicle_color_classifier_0, track_0});
osd_0->attach_to({sync});
screen_des_0->attach_to({osd_0});
/*
the format of pipeline:
/ trt_vehicle_color_classifier_0 \
file_src_0 -> trt_vehicle_detector_0 -> split -> -> sync -> osd_0 -> screen_des_0
\ track_0 /
*/
// start 1-N-1 pipeline
file_src_0->start();
// visualize pipelines for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_plate_detector_v2.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/vp_sync_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-N-1_sample_sample ##
* 1 input video, detect vehicles + classify by colors, detect license plate + track by sort, 2 tasks in parallel，then sync data and output on screen.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::DEBUG);
VP_SET_LOG_KEYWORDS_FOR_DEBUG({"sync"}); // only write debug log for sync node
VP_LOGGER_INIT();
// create nodes for 1-N-1 pipeline
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/plate2.mp4");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true); // split by deep-copy not by channel!
auto vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto vehicle_color_cls = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("vehicle_color_cls", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector_v2>("plate_detector", "./vp_data/models/trt/plate/det_v8.5.trt", "./vp_data/models/trt/plate/rec_v8.5.trt");
auto plate_tracker = std::make_shared<vp_nodes::vp_sort_track_node>("plate_tracker");
auto sync = std::make_shared<vp_nodes::vp_sync_node>("sync");
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct 1-N-1 pipeline
split->attach_to({file_src_0});
vehicle_detector->attach_to({split});
plate_detector->attach_to({split});
vehicle_color_cls->attach_to({vehicle_detector});
plate_tracker->attach_to({plate_detector});
sync->attach_to({vehicle_color_cls, plate_tracker});
osd->attach_to({sync});
screen_des_0->attach_to({osd});
/*
the format of pipeline:
/ vehicle_detector -> vehicle_color_cls \
file_src_0 -> split -> -> sync -> osd -> screen_des_0
\ plate_detector -> plate_tracker /
*/
// start 1-N-1 pipeline
file_src_0->start();
// visualize pipelines for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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samples/1-N-N_sample.cpp Normal file
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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_split_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## 1-N-N sample ##
* 1 video input and then split into 2 branches for different infer tasks, then 2 total outputs(no need to sync in such situations).
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto split = std::make_shared<vp_nodes::vp_split_node>("split", false, true); // split by deep-copy not by channel!
// branch a
auto yunet_face_detector_a = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_a", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_a = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_a", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_a = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_a");
auto screen_des_a = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_a", 0);
// branch b
auto yunet_face_detector_b = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_b", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_b = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_b", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_b = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_b");
auto screen_des_b = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_b", 0);
// construct pipeline
split->attach_to({file_src_0});
// branch a
yunet_face_detector_a->attach_to({split});
sface_face_encoder_a->attach_to({yunet_face_detector_a});
osd_a->attach_to({sface_face_encoder_a});
screen_des_a->attach_to({osd_a});
// branch b
yunet_face_detector_b->attach_to({split});
sface_face_encoder_b->attach_to({yunet_face_detector_b});
osd_b->attach_to({sface_face_encoder_b});
screen_des_b->attach_to({osd_b});
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();
}

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# can ONLY be called by parent CMakeLists.txt, because no environment settings for this script.#
if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
message(FATAL_ERROR "can ONLY be called by parent CMakeLists.txt.")
endif()
message("start build for simple samples...")
# save all exe to 'build/bin'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
add_executable(1-1-1_sample "1-1-1_sample.cpp")
target_link_libraries(1-1-1_sample ${PROJECT_NAME})
add_executable(1-1-N_sample "1-1-N_sample.cpp")
target_link_libraries(1-1-N_sample ${PROJECT_NAME})
add_executable(1-N-N_sample "1-N-N_sample.cpp")
target_link_libraries(1-N-N_sample ${PROJECT_NAME})
add_executable(ba_crossline_sample "ba_crossline_sample.cpp")
target_link_libraries(ba_crossline_sample ${PROJECT_NAME})
add_executable(enet_seg_sample "enet_seg_sample.cpp")
target_link_libraries(enet_seg_sample ${PROJECT_NAME})
add_executable(face_tracking_sample "face_tracking_sample.cpp")
target_link_libraries(face_tracking_sample ${PROJECT_NAME})
add_executable(image_des_sample "image_des_sample.cpp")
target_link_libraries(image_des_sample ${PROJECT_NAME})
add_executable(image_src_sample "image_src_sample.cpp")
target_link_libraries(image_src_sample ${PROJECT_NAME})
add_executable(interaction_with_pipe_sample "interaction_with_pipe_sample.cpp")
target_link_libraries(interaction_with_pipe_sample ${PROJECT_NAME})
add_executable(mask_rcnn_sample "mask_rcnn_sample.cpp")
target_link_libraries(mask_rcnn_sample ${PROJECT_NAME})
add_executable(message_broker_sample "message_broker_sample.cpp")
target_link_libraries(message_broker_sample ${PROJECT_NAME})
add_executable(multi_detectors_and_classifiers_sample "multi_detectors_and_classifiers_sample.cpp")
target_link_libraries(multi_detectors_and_classifiers_sample ${PROJECT_NAME})
add_executable(N-1-N_sample "N-1-N_sample.cpp")
target_link_libraries(N-1-N_sample ${PROJECT_NAME})
add_executable(N-N_sample "N-N_sample.cpp")
target_link_libraries(N-N_sample ${PROJECT_NAME})
add_executable(openpose_sample "openpose_sample.cpp")
target_link_libraries(openpose_sample ${PROJECT_NAME})
add_executable(record_sample "record_sample.cpp")
target_link_libraries(record_sample ${PROJECT_NAME})
add_executable(rtsp_des_sample "rtsp_des_sample.cpp")
target_link_libraries(rtsp_des_sample ${PROJECT_NAME})
add_executable(rtsp_src_sample "rtsp_src_sample.cpp")
target_link_libraries(rtsp_src_sample ${PROJECT_NAME})
add_executable(vp_logger_sample "vp_logger_sample.cpp")
target_link_libraries(vp_logger_sample ${PROJECT_NAME})
add_executable(skip_sample "skip_sample.cpp")
target_link_libraries(skip_sample ${PROJECT_NAME})
add_executable(obstacle_detect_sample "obstacle_detect_sample.cpp")
target_link_libraries(obstacle_detect_sample ${PROJECT_NAME})
add_executable(multi_detectors_sample "multi_detectors_sample.cpp")
target_link_libraries(multi_detectors_sample ${PROJECT_NAME})
add_executable(firesmoke_detect_sample "firesmoke_detect_sample.cpp")
target_link_libraries(firesmoke_detect_sample ${PROJECT_NAME})
add_executable(face_swap_sample "face_swap_sample.cpp")
target_link_libraries(face_swap_sample ${PROJECT_NAME})
add_executable(video_restoration_sample "video_restoration_sample.cpp")
target_link_libraries(video_restoration_sample ${PROJECT_NAME})
add_executable(app_des_sample "app_des_sample.cpp")
target_link_libraries(app_des_sample ${PROJECT_NAME})
add_executable(app_src_des_sample "app_src_des_sample.cpp")
target_link_libraries(app_src_des_sample ${PROJECT_NAME})
add_executable(lane_detect_sample "lane_detect_sample.cpp")
target_link_libraries(lane_detect_sample ${PROJECT_NAME})
add_executable(frame_fusion_sample "frame_fusion_sample.cpp")
target_link_libraries(frame_fusion_sample ${PROJECT_NAME})
add_executable(yolov5_seg_sample "yolov5_seg_sample.cpp")
target_link_libraries(yolov5_seg_sample ${PROJECT_NAME})
add_executable(vp_test "vp_test.cpp")
target_link_libraries(vp_test ${PROJECT_NAME})
# samples depend on Kafka
if(VP_WITH_KAFKA)
add_executable(message_broker_kafka_sample "message_broker_kafka_sample.cpp")
target_link_libraries(message_broker_kafka_sample ${PROJECT_NAME})
endif()
# samples depend on LLM
if(VP_WITH_LLM)
add_executable(mllm_analyse_sample "mllm_analyse_sample.cpp")
target_link_libraries(mllm_analyse_sample ${PROJECT_NAME})
add_executable(mllm_analyse_sample_openai "mllm_analyse_sample_openai.cpp")
target_link_libraries(mllm_analyse_sample_openai ${PROJECT_NAME})
endif()
# samples depend on FFmpeg
if(VP_WITH_FFMPEG)
add_executable(ffmpeg_src_des_sample "ffmpeg_src_des_sample.cpp")
target_link_libraries(ffmpeg_src_des_sample ${PROJECT_NAME})
add_executable(ffmpeg_transcode_sample "ffmpeg_transcode_sample.cpp")
target_link_libraries(ffmpeg_transcode_sample ${PROJECT_NAME})
endif()
# samples depend on PaddlePaddle
if(VP_WITH_PADDLE)
add_executable(app_src_sample "app_src_sample.cpp")
target_link_libraries(app_src_sample ${PROJECT_NAME})
add_executable(paddle_infer_sample "paddle_infer_sample.cpp")
target_link_libraries(paddle_infer_sample ${PROJECT_NAME})
endif()
# samples depend on CUDA(maybe other dependency required too)
if(VP_WITH_CUDA)
# nvdec & nvenc plugins required from DeepStream
add_executable(nv_hard_codec_sample "nv_hard_codec_sample.cpp")
target_link_libraries(nv_hard_codec_sample ${PROJECT_NAME})
endif()
# samples depend on TensorRT
if(VP_WITH_TRT)
add_executable(ba_jam_sample "ba_jam_sample.cpp")
target_link_libraries(ba_jam_sample ${PROJECT_NAME})
add_executable(ba_stop_sample "ba_stop_sample.cpp")
target_link_libraries(ba_stop_sample ${PROJECT_NAME})
add_executable(body_scan_and_plate_detect_sample "body_scan_and_plate_detect_sample.cpp")
target_link_libraries(body_scan_and_plate_detect_sample ${PROJECT_NAME})
add_executable(dynamic_pipeline_sample "dynamic_pipeline_sample.cpp")
target_link_libraries(dynamic_pipeline_sample ${PROJECT_NAME})
add_executable(dynamic_pipeline_sample2 "dynamic_pipeline_sample2.cpp")
target_link_libraries(dynamic_pipeline_sample2 ${PROJECT_NAME})
add_executable(message_broker_sample2 "message_broker_sample2.cpp")
target_link_libraries(message_broker_sample2 ${PROJECT_NAME})
add_executable(multi_trt_infer_nodes_sample "multi_trt_infer_nodes_sample.cpp")
target_link_libraries(multi_trt_infer_nodes_sample ${PROJECT_NAME})
add_executable(plate_recognize_sample "plate_recognize_sample.cpp")
target_link_libraries(plate_recognize_sample ${PROJECT_NAME})
add_executable(src_des_sample "src_des_sample.cpp")
target_link_libraries(src_des_sample ${PROJECT_NAME})
add_executable(trt_infer_sample "trt_infer_sample.cpp")
target_link_libraries(trt_infer_sample ${PROJECT_NAME})
add_executable(vehicle_body_scan_sample "vehicle_body_scan_sample.cpp")
target_link_libraries(vehicle_body_scan_sample ${PROJECT_NAME})
add_executable(vehicle_cluster_based_on_classify_encoding_sample "vehicle_cluster_based_on_classify_encoding_sample.cpp")
target_link_libraries(vehicle_cluster_based_on_classify_encoding_sample ${PROJECT_NAME})
add_executable(vehicle_tracking_sample "vehicle_tracking_sample.cpp")
target_link_libraries(vehicle_tracking_sample ${PROJECT_NAME})
add_executable(1-N-1_sample "1-N-1_sample.cpp")
target_link_libraries(1-N-1_sample ${PROJECT_NAME})
add_executable(1-N-1_sample2 "1-N-1_sample2.cpp")
target_link_libraries(1-N-1_sample2 ${PROJECT_NAME})
add_executable(1-N-1_sample3 "1-N-1_sample3.cpp")
target_link_libraries(1-N-1_sample3 ${PROJECT_NAME})
add_executable(trt_yolov8_sample "trt_yolov8_sample.cpp")
target_link_libraries(trt_yolov8_sample ${PROJECT_NAME})
add_executable(trt_yolov8_sample2 "trt_yolov8_sample2.cpp")
target_link_libraries(trt_yolov8_sample2 ${PROJECT_NAME})
add_executable(rtmp_src_sample "rtmp_src_sample.cpp")
target_link_libraries(rtmp_src_sample ${PROJECT_NAME})
endif()
if(VP_BUILD_COMPLEX_SAMPLES)
message("start build for complex sampels...")
# save exe to 'face_recognize'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/face_recognize)
add_executable(face_recognize_pipeline "face_recognize/face_recognize_pipeline.cpp")
target_link_libraries(face_recognize_pipeline ${PROJECT_NAME})
if(VP_WITH_TRT) # samples depend on TensorRT
# save exe to 'similiarity_search'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/similiarity_search)
add_executable(face_encoding_pipeline "similiarity_search/face_encoding_pipeline.cpp")
target_link_libraries(face_encoding_pipeline ${PROJECT_NAME})
add_executable(vehicle_encoding_pipeline "similiarity_search/vehicle_encoding_pipeline.cpp")
target_link_libraries(vehicle_encoding_pipeline ${PROJECT_NAME})
# save exe to 'vehicle_behaviour_analysis'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/vehicle_behaviour_analysis)
add_executable(vehicle_ba_pipeline "vehicle_behaviour_analysis/vehicle_ba_pipeline.cpp")
target_link_libraries(vehicle_ba_pipeline ${PROJECT_NAME})
# save exe to 'vehicle_property_and_similiarity_search'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/vehicle_property_and_similiarity_search)
add_executable(vehicle_encoding_classify_pipeline "vehicle_property_and_similiarity_search/vehicle_encoding_classify_pipeline.cpp")
target_link_libraries(vehicle_encoding_classify_pipeline ${PROJECT_NAME})
# save exe to 'lpr_camera'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/lpr_camera)
add_executable(plate_recognize_pipeline "lpr_camera/plate_recognize_pipeline.cpp")
target_link_libraries(plate_recognize_pipeline ${PROJECT_NAME})
endif()
if(VP_WITH_PADDLE)
# save exe to 'math_review'
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/math_review)
add_executable(math_expression_check_pipeline "math_review/math_expression_check_pipeline.cpp")
target_link_libraries(math_expression_check_pipeline ${PROJECT_NAME})
endif()
endif()

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_split_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## N-1-N sample ##
* 2 video input and merge into 1 branch automatically for 1 infer task, then resume to 2 branches for outputs again.
*/
int main() {
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::WARN);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/face2.mp4", 0.6);
auto yunet_face_detector = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true); // split by channel index
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000");
auto osd_1 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_1");
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
auto rtmp_des_1 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_1", 1, "rtmp://192.168.77.60/live/10000");
// construct pipeline
yunet_face_detector->attach_to({file_src_0, file_src_1});
sface_face_encoder->attach_to({yunet_face_detector});
split->attach_to({sface_face_encoder});
// split by vp_split_node
osd_0->attach_to({split});
osd_1->attach_to({split});
// auto split again on channel 0
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
// auto split again on channel 1
screen_des_1->attach_to({osd_1});
rtmp_des_1->attach_to({osd_1});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## N-N sample ##
* multi pipe exist separately and each pipe is 1-1-1 (can be any structure like 1-1-N, 1-N-N)
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 0, "./vp_data/test_video/face2.mp4");
auto yunet_face_detector_1 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_1", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_1 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_1", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_1 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_1");
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 0);
// construct pipeline
// pipe 0
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
screen_des_0->attach_to({osd_0});
// pipe 1
yunet_face_detector_1->attach_to({file_src_1});
sface_face_encoder_1->attach_to({yunet_face_detector_1});
osd_1->attach_to({sface_face_encoder_1});
screen_des_1->attach_to({osd_1});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display();
}

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## 1-1-1_sample ##
1 video input, 1 infer task, and 1 output.
![](../doc/p10.png)
## 1-1-N_sample ##
1 video input, 1 infer task, and 2 outputs.
![](../doc/p11.png)
## 1-N-N_sample ##
1 video input and then split into 2 branches for different infer tasks, then 2 total outputs.
![](../doc/p12.png)
## N-1-N_sample ##
2 video input and merge into 1 branch automatically for 1 infer task, then resume to 2 branches for outputs again.
![](../doc/p13.png)
## N-N_sample ##
multi pipe exist separately and each pipe is 1-1-1 (can be any structure like 1-1-N, 1-N-N)
![](../doc/p14.png)
## paddle_infer_sample ##
ocr based on paddle (install paddle_inference first!), 1 video input and 2 outputs (screen, rtmp)
![](../doc/p15.png)
## src_des_sample ##
show how src nodes and des nodes work.
3 (file, rtsp, udp) input and merge into 1 infer task, then resume to 3 branches for outputs (screen, rtmp, fake)
![](../doc/p16.png)
## trt_infer_sample ##
vehicle and plate detector based on tensorrt (install tensorrt first!), 1 video input and 3 outputs (screen, file, rtmp)
![](../doc/p17.png)
## vp_logger_sample ##
show how `vp_logger` works.
## face_tracking_sample ##
tracking for multi faces.
![](../doc/p18.png)
## vehicle_tracking_sample ##
tracking for multi vehicles.
![](../doc/p22.png)
## interaction_with_pipe_sample ##
show how to interact with pipe, such as start/stop channel by calling api.
## record_sample ##
show how `vp_record_node` works.
## message_broker_sample & message_broker_sample2 ##
show how message broker nodes work.
![](../doc/p20.png)
![](../doc/p21.png)
## mask_rcnn_sample ##
show image segmentation by mask-rcnn.
![](../doc/p30.png)
## openpose_sample ##
show pose estimation by openpose network.
![](../doc/p31.png)
## enet_seg_sample ##
show semantic segmentation by enet network.
![](../doc/p32.png)
## multi_detectors_and_classifiers_sample ##
show multi infer node work together.
![](../doc/p33.png)
## image_des_sample ##
show save/push image to local file or remote via udp.
![](../doc/p34.png)
## image_src_sample ##
show read/receive image from local file or remote via udp.
![](../doc/p35.png)
## rtsp_des_sample ##
show push video stream via rtsp, no rtsp server needed, you can visit it directly.
![](../doc/p36.png)
## ba_crossline_sample ##
count for vehicle based on tracking, the simplest one of behaviour analysis.
![](../doc/p37.png)
## plate_recognize_sample ##
vehicle plate detect and recognize on the whole frame (no need to detect vechile first)
![](../doc/p38.png)
## vehicle_body_scan_sample ##
detect parts of vehicle based on side view of body
![](../doc/p40.png)
## body_scan_and_plate_detect_sample ##
2 channels to detect parts of vehicle and detect vehicle plate, you can do something like data fusion later
![](../doc/p39.png)
## app_src_sample ##
send data to pipeline from host coda using app_src_node
![](../doc/p41.png)
## vehicle_cluster_based_on_classify_encoding_sample ##
vehicle cluster based on labels(classify) and encoding(feature extract), pipeline would display 3 windows (cluster by t-SNE, cluster by labels, detect result)
![](../doc/p42.png)
## ba_stop_sample ##
vehicle stop behaviour analysis
![](../doc/p49.png)
## similiarity search ##
flask demo for vehicle and face similiarity search <br/>
![](../doc/p44.png)![](../doc/p43.png)![](../doc/p45.png)
## behaviour analysis ##
flask demo for crossline and stop<br/>
![](../doc/p48.png)
## property and similiarity search ##
flask demo for vehicle search by similiarity and properties<br/>
![](../doc/p46.png)![](../doc/p47.png)
## ba_jam_sample ##
traffic jam behaviour analysis<br/>
![](../doc/p50.png)
## face recognize ##
flask demo for face recognize<br/>
![](../doc/p51.png)
## license plate recognize ##
flask demo for license plate recognize<br/>
![](../doc/p52.png)
[for more samples](../SAMPLES.md)

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_app_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## app_des_sample ##
* 1. reading video from file
* 2. detect faces and draw results
* 3. display on screen in host code using cv::imshow(...)
* using vp_app_des_node INSTEAD OF vp_screen_des_node for displaying.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4");
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node>("osd_0");
auto app_des_0 = std::make_shared<vp_nodes::vp_app_des_node>("app_des_0", 0);
// register callback to display result
std::string ori_win_title = "original frame using cv::imshow(...)";
std::string osd_win_title = "osd frame using cv::imshow(...)";
cv::namedWindow(ori_win_title,cv::WindowFlags::WINDOW_NORMAL);
cv::namedWindow(osd_win_title,cv::WindowFlags::WINDOW_NORMAL);
app_des_0->set_app_des_result_hooker([&](std::string node_name, std::shared_ptr<vp_objects::vp_meta> meta) {
// only deal with frame meta
if (meta->meta_type == vp_objects::vp_meta_type::FRAME) {
auto frame_meta = std::dynamic_pointer_cast<vp_objects::vp_frame_meta>(meta);
cv::imshow(ori_win_title, frame_meta->frame);
// osd frame may be empty
if (!frame_meta->osd_frame.empty()) {
cv::imshow(osd_win_title, frame_meta->osd_frame);
}
}
});
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
osd_0->attach_to({yunet_face_detector_0});
app_des_0->attach_to({osd_0});
// start pipeline
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_app_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_app_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## app_src_des_sample ##
* 1. receive images from host code， based on vp_app_src_node
* 2. detect faces and draw results
* 3. display on screen in host code again using cv::imshow(...) and print rectangles and keypoints of face, based on vp_app_des_node
* we treat VideoPipe(pipeline) as a simple face detector tool in this sample.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto app_src_0 = std::make_shared<vp_nodes::vp_app_src_node>("app_src_0", 0);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node>("osd_0");
auto app_des_0 = std::make_shared<vp_nodes::vp_app_des_node>("app_des_0", 0);
// register callback to display result
std::string ori_win_title = "original frame using cv::imshow(...)";
std::string osd_win_title = "osd frame using cv::imshow(...)";
cv::namedWindow(ori_win_title,cv::WindowFlags::WINDOW_NORMAL);
cv::namedWindow(osd_win_title,cv::WindowFlags::WINDOW_NORMAL);
app_des_0->set_app_des_result_hooker([&](std::string node_name, std::shared_ptr<vp_objects::vp_meta> meta) {
// only deal with frame meta
if (meta->meta_type == vp_objects::vp_meta_type::FRAME) {
auto frame_meta = std::dynamic_pointer_cast<vp_objects::vp_frame_meta>(meta);
cv::imshow(ori_win_title, frame_meta->frame);
// osd frame may be empty
if (!frame_meta->osd_frame.empty()) {
cv::imshow(osd_win_title, frame_meta->osd_frame);
}
// print rectangle and keypoints of face
std::cout << "detected " << frame_meta->face_targets.size() << " faces:(print from host code)" << std::endl;
for (int i = 0; i < frame_meta->face_targets.size(); ++i) {
auto f = frame_meta->face_targets[i];
std::cout << i << ": [" << f->x << "," << f->y << "," << f->width << "," << f->height << "] [";
for (auto k: f->key_points) {
std::cout << "(" << k.first << "," << k.second << ")";
}
std::cout << "]" << std::endl;
}
}
});
// construct pipeline
yunet_face_detector_0->attach_to({app_src_0});
osd_0->attach_to({yunet_face_detector_0});
app_des_0->attach_to({osd_0});
// start pipeline
app_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({app_src_0});
board.display(1, false); // no block
// read image in host code manually
auto img = cv::imread("./vp_data/test_images/faces/swap/2mans.jpg");
// push image to pipeline in host code manually
app_src_0->push_frames({img});
// pipeline will process image asynchronously and display result here...
std::string wait;
std:getline(std::cin, wait);
}

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#include "../nodes/vp_app_src_node.h"
#include "../nodes/infers/vp_ppocr_text_detector_node.h"
#include "../nodes/osd/vp_text_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## app src sample ##
* receive frames(cv::Mat) from host code
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto app_src_0 = std::make_shared<vp_nodes::vp_app_src_node>("app_src_0", 0);
auto ppocr_text_detector = std::make_shared<vp_nodes::vp_ppocr_text_detector_node>("ppocr_text_detector",
"./vp_data/models/text/ppocr/ch_PP-OCRv3_det_infer",
"./vp_data/models/text/ppocr/ch_ppocr_mobile_v2.0_cls_infer",
"./vp_data/models/text/ppocr/ch_PP-OCRv3_rec_infer",
"./vp_data/models/text/ppocr/ppocr_keys_v1.txt");
auto osd_0 = std::make_shared<vp_nodes::vp_text_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
ppocr_text_detector->attach_to({app_src_0});
osd_0->attach_to({ppocr_text_detector});
screen_des_0->attach_to({osd_0});
// start pipeline
app_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({app_src_0});
board.display(1, false); // no block since we need interactions from console later
// simulate push frame to pipeline regularly in a separate thread
bool exit = false;
auto simulate_run = [&]() {
auto index = 0;
auto count = 0;
auto path = "./vp_data/test_images/text/";
while (!exit) {
auto frame = cv::imread(path + std::to_string(index) + ".jpg");
assert(!frame.empty());
app_src_0->push_frames({frame}); // push frame to pipeline, return false means failed
count++;
std::cout << "main thread has pushed [" << count << "] frames into pipeline..." << std::endl;
index++;
index = index % 3;
std::this_thread::sleep_for(std::chrono::milliseconds(2000)); // sleep for 2 seconds
}
};
std::thread simulate_thread(simulate_run);
/* interact from console, start or stop the pipeline */
/* no except check */
std::string input;
std::getline(std::cin, input);
while (input != "quit") {
if (input == "start") {
app_src_0->start();
}
else if (input == "stop") {
app_src_0->stop(); // app_src_0->push_frames(...) will print Warn message since it has stopped working
}
else {
std::cout << "invalid command!" << std::endl;
}
std::getline(std::cin, input);
}
std::cout << "app_src_sample sample exits..." << std::endl;
exit = true;
simulate_thread.join();
app_src_0->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/ba/vp_ba_crossline_node.h"
#include "../nodes/osd/vp_ba_crossline_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## ba crossline sample ##
* behaviour analysis for crossline.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.4);
auto yolo_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("yolo_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 tracker = std::make_shared<vp_nodes::vp_sort_track_node>("sort_tracker");
// define a line in frame for every channel (value MUST in the scope of frame'size)
vp_objects::vp_point start(0, 250); // change to proper value
vp_objects::vp_point end(700, 220); // change to proper value
std::map<int, vp_objects::vp_line> lines = {{0, vp_objects::vp_line(start, end)}}; // channel0 -> line
auto ba_crossline = std::make_shared<vp_nodes::vp_ba_crossline_node>("ba_crossline", lines);
auto osd = std::make_shared<vp_nodes::vp_ba_crossline_osd_node>("osd");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/9000");
// construct pipeline
yolo_detector->attach_to({file_src_0});
tracker->attach_to({yolo_detector});
ba_crossline->attach_to({tracker});
osd->attach_to({ba_crossline});
screen_des_0->attach_to({osd});
rtmp_des_0->attach_to({osd});
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();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/ba/vp_ba_jam_node.h"
#include "../nodes/osd/vp_ba_jam_osd_node.h"
#include "../nodes/record/vp_record_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## ba jam sample ##
* behaviour analysis for jam, single instance of ba node work on 2 channels.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/jam.mp4", 0.5);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/jam2.mp4");
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
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, 360),
vp_objects::vp_point(400, 250),
vp_objects::vp_point(535, 250),
vp_objects::vp_point(555, 560),
vp_objects::vp_point(30, 550)}}, // channel0 -> region
{1, std::vector<vp_objects::vp_point>{vp_objects::vp_point(20*0.6, 588*0.6),
vp_objects::vp_point(786*0.6, 180*0.6),
vp_objects::vp_point(968*0.6, 166*0.6),
vp_objects::vp_point(1220*0.6, 665*0.6)}} // channel1 -> region
};
auto ba_jam = std::make_shared<vp_nodes::vp_ba_jam_node>("ba_jam", regions);
auto osd = std::make_shared<vp_nodes::vp_ba_jam_osd_node>("jam_osd");
auto recorder = std::make_shared<vp_nodes::vp_record_node>("recorder", "./record", "./record");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
trt_vehicle_detector->attach_to({file_src_0, file_src_1});
tracker->attach_to({trt_vehicle_detector});
ba_jam->attach_to({tracker});
osd->attach_to({ba_jam});
recorder->attach_to({osd});
split->attach_to({recorder});
screen_des_0->attach_to({split});
screen_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/ba/vp_ba_stop_node.h"
#include "../nodes/osd/vp_ba_stop_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## ba stop sample ##
* behaviour analysis for stop, single instance of ba node work on 2 channels.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_stop.mp4", 0.6);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/vehicle_stop.mp4", 0.6);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data//models/trt/vehicle/vehicle_v8.5.trt");
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_stop = std::make_shared<vp_nodes::vp_ba_stop_node>("ba_stop", regions);
auto osd = std::make_shared<vp_nodes::vp_ba_stop_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
trt_vehicle_detector->attach_to({file_src_0, file_src_1});
tracker->attach_to({trt_vehicle_detector});
ba_stop->attach_to({tracker});
osd->attach_to({ba_stop});
split->attach_to({osd});
screen_des_0->attach_to({split});
screen_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_scanner.h"
#include "../nodes/infers/vp_trt_vehicle_plate_detector_v2.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/osd/vp_plate_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## body_scan_and_plate_detect_sample ##
* first channel detects wheels and vehicle type based on side view of vehicle
* second channel detects plate based on head view of vehicle
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_0", 0, "./vp_data/test_images/body/%d.jpg");
auto image_src_1 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_1", 1, "./vp_data/test_images/plates/%d.jpg");
auto vehicle_scanner = std::make_shared<vp_nodes::vp_trt_vehicle_scanner>("vehicle_scanner",
"./vp_data/models/trt/vehicle/vehicle_scan_v8.5.trt");
auto plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector_v2>("plate_detector",
"./vp_data/models/trt/plate/det_v8.5.trt",
"./vp_data/models/trt/plate/rec_v8.5.trt");
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto osd_1 = std::make_shared<vp_nodes::vp_plate_osd_node>("osd_1", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct first pipeline
vehicle_scanner->attach_to({image_src_0});
osd_0->attach_to({vehicle_scanner});
screen_des_0->attach_to({osd_0});
// construct second pipeline
plate_detector->attach_to({image_src_1});
osd_1->attach_to({plate_detector});
screen_des_1->attach_to({osd_1});
image_src_0->start();
image_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0, image_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
image_src_0->detach_recursively();
image_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/broker/vp_json_console_broker_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## dynamic_pipeline_sample ##
* 1. insert and remove channels(SRC & DES nodes) to/from existing pipeline.
* 2. insert and remove MID nodes to/from existing pipeline.
* 3. all nodes destroy and process exit normally after user press enter from console.
* 4. no need to stop the pipeline and all operations in multi-threads, it works with hot-plug mode.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_stop.mp4", 0.4);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline the first time
trt_vehicle_detector->attach_to({file_src_0});
osd->attach_to({trt_vehicle_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
std::vector<std::shared_ptr<vp_nodes::vp_node>> src_nodes = {file_src_0};
vp_utils::vp_analysis_board board(src_nodes);
board.display(1, false); // no block
/* the original format of pipeline is:
file_src_0 -> trt_vehicle_detector -> osd -> split -> screen_des_0
*/
// simulation function for dynamically operating on piepline
bool exit = false;
auto simulate_run = [&]() {
while (!exit) {
// 1. wait for 5 seconds then insert the 2nd channel(input and output) to pipeline
std::this_thread::sleep_for(std::chrono::seconds(5));
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/vehicle_stop.mp4", 0.4);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
trt_vehicle_detector->attach_to({file_src_1});
screen_des_1->attach_to({split});
// start 2nd channel
file_src_1->start();
// reload board using 2 SRC nodes
src_nodes.push_back(file_src_1);
board.reload(src_nodes);
/* now the format of pipeline is:
file_src_0 \ / screen_des_0
-> trt_vehicle_detector -> osd -> split ->
file_src_1 / \ screen_des_1
*/
// 2. wait for 5 seconds then insert the 3rd channel(input and output) to pipeline
std::this_thread::sleep_for(std::chrono::seconds(5));
auto file_src_2 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_2", 2, "./vp_data/test_video/vehicle_stop.mp4", 0.4);
auto screen_des_2 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_2", 2);
trt_vehicle_detector->attach_to({file_src_2});
screen_des_2->attach_to({split});
// start 3rd channel
file_src_2->start();
// reload board using 3 SRC nodes
src_nodes.push_back(file_src_2);
board.reload(src_nodes);
/* now the format of pipeline is:
file_src_0 \ / screen_des_0
file_src_1 -> trt_vehicle_detector -> osd -> split -> screen_des_1
file_src_2 / \ screen_des_2
*/
// 3. wait for 5 seconds then remove the DES node(output) of 3rd channel from pipeline
std::this_thread::sleep_for(std::chrono::seconds(5));
screen_des_2->detach(); // call detach() since there is only 1 previous node for screen_des_2
screen_des_2 = nullptr; // force call destructor immediately
// reload board using previous SRC nodes
board.reload();
/* now the format of pipeline is:
file_src_0 \ / screen_des_0
file_src_1 -> trt_vehicle_detector -> osd -> split -> screen_des_1
file_src_2 /
*/
// 4. wait for 5 seconds then remove the SRC node(input) of 3rd channel from pipeline
std::this_thread::sleep_for(std::chrono::seconds(5));
trt_vehicle_detector->detach_from({"file_src_2"}); // call detach_from(...) since there are many previous nodes for trt_vehicle_detector
file_src_2->stop(); // call stop() on SRC node which is not reused later
file_src_2 = nullptr; // force call destructor immediately
// reload board using 2 SRC nodes
src_nodes.pop_back();
board.reload(src_nodes);
/* now the format of pipeline is:
file_src_0 \ / screen_des_0
-> trt_vehicle_detector -> osd -> split ->
file_src_1 / \ screen_des_1
*/
// 5. wait for 5 seconds then insert a secondary classifier node, track node and broker node into pipeline
std::this_thread::sleep_for(std::chrono::seconds(5));
auto trt_color_cls = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("trt_color_cls", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto track = std::make_shared<vp_nodes::vp_sort_track_node>("track");
auto console_broker = std::make_shared<vp_nodes::vp_json_console_broker_node>("console_broker");
osd->detach(); // first detach osd node from pipeline
osd->attach_to({console_broker}); // then attach osd node to broker node
console_broker->attach_to({track}); // attach broker node to track node
track->attach_to({trt_color_cls}); // attach track node to classifier node
trt_color_cls->attach_to({trt_vehicle_detector}); // attach classifier node into pipeline
// reload board using previous SRC nodes
board.reload();
/* now the format of pipeline is:
file_src_0 \ / screen_des_0
-> trt_vehicle_detector -> trt_color_cls -> track -> console_broker -> osd -> split ->
file_src_1 / \ screen_des_1
*/
// 6. wait for 10 seconds then remove the 2nd channel (both SRC node and DES node) from pipeline
std::this_thread::sleep_for(std::chrono::seconds(10));
screen_des_1->detach(); // call detach() since there is only 1 previous node for screen_des_1
trt_vehicle_detector->detach_from({"file_src_1"}); // call detach_from(...) since there are many previous nodes for trt_vehicle_detector
file_src_1->stop(); // call stop() on SRC node which is not reused later
screen_des_1 = nullptr; // force call destructor immediately
file_src_1 = nullptr; // force call destructor immediately
// reload board using 1 SRC nodes
src_nodes.pop_back();
board.reload(src_nodes);
/* now the format of pipeline is:
file_src_0 -> trt_vehicle_detector -> trt_color_cls -> track -> console_broker -> osd -> split -> screen_des_0
*/
// 7. wait for 10 seconds then remove classifier node, track node and broker node from pipeline
std::this_thread::sleep_for(std::chrono::seconds(10));
osd->detach();
console_broker->detach();
track->detach();
trt_color_cls->detach();
osd->attach_to({trt_vehicle_detector}); // relink osd and trt_vehicle_detector
console_broker = nullptr;
track = nullptr;
trt_color_cls = nullptr;
// reload board using previous SRC nodes
board.reload();
/* now the format of pipeline is:
file_src_0 -> trt_vehicle_detector -> osd -> split -> screen_des_0
*/
}
};
// start simulation thread
std::thread simulator(simulate_run);
// enter to exit
std::string input;
std::getline(std::cin, input);
exit = true;
simulator.join();
// split pipeline into single nodes before process exit
for (auto& n: src_nodes) {
n->detach_recursively();
}
// pipeline destroyed and process exit normally
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
#include "../nodes/record/vp_record_node.h"
#include "../nodes/broker/vp_json_console_broker_node.h"
#include "../nodes/vp_rtsp_src_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/infers/vp_trt_vehicle_type_classifier.h"
/*
* ## dynamic_pipeline_sample2 ##
* insert/remove nodes to/from pipeline step by step, then process exits normally.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_stop.mp4", 0.4);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto console_broker = std::make_shared<vp_nodes::vp_json_console_broker_node>("console_broker");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
trt_vehicle_detector->attach_to({file_src_0});
osd->attach_to({trt_vehicle_detector});
console_broker->attach_to({osd});
split->attach_to({console_broker});
screen_des_0->attach_to({split});
file_src_0->start();
std::vector<std::shared_ptr<vp_nodes::vp_node>> src_nodes = {file_src_0};
std::string wait;
std::cin >> wait; // display pipeline
vp_utils::vp_analysis_board board(src_nodes);
board.display(1, false); // no block
std::cin >> wait; // add rtsp input
auto rtsp_src_1 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_1", 1, "rtsp://admin:admin12345@192.168.77.203", 0.4);
trt_vehicle_detector->attach_to({rtsp_src_1});
rtsp_src_1->start();
src_nodes.push_back(rtsp_src_1);
board.reload(src_nodes);
std::cin >> wait; // add rtmp output
auto rtmp_des_1 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_1", 1, "rtmp://192.168.77.60/live/dynamic_pipeline_sample2");
rtmp_des_1->attach_to({split});
board.reload();
std::cin >> wait; // add classifier
auto trt_vehicle_type_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_type_classifier>("trt_type_cls", "./vp_data/models/trt/vehicle/vehicle_type_v8.5.trt", std::vector<int>{0, 1, 2});
osd->detach();
osd->attach_to({trt_vehicle_type_classifier});
trt_vehicle_type_classifier->attach_to({trt_vehicle_detector});
board.reload();
std::cin >> wait; // remove broker
console_broker->detach();
split->detach();
split->attach_to({osd});
board.reload();
std::cin >> wait; // destroy pipeline and process exit
for(auto& n: src_nodes) {
n->detach_recursively();
}
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_enet_seg_node.h"
#include "../nodes/osd/vp_seg_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## enet seg sample ##
* semantic segmentation based on ENet.
* 1 input, 2 outputs including orignal frame and mask frame.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/enet_seg.mp4");
auto enet_seg = std::make_shared<vp_nodes::vp_enet_seg_node>("enet_seg", "./vp_data/models/enet-cityscapes/enet-model.net");
auto seg_osd_0 = std::make_shared<vp_nodes::vp_seg_osd_node>("seg_osd_0", "./vp_data/models/enet-cityscapes/enet-classes.txt", "./vp_data/models/enet-cityscapes/enet-colors.txt");
auto screen_des_mask = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_mask", 0, true, vp_objects::vp_size(400, 225));
auto screen_des_original = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_original", 0, false, vp_objects::vp_size(400, 225));
// construct pipeline
enet_seg->attach_to({file_src_0});
seg_osd_0->attach_to({enet_seg});
screen_des_mask->attach_to({seg_osd_0});
screen_des_original->attach_to({seg_osd_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_face_swap_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_file_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## face_swap_sample ##
* swap face for any video/images, no training need before running.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 1.0, true, "avdec_h264", 4);
auto yunet_face_detector = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto face_swap = std::make_shared<vp_nodes::vp_face_swap_node>("face_swap", "./vp_data/models/face/face_detection_yunet_2022mar.onnx", "./vp_data/models/face/swap/w600k_r50.onnx", "./vp_data/models/face/swap/emap.txt", "./vp_data/models/face/swap/inswapper_128.onnx", "./github/inswapper/data/mans1.jpeg");
//auto osd = std::make_shared<vp_nodes::vp_face_osd_node>("osd");
auto screen_des_0_ori = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_ori", 0, false);
auto screen_des_0_osd = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_osd", 0);
auto file_des_node_0 = std::make_shared<vp_nodes::vp_file_des_node>("file_des_0", 0, ".", "", 1);
// construct pipeline
yunet_face_detector->attach_to({file_src_0});
face_swap->attach_to({yunet_face_detector});
//osd->attach_to({face_swap});
screen_des_0_ori->attach_to({face_swap});
screen_des_0_osd->attach_to({face_swap});
file_des_node_0->attach_to({face_swap}); // save swap result to file
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();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## face tracking sample ##
* track for multi faces using vp_sort_track_node.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4");
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto track_0 = std::make_shared<vp_nodes::vp_sort_track_node>("track_0", vp_nodes::vp_track_for::FACE); // track for face
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
track_0->attach_to({sface_face_encoder_0});
osd_0->attach_to({track_0});
screen_des_0->attach_to({osd_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/ffio/vp_ff_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/ffio/vp_ff_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## ffmpeg_src_des_sample ##
* reading & pushing stream based on ffmpeg (soft decode and encode using CPUs).
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
/*
uri for vp_ff_src_node:
1. rtmp://192.168.77.196/live/1000 --> reading rtmp live stream
2. rtsp://192.168.77.213/live/mainstream --> reading rtsp live stream
3. ./vp_data/test_video/face.mp4 --> reading video file
uri for vp_ff_des_node:
1. rtmp://192.168.77.196/live/10000 --> pushing rtmp live stream
2. ./output/records.mp4 --> saving to video file
*/
auto ff_src_0 = std::make_shared<vp_nodes::vp_ff_src_node>("ff_src_0", 0, "./vp_data/test_video/face.mp4", "h264", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto ff_des_0 = std::make_shared<vp_nodes::vp_ff_des_node>("ff_des_0", 0, "rtmp://192.168.77.60/live/20000");
//auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.196/live/20000");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({ff_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
ff_des_0->attach_to({osd_0});
screen_des_0->attach_to({osd_0});
ff_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({ff_src_0});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
ff_src_0->detach_recursively();
}

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#include "../nodes/ffio/vp_ff_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/ffio/vp_ff_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## ffmpeg_transcode_sample ##
* transcoding in parallel, modify codec & resolution & bitrate & add watermask in picture.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto ff_src_0 = std::make_shared<vp_nodes::vp_ff_src_node>("ff_src_0", 0, "rtmp://192.168.77.196/live/1000", "h264", 0.5);
auto ff_des_0 = std::make_shared<vp_nodes::vp_ff_des_node>("ff_des_0", 0, "rtmp://192.168.77.196/live/0");
auto ff_src_1 = std::make_shared<vp_nodes::vp_ff_src_node>("ff_src_1", 0, "rtmp://192.168.77.196/live/1000", "h264", 0.5);
auto ff_des_1 = std::make_shared<vp_nodes::vp_ff_des_node>("ff_des_1", 0, "rtmp://192.168.77.196/live/1");
auto ff_src_2 = std::make_shared<vp_nodes::vp_ff_src_node>("ff_src_2", 0, "rtsp://192.168.77.213/live/mainstream", "h264", 0.5);
auto ff_des_2 = std::make_shared<vp_nodes::vp_ff_des_node>("ff_des_2", 0, "rtmp://192.168.77.196/live/2");
auto ff_src_3 = std::make_shared<vp_nodes::vp_ff_src_node>("ff_src_3", 0, "rtsp://192.168.77.213/live/mainstream", "h264", 0.5);
auto ff_des_3 = std::make_shared<vp_nodes::vp_ff_des_node>("ff_des_3", 0, "rtmp://192.168.77.196/live/3");
// construct pipeline
ff_des_0->attach_to({ff_src_0});
ff_des_1->attach_to({ff_src_1});
ff_des_2->attach_to({ff_src_2});
ff_des_3->attach_to({ff_src_3});
// start pipelines
ff_src_0->start();
ff_src_1->start();
ff_src_2->start();
ff_src_3->start();
// for debug purpose
vp_utils::vp_analysis_board board({ff_src_0, ff_src_1, ff_src_2, ff_src_3});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
ff_src_0->detach_recursively();
ff_src_1->detach_recursively();
ff_src_2->detach_recursively();
ff_src_3->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtsp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## firesmoke_detect_sample ##
* detect firesmoke using yolo.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/smoke2.mp4", 0.5);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/fire.mp4", 0.5);
auto yolo_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);
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split_by_channel", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto srceen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
yolo_detector->attach_to({file_src_0, file_src_1});
osd->attach_to({yolo_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
srceen_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/proc/vp_frame_fusion_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_placeholder_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## frame_fusion_sample ##
* fuse frames of 2 channels, just merge adjacent frames from 2 channels directly without considering timestamp synchronization.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/infrared.mp4"); // source of fusion
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/rgb.mp4"); // destination of fusion
// initialize calibration points manually
std::vector<vp_objects::vp_point> src_cali_points = {vp_objects::vp_point(133, 111), vp_objects::vp_point(338, 110), vp_objects::vp_point(15, 330), vp_objects::vp_point(14, 214)};
std::vector<vp_objects::vp_point> des_cali_points = {vp_objects::vp_point(1219, 365), vp_objects::vp_point(1787, 367), vp_objects::vp_point(891, 982), vp_objects::vp_point(892, 659)};
auto fusion = std::make_shared<vp_nodes::vp_frame_fusion_node>("fusion", src_cali_points, des_cali_points);
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto screen_des_0_ori = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_ori", 0, false); // original frame for the first channel
auto screen_des_1_osd = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1_osd", 1); // fusion result(osd frame) for the second channel
// construct pipeline
fusion->attach_to({file_src_0, file_src_1});
split->attach_to({fusion});
screen_des_0_ori->attach_to({split});
screen_des_1_osd->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_image_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## image_des_sample ##
* show how vp_image_des_node works, save image to local file or push image to remote via udp.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
/* save to file, `%d` is placeholder for filename index */
//auto image_des_0 = std::make_shared<vp_nodes::vp_image_des_node>("image_file_des_0", 0, "./images/%d.jpg", 3, vp_objects::vp_size(), false);
/* push via udp, receiving command for test: `gst-launch-1.0 udpsrc port=6000 ! application/x-rtp,encoding-name=jpeg ! rtpjpegdepay ! jpegparse ! jpegdec ! queue ! videoconvert ! autovideosink` */
auto image_des_0 = std::make_shared<vp_nodes::vp_image_des_node>("image_udp_des_0", 0, "192.168.77.248:6000", 2, vp_objects::vp_size(600, 300));
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
screen_des_0->attach_to({osd_0});
image_des_0->attach_to({osd_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## image_des_sample ##
* show how vp_image_src_node works, read image from local file or receive image from remote via udp.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_file_src_0", 0, "./vp_data/test_images/vehicle/%d.jpg", 1, 0.4); // read 1 image EVERY 1 second from local files, such as test_0.jpg,test_1.jpg
/* sending command for test: `gst-launch-1.0 filesrc location=16.mp4 ! qtdemux ! avdec_h264 ! videoconvert ! videoscale ! video/x-raw,width=416,height=416 ! videorate ! video/x-raw,framerate=1/1 ! jpegenc ! rtpjpegpay ! udpsink host=ip port=6000` */
auto image_src_1 = std::make_shared<vp_nodes::vp_image_src_node>("image_udp_src_1", 1, "6000", 3); // receive 1 image EVERY 3 seconds from remote via udp , such as 127.0.0.1:6000
auto yolo_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("yolo_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 osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split_by_channel", true); // split by channel index (important!)
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
yolo_detector->attach_to({image_src_0, image_src_1});
osd->attach_to({yolo_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
screen_des_1->attach_to({split});
image_src_0->start(); // start read from local file
image_src_1->start(); // start receive from remote via udp
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0, image_src_1});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_split_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## interaction_with_pipe sample ##
* show how to interact with pipe, start/stop/speak on src nodes independently.
*/
int main() {
VP_LOGGER_INIT();
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/face2.mp4", 0.6);
auto yunet_face_detector = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true); // split by channel index
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000");
auto osd_1 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_1");
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
auto rtmp_des_1 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_1", 1, "rtmp://192.168.77.60/live/10000");
// construct pipeline
yunet_face_detector->attach_to({file_src_0, file_src_1});
sface_face_encoder->attach_to({yunet_face_detector});
split->attach_to({sface_face_encoder});
// split by vp_split_node
osd_0->attach_to({split});
osd_1->attach_to({split});
// auto split again on channel 0
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
// auto split again on channel 1
screen_des_1->attach_to({osd_1});
rtmp_des_1->attach_to({osd_1});
// for debug purpose
std::vector<std::shared_ptr<vp_nodes::vp_node>> src_nodes_in_pipe{file_src_0, file_src_1};
vp_utils::vp_analysis_board board(src_nodes_in_pipe);
board.display(1, false); // no block since we need interactions from console later
/* interact from console */
/* no except check */
std::string input;
std::getline(std::cin, input);
// input format: `start channel`, like `start 0` means start channel 0
auto inputs = vp_utils::string_split(input, ' ');
while (inputs[0] != "quit") {
// no except check
auto command = inputs[0];
auto index = std::stoi(inputs[1]);
auto src_by_channel = std::dynamic_pointer_cast<vp_nodes::vp_src_node>(src_nodes_in_pipe[index]);
if (command == "start") {
src_by_channel->start();
}
else if (command == "stop") {
src_by_channel->stop();
}
else if (command == "speak") {
src_by_channel->speak();
}
else {
std::cout << "invalid command!" << std::endl;
}
std::getline(std::cin, input);
inputs = vp_utils::string_split(input, ' ');
if (inputs.size() != 2) {
std::cout << "invalid input!" << std::endl;
break;
}
}
std::cout << "interaction_with_pipe sample exits..." << std::endl;
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_lane_detector_node.h"
#include "../nodes/osd/vp_lane_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## lane_detect_sample ##
* detect lanes on road.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.6, true, "avdec_h264", 4);
auto lane_detector = std::make_shared<vp_nodes::vp_lane_detector_node>("lane_detector", "./vp_data/models/lane/lane_det.onnx");
auto lane_osd = std::make_shared<vp_nodes::vp_lane_osd_node>("lane_osd");
auto screen_des_0_osd = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_osd", 0);
auto srceen_des_0_ori = std::make_shared<vp_nodes::vp_screen_des_node>("srceen_des_0_ori", 0, false);
// construct pipeline
lane_detector->attach_to({file_src_0});
lane_osd->attach_to({lane_detector});
screen_des_0_osd->attach_to({lane_osd});
srceen_des_0_ori->attach_to({lane_osd});
// start pipeline
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();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_mask_rcnn_detector_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_osd_node_v3.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## mask rcnn sample ##
* image segmentation using mask rcnn.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/mask_rcnn.mp4", 0.6);
auto mask_rcnn_detector = std::make_shared<vp_nodes::vp_mask_rcnn_detector_node>("mask_rcnn_detector", "./vp_data/models/mask_rcnn/frozen_inference_graph.pb", "./vp_data/models/mask_rcnn/mask_rcnn_inception_v2_coco_2018_01_28.pbtxt", "./vp_data/models/coco_80classes.txt");
auto track_0 = std::make_shared<vp_nodes::vp_sort_track_node>("sort_track_0");
auto osd_v3_0 = std::make_shared<vp_nodes::vp_osd_node_v3>("osd_v3_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
mask_rcnn_detector->attach_to({file_src_0});
track_0->attach_to({mask_rcnn_detector});
osd_v3_0->attach_to({track_0});
screen_des_0->attach_to({osd_v3_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/broker/vp_json_kafka_broker_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## message_broker_kafka_sample ##
* show how message broker node works.
* serialize vp_frame_face_target objects to json and broke to kafka.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto json_kafka_broker_0 = std::make_shared<vp_nodes::vp_json_kafka_broker_node>("json_kafka_broker_0", "192.168.77.87:9092", "videopipe_topic", vp_nodes::vp_broke_for::FACE);
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
json_kafka_broker_0->attach_to({sface_face_encoder_0});
osd_0->attach_to({json_kafka_broker_0});
screen_des_0->attach_to({osd_0});
// start pipeline
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();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/broker/vp_json_console_broker_node.h"
#include "../nodes/broker/vp_xml_file_broker_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## message broker sample ##
* show how message broker node works.
* serialize vp_frame_face_target objects to json and broke to console.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto json_console_broker_0 = std::make_shared<vp_nodes::vp_json_console_broker_node>("json_console_broker_0", vp_nodes::vp_broke_for::FACE);
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
json_console_broker_0->attach_to({sface_face_encoder_0});
osd_0->attach_to({json_console_broker_0});
screen_des_0->attach_to({osd_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_plate_detector.h"
#include "../nodes/osd/vp_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/broker/vp_xml_socket_broker_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## message broker sample2 ##
* show how message broker node works.
* serialize vp_frame_target (vp_sub_target) objects to xml and broke to socket via udp.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/plate.mp4");
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto trt_vehicle_plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector>("vehicle_plate_detector", "./vp_data/models/trt/plate/det_v8.5.trt", "./vp_data/models/trt/plate/rec_v8.5.trt");
auto xml_socket_broker_0 = std::make_shared<vp_nodes::vp_xml_socket_broker_node>("xml_socket_broker_0", "192.168.77.68", 6666);
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node_v2>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0, true, vp_objects::vp_size{640, 360});
// construct pipeline
trt_vehicle_detector->attach_to({file_src_0});
trt_vehicle_plate_detector->attach_to({trt_vehicle_detector});
xml_socket_broker_0->attach_to({trt_vehicle_plate_detector});
osd_0->attach_to({xml_socket_broker_0});
screen_des_0->attach_to({osd_0});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_mllm_analyser_node.h"
#include "../nodes/osd/vp_mllm_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## mllm_analyse_sample ##
* image(frame) analyse based on Multimodal Large Language Model(from Ollama).
* read images from disk and analyse the image using MLLM using the prepared prompt.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_file_src_0", 0, "./vp_data/test_images/llm/writing/%d.jpg", 2, 0.5);
auto understanding_prompt = "一句话描述图片内容，要求包含：\n"
"1. 对天气的描述\n"
"2. 对环境的描述\n"
"3. 对位置的描述（如果可以从图片上的文字信息得出）\n"
"4. 字数不超过50字"
"你的输出结果是：";
auto writing_prompt = "根据图片写一段故事，要求包含：\n"
"1. 完整的故事结构\n"
"2. 故事内容要包含时间、地点、人物等元素"
"3. 字数不超过50字"
"你的输出结果是：";
auto mllm_analyser_0 = std::make_shared<vp_nodes::vp_mllm_analyser_node>("mllm_analyser_0", // node name
"minicpm-v:8b", // mllm model name (support image as input)
writing_prompt, // prompt
"http://192.168.77.219:11434", // api base url
"", // api key (not required by Ollama)
llmlib::LLMBackendType::Ollama); // backend type, make sure Ollama is installed at 192.168.77.219
auto mllm_osd_0 = std::make_shared<vp_nodes::vp_mllm_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
mllm_analyser_0->attach_to({image_src_0});
mllm_osd_0->attach_to({mllm_analyser_0});
screen_des_0->attach_to({mllm_osd_0});
image_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
image_src_0->detach_recursively();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_mllm_analyser_node.h"
#include "../nodes/osd/vp_mllm_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## mllm_analyse_sample_openai ##
* image(frame) analyse based on Multimodal Large Language Model(from aliyun or other OpenAI-compatible api services).
* read images from disk and analyse the image using MLLM using the prepared prompt.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_file_src_0", 0, "./vp_data/test_images/llm/understanding/%d.jpg", 2, 0.5);
auto writing_prompt = "给图片打标签，要求包含：\n"
"1. 先仔细观察图片内容，为图片赋予适合的标签\n"
"2. 给出的标签最多不超过5个\n"
"3. 输出按以下格式：\n"
"通过仔细观察图片，可以为图片赋予这些标签：['标签1', '标签2', '标签3']。";
auto mllm_analyser_0 = std::make_shared<vp_nodes::vp_mllm_analyser_node>("mllm_analyser_0", // node name
"qwen-vl-max", // mllm model name (from aliyun, support image as input)
writing_prompt, // prompt
"https://dashscope.aliyuncs.com/compatible-mode/v1", // api base url
"sk-XXX", // api key (from aliyun)
llmlib::LLMBackendType::OpenAI); // backend type
auto mllm_osd_0 = std::make_shared<vp_nodes::vp_mllm_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
mllm_analyser_0->attach_to({image_src_0});
mllm_osd_0->attach_to({mllm_analyser_0});
screen_des_0->attach_to({mllm_osd_0});
image_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
image_src_0->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/infers/vp_classifier_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## multi detectors and classifiers sample ##
* show multi infer nodes work together.
* 1 detector and 2 classifiers applied on primary class ids(1/2/3).
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_stop.mp4", 0.6);
/* primary detector */
// labels for detector model
// 0 - person
// 1 - car
// 2 - bus
// 3 - truck
// 4 - 2wheel
auto primary_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("primary_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", 416, 416, 1);
/* secondary classifier 1, applied to car(1)/bus(2)/truck(3) only */
auto _1st_classifier = std::make_shared<vp_nodes::vp_classifier_node>("1st_classifier", "./vp_data/models/det_cls/vehicle/resnet18-batch=N-type_view_0322_nhwc.onnx", "", "./vp_data/models/det_cls/vehicle/vehicle_types.txt", 224, 224, 1, std::vector<int>{1, 2, 3}, 20, 20, 10, false, 1, cv::Scalar(), cv::Scalar(), true, true);
/* secondary classifier 2, applied to car(1)/bus(2)/truck(3) only */
auto _2nd_classifier = std::make_shared<vp_nodes::vp_classifier_node>("2nd_classifier", "./vp_data/models/det_cls/vehicle/resnet18-batch=N-color_view_0322_nhwc.onnx", "", "./vp_data/models/det_cls/vehicle/vehicle_colors.txt", 224, 224, 1, std::vector<int>{1, 2, 3}, 20, 20, 10, false, 1, cv::Scalar(), cv::Scalar(), true, true);
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_o", 0);
// construct pipeline
primary_detector->attach_to({file_src_0});
_1st_classifier->attach_to({primary_detector});
_2nd_classifier->attach_to({_1st_classifier});
osd_0->attach_to({_2nd_classifier});
screen_des_0->attach_to({osd_0});
// start
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtsp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## multi_detectors_sample ##
* detect obstacles AND vehicles using yolo on road.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/unclear.mp4", 0.5);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/roadblock.mp4", 0.6);
auto obstacle_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("obstacle_detector", "./vp_data/models/det_cls/obstacles_yolov5s.onnx", "", "./vp_data/models/det_cls/obstacles_2classes.txt", 640, 640);
// MUST set class_id_offset for the 2nd detector which is equal with total classes of the 1st detectors
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", 416, 416, 1, 2);
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split_by_channel", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto srceen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
obstacle_detector->attach_to({file_src_0, file_src_1});
vehicle_detector->attach_to({obstacle_detector});
osd->attach_to({vehicle_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
srceen_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_type_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_feature_encoder.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## multi_trt_infer_nodes_sample ##
* detect/classify/encoding on vehicle object using tensorrt
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_0", 0, "./vp_data/test_images/vehicle/%d.jpg");
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto trt_vehicle_color_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("trt_color_cls", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto trt_vehicle_type_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_type_classifier>("trt_type_cls", "./vp_data/models/trt/vehicle/vehicle_type_v8.5.trt", std::vector<int>{0, 1, 2});
auto trt_vehicle_feature_encoder = std::make_shared<vp_nodes::vp_trt_vehicle_feature_encoder>("trt_encoder", "./vp_data/models/trt/vehicle/vehicle_embedding_v8.5.trt", std::vector<int>{0, 1, 2});
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
trt_vehicle_detector->attach_to({image_src_0});
trt_vehicle_color_classifier->attach_to({trt_vehicle_detector});
trt_vehicle_type_classifier->attach_to({trt_vehicle_color_classifier});
trt_vehicle_feature_encoder->attach_to({trt_vehicle_type_classifier});
osd_0->attach_to({trt_vehicle_feature_encoder});
screen_des_0->attach_to({osd_0});
// start pipeline
image_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({image_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## nv_hard_codec_sample ##
* use hardware-based `nvv4l2decoder`/`nvv4l2h264enc` gstreamer plugins (come from DeepStream 4.0+) to decode/encode video stream, which would occupy NVIDIA GPUs.
* run `nvidia-smi -a` command to watch the Utilization of GPU/Decode/Encode .
*
* for more information: https://github.com/sherlockchou86/video_pipe_c/blob/master/doc/env.md#about-hardware-acceleration
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6, true, "nvv4l2decoder ! nvvideoconvert");
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000", vp_objects::vp_size(), 1024 * 4000, true, "nvvideoconvert ! nvv4l2h264enc");
// construct pipeline
yunet_face_detector_0->attach_to({file_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
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();
/*
cv::VideoCapture cap("filesrc location=/windows2/zhzhi/vp_data/test_video/face.mp4 ! qtdemux ! h264parse ! nvv4l2decoder ! nvvideoconvert ! appsink");
cv::Mat frame;
cap.read(frame);
return 0;
*/
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtsp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## obstacle_detect_sample ##
* detect obstacles using yolo on road.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/unclear.mp4", 0.5);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/roadblock.mp4", 0.5);
auto yolo_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("obstacle_detector", "./vp_data/models/det_cls/obstacles_yolov5s.onnx", "", "./vp_data/models/det_cls/obstacles_2classes.txt", 640, 640);
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split_by_channel", true);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto srceen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
yolo_detector->attach_to({file_src_0, file_src_1});
osd->attach_to({yolo_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
srceen_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_openpose_detector_node.h"
#include "../nodes/osd/vp_pose_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## openpose sample ##
* pose estimation by OpenPose network.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/pose.mp4");
auto openpose_detector = std::make_shared<vp_nodes::vp_openpose_detector_node>("openpose_detector", "./vp_data/models/openpose/pose/body_25_pose_iter_584000.caffemodel", "./vp_data/models/openpose/pose/body_25_pose_deploy.prototxt", "", 368, 368, 1, 0, 0.1, vp_objects::vp_pose_type::body_25);
auto pose_osd_0 = std::make_shared<vp_nodes::vp_pose_osd_node>("pose_osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
openpose_detector->attach_to({file_src_0});
pose_osd_0->attach_to({openpose_detector});
screen_des_0->attach_to({pose_osd_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_ppocr_text_detector_node.h"
#include "../nodes/osd/vp_text_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
#include "../nodes/vp_file_des_node.h"
/*
* ## paddle infer sample ##
* ocr based on paddle (install paddle_inference first!)
* 1 video input and 2 outputs (screen, rtmp)
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/ocr.mp4", 0.4);
auto ppocr_text_detector = std::make_shared<vp_nodes::vp_ppocr_text_detector_node>("ppocr_text_detector", "./vp_data/models/text/ppocr/ch_PP-OCRv3_det_infer","./vp_data/models/text/ppocr/ch_ppocr_mobile_v2.0_cls_infer","./vp_data/models/text/ppocr/ch_PP-OCRv3_rec_infer","./vp_data/models/text/ppocr/ppocr_keys_v1.txt");
auto osd_0 = std::make_shared<vp_nodes::vp_text_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0, true);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000");
// construct pipeline
ppocr_text_detector->attach_to({file_src_0});
osd_0->attach_to({ppocr_text_detector});
// split into 2 sub branches automatically
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_plate_detector_v2.h"
#include "../nodes/osd/vp_plate_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## plate recognize sample ##
* detect and recognize plate in the whole frame
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_0", 0, "./vp_data/test_images/plates/%d.jpg", 1);
auto plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector_v2>("plate_detector", "./vp_data/models/trt/plate/det_v8.5.trt", "./vp_data/models/trt/plate/rec_v8.5.trt");
auto osd_0 = std::make_shared<vp_nodes::vp_plate_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
plate_detector->attach_to({image_src_0});
osd_0->attach_to({plate_detector});
screen_des_0->attach_to({osd_0});
// start pipeline
image_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({image_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/record/vp_record_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## record sample ##
* show how to use vp_record_node to record image and video.
* NOTE:
* the recording signal in this demo is triggered by users outside pipe (via calling vp_src_node::record_video_manually or vp_src_node::record_image_manually)
* in product situations, recording signal is triggered inside pipe automatically.
*/
int main() {
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_SET_LOG_TO_CONSOLE(false); // need interact on console
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face.mp4", 0.6);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/face2.mp4", 0.6);
auto yunet_face_detector = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto track = std::make_shared<vp_nodes::vp_sort_track_node>("track", vp_nodes::vp_track_for::FACE);
auto osd = std::make_shared<vp_nodes::vp_face_osd_node>("osd");
auto recorder = std::make_shared<vp_nodes::vp_record_node>("recorder", "./record", "./record");
auto split = std::make_shared<vp_nodes::vp_split_node>("split", true); // split by channel index
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// construct pipeline
yunet_face_detector->attach_to({file_src_0, file_src_1});
sface_face_encoder->attach_to({yunet_face_detector});
track->attach_to({sface_face_encoder});
osd->attach_to({track});
recorder->attach_to({osd});
split->attach_to({recorder});
// split by vp_split_node
screen_des_0->attach_to({split});
screen_des_1->attach_to({split});
/*
* set hookers for vp_record_node when task compeleted
*/
// define hooker
auto record_hooker = [](int channel, vp_nodes::vp_record_info record_info) {
auto record_type = record_info.record_type == vp_nodes::vp_record_type::IMAGE ? "image" : "video";
std::cout << "channel:[" << channel << "] [" << record_type << "]" << " record task completed! full path: " << record_info.full_record_path << std::endl;
};
recorder->set_image_record_complete_hooker(record_hooker);
recorder->set_video_record_complete_hooker(record_hooker);
// start channels
file_src_0->start();
file_src_1->start();
// for debug purpose
std::vector<std::shared_ptr<vp_nodes::vp_node>> src_nodes_in_pipe{file_src_0, file_src_1};
vp_utils::vp_analysis_board board(src_nodes_in_pipe);
board.display(1, false); // no block
/* interact from console */
/* no except check */
std::string input;
std::getline(std::cin, input);
// input format: `image channel` or `video channel`, like `video 0` means start recording video at channel 0
auto inputs = vp_utils::string_split(input, ' ');
while (inputs[0] != "quit") {
// no except check
auto command = inputs[0];
auto index = std::stoi(inputs[1]);
auto src_by_channel = std::dynamic_pointer_cast<vp_nodes::vp_src_node>(src_nodes_in_pipe[index]);
if (command == "video") {
src_by_channel->record_video_manually(true); // debug api
// or
// src_by_channel->record_video_manually(true, 5);
// src_by_channel->record_video_manually(false, 20);
}
else if (command == "image") {
src_by_channel->record_image_manually(); // debug api
// or
// src_by_channel->record_image_manually(true);
}
else {
std::cout << "invalid command!" << std::endl;
}
std::getline(std::cin, input);
inputs = vp_utils::string_split(input, ' ');
if (inputs.size() != 2) {
std::cout << "invalid input!" << std::endl;
break;
}
}
std::cout << "record sample exits..." << std::endl;
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_rtmp_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## rtmp_src_sample ##
* 1 rtmp video input, 1 infer task, and 1 output.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto rtmp_src_0 = std::make_shared<vp_nodes::vp_rtmp_src_node>("rtmp_src_0", 0, "rtmp://192.168.77.196/live/1000", 0.6);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto track_0 = std::make_shared<vp_nodes::vp_sort_track_node>("track_0");
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.196/live/2000", vp_objects::vp_size{1280, 720}, 1024 * 2);
// construct pipeline
trt_vehicle_detector->attach_to({rtmp_src_0});
track_0->attach_to({trt_vehicle_detector});
osd_0->attach_to({track_0});
rtmp_des_0->attach_to({osd_0});
rtmp_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({rtmp_src_0});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
rtmp_src_0->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtsp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## rtsp_des_sample ##
* show how vp_rtsp_des_node works, push video stream via rtsp, no specialized rtsp server needed.
* visit `rtsp://server-ip:rtsp_port/rtsp_name directly.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.5);
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/vehicle_stop.mp4", 0.5);
auto yolo_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("yolo_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 osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto split = std::make_shared<vp_nodes::vp_split_node>("split_by_channel", true);
//auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtsp_des_0 = std::make_shared<vp_nodes::vp_rtsp_des_node>("rtsp_des_0", 0, 8000, "rtsp_0");
//auto srceen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
auto rtsp_des_1 = std::make_shared<vp_nodes::vp_rtsp_des_node>("rtsp_des_1", 1, 8000, "rtsp_1");
// construct pipeline
yolo_detector->attach_to({file_src_0, file_src_1});
osd->attach_to({yolo_detector});
split->attach_to({osd});
rtsp_des_0->attach_to({split});
rtsp_des_1->attach_to({split});
file_src_0->start();
file_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, file_src_1});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
file_src_0->detach_recursively();
file_src_1->detach_recursively();
}

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#include "../nodes/vp_rtsp_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## rtsp_src_sample ##
* 1 rtsp video input, 1 infer task, and 1 output.
* support switching/restarting input rtsp stream.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto rtsp_src_0 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_0", 0, "rtsp://192.168.77.213/live/mainstream", 0.6);
auto yunet_face_detector_0 = std::make_shared<vp_nodes::vp_yunet_face_detector_node>("yunet_face_detector_0", "./vp_data/models/face/face_detection_yunet_2022mar.onnx");
auto sface_face_encoder_0 = std::make_shared<vp_nodes::vp_sface_feature_encoder_node>("sface_face_encoder_0", "./vp_data/models/face/face_recognition_sface_2021dec.onnx");
auto osd_0 = std::make_shared<vp_nodes::vp_face_osd_node_v2>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yunet_face_detector_0->attach_to({rtsp_src_0});
sface_face_encoder_0->attach_to({yunet_face_detector_0});
osd_0->attach_to({sface_face_encoder_0});
screen_des_0->attach_to({osd_0});
rtsp_src_0->start();
/* manually switching/restarting RTSP video sources, where the video sources have different widths, heights, and frame rates.
continuously print width, height, fps. */
while (true) {
auto width = rtsp_src_0->get_original_width();
auto height = rtsp_src_0->get_original_height();
auto fps = rtsp_src_0->get_original_fps();
std::cout << "original_width: " << width << "original_height: " << height << "original_fps: " << fps << std::endl;
this_thread::sleep_for(std::chrono::milliseconds(1000));
}
rtsp_src_0->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/vp_rtsp_src_node.h"
#include "../nodes/infers/vp_yolo_detector_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## skip_sample ##
* 2 inputs , and skip 2 frames every 3 frames for the 2nd channel.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.5);
auto rtsp_src_1 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_1", 1, "rtsp://admin:admin12345@192.168.3.157", 0.4, "avdec_h264", 2); // skip 2 frames every 3 frames
auto yolo_detector = std::make_shared<vp_nodes::vp_yolo_detector_node>("yolo_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 split = std::make_shared<vp_nodes::vp_split_node>("split", true);
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_1 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 1, "rtmp://192.168.77.60/live/10000");
// construct pipeline
yolo_detector->attach_to({file_src_0, rtsp_src_1});
osd->attach_to({yolo_detector});
split->attach_to({osd});
screen_des_0->attach_to({split});
rtmp_des_1->attach_to({split});
// start channels
file_src_0->start();
rtsp_src_1->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, rtsp_src_1});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/vp_rtsp_src_node.h"
#include "../nodes/vp_udp_src_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_fake_des_node.h"
#include "../nodes/vp_file_des_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_split_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## src des sample ##
* show how src nodes and des nodes work
* 3 (file, rtsp, udp) input and merge into 1 infer task, then resume to 3 branches for outputs (screen, rtmp, fake)
*/
int main() {
// log config
// ...
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.5);
auto rtsp_src_1 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_1", 1, "rtsp://admin:admin12345@192.168.77.203", 0.4);
auto udp_src_2 = std::make_shared<vp_nodes::vp_udp_src_node>("udp_src_2", 2, 6000, 0.3);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_vehicle_detector","./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto split = std::make_shared<vp_nodes::vp_split_node>("", true);
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto osd_1 = std::make_shared<vp_nodes::vp_osd_node>("osd_1", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto osd_2 = std::make_shared<vp_nodes::vp_osd_node>("osd_2", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto rtmp_des_1 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 1, "rtmp://192.168.77.60/live/10000");
auto fake_des_2 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_2", 2);
// construct pipeline
// auto merge
trt_vehicle_detector->attach_to({file_src_0, rtsp_src_1, udp_src_2});
split->attach_to({trt_vehicle_detector});
// resume to 3 branches
osd_0->attach_to({split});
osd_1->attach_to({split});
osd_2->attach_to({split});
screen_des_0->attach_to({osd_0});
rtmp_des_1->attach_to({osd_1});
fake_des_2->attach_to({osd_2});
// start channels
file_src_0->start();
rtsp_src_1->start();
udp_src_2->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0, rtsp_src_1, udp_src_2});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_plate_detector.h"
#include "../nodes/osd/vp_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
#include "../nodes/vp_file_des_node.h"
/*
* ## trt infer sample ##
* vehicle and plate detector based on tensorrt (install tensorrt first!)
* 1 video input and 3 outputs (screen, file, rtmp)
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/plate.mp4");
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto trt_vehicle_plate_detector = std::make_shared<vp_nodes::vp_trt_vehicle_plate_detector>("vehicle_plate_detector", "./vp_data/models/trt/plate/det_v8.5.trt", "./vp_data/models/trt/plate/rec_v8.5.trt");
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node_v2>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0, true, vp_objects::vp_size{640, 360});
auto rtmp_des_0 = std::make_shared<vp_nodes::vp_rtmp_des_node>("rtmp_des_0", 0, "rtmp://192.168.77.60/live/10000", vp_objects::vp_size{1280, 720});
auto file_des_0 = std::make_shared<vp_nodes::vp_file_des_node>("file_des_0", 0, ".");
// construct pipeline
trt_vehicle_detector->attach_to({file_src_0});
trt_vehicle_plate_detector->attach_to({trt_vehicle_detector});
osd_0->attach_to({trt_vehicle_plate_detector});
// split into 3 sub branches automatically
screen_des_0->attach_to({osd_0});
rtmp_des_0->attach_to({osd_0});
file_des_0->attach_to({osd_0});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_yolov8_detector.h"
#include "../nodes/infers/vp_trt_yolov8_seg_detector.h"
#include "../nodes/infers/vp_trt_yolov8_pose_detector.h"
#include "../nodes/osd/vp_osd_node_v3.h"
#include "../nodes/osd/vp_pose_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## trt yolov8 sample ##
* detection/segmentation/pose_estimation using yolov8 based on tensorrt
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes for 1st pipeline
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/face2.mp4");
auto yolo8_detector = std::make_shared<vp_nodes::vp_trt_yolov8_detector>("yolo8_detector", "./vp_data/models/trt/others/yolov8s_v8.5.engine", "./vp_data/models/coco_80classes.txt");
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node_v3>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// create nodes for 2nd pipeline
auto file_src_1 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_1", 1, "./vp_data/test_video/face2.mp4");
auto yolo8_seg_detector = std::make_shared<vp_nodes::vp_trt_yolov8_seg_detector>("yolo8_seg_detector", "./vp_data/models/trt/others/yolov8s-seg_v8.5.engine", "./vp_data/models/coco_80classes.txt");
auto osd_1 = std::make_shared<vp_nodes::vp_osd_node_v3>("osd_1", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_1 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_1", 1);
// create nodes for 3rd pipeline
auto file_src_2 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_2", 2, "./vp_data/test_video/face2.mp4");
auto yolo8_pose_detector = std::make_shared<vp_nodes::vp_trt_yolov8_pose_detector>("yolo8_pose_detector", "./vp_data/models/trt/others/yolov8s-pose_v8.5.engine");
auto osd_2 = std::make_shared<vp_nodes::vp_pose_osd_node>("osd_2");
auto screen_des_2 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_2", 2);
// construct 1st pipeline
yolo8_detector->attach_to({file_src_0});
osd_0->attach_to({yolo8_detector});
screen_des_0->attach_to({osd_0});
// construct 2nd pipeline
yolo8_seg_detector->attach_to({file_src_1});
osd_1->attach_to({yolo8_seg_detector});
screen_des_1->attach_to({osd_1});
// construct 3rd pipeline
yolo8_pose_detector->attach_to({file_src_2});
osd_2->attach_to({yolo8_pose_detector});
screen_des_2->attach_to({osd_2});
// start pipelines
file_src_0->start();
file_src_1->start();
file_src_2->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0, file_src_1, file_src_2});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_yolov8_detector.h"
#include "../nodes/infers/vp_trt_yolov8_classifier.h"
#include "../nodes/osd/vp_osd_node_v3.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## trt yolov8 sample2 ##
* detection/classification using yolov8 based on tensorrt
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/mask_rcnn.mp4");
auto yolo8_detector = std::make_shared<vp_nodes::vp_trt_yolov8_detector>("yolo8_detector", "./vp_data/models/trt/others/yolov8s_v8.5.engine", "./vp_data/models/coco_80classes.txt");
auto yolo8_classifier = std::make_shared<vp_nodes::vp_trt_yolov8_classifier>("yolo8_classifier", "./vp_data/models/trt/others/yolov8s-cls_v8.5.engine", "./vp_data/models/imagenet_1000labels1.txt");
auto osd = std::make_shared<vp_nodes::vp_osd_node_v3>("osd", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
yolo8_detector->attach_to({file_src_0});
yolo8_classifier->attach_to({yolo8_detector});
osd->attach_to({yolo8_classifier});
screen_des_0->attach_to({osd});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_scanner.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## vehicle_body_scan_sample ##
* detect wheels and vehicle type based on side view of vehicle
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_0", 0, "./vp_data/test_images/body/%d.jpg");
auto vehicle_scanner = std::make_shared<vp_nodes::vp_trt_vehicle_scanner>("vehicle_scanner", "./vp_data/models/trt/vehicle/vehicle_scan_v8.5.trt");
auto osd = std::make_shared<vp_nodes::vp_osd_node>("osd");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
vehicle_scanner->attach_to({image_src_0});
osd->attach_to({vehicle_scanner});
screen_des_0->attach_to({osd});
image_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0});
board.display();
}

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#include "../nodes/vp_image_src_node.h"
#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/infers/vp_trt_vehicle_color_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_type_classifier.h"
#include "../nodes/infers/vp_trt_vehicle_feature_encoder.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/osd/vp_cluster_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_fake_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## vehicle_cluster_based_on_classify_encoding_sample ##
* vehicle cluster based on classify(categories) and encoding(features), pipeline would display 3 windows (cluster by t-SNE, cluster by categories, detect osd result)
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_src_0", 0, "./vp_data/test_images/vehicle/%d.jpg");
//auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./test_video/22.mp4");
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("trt_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto trt_vehicle_color_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_color_classifier>("trt_color_cls", "./vp_data/models/trt/vehicle/vehicle_color_v8.5.trt", std::vector<int>{0, 1, 2});
auto trt_vehicle_type_classifier = std::make_shared<vp_nodes::vp_trt_vehicle_type_classifier>("trt_type_cls", "./vp_data/models/trt/vehicle/vehicle_type_v8.5.trt", std::vector<int>{0, 1, 2});
auto trt_vehicle_feature_encoder = std::make_shared<vp_nodes::vp_trt_vehicle_feature_encoder>("trt_encoder", "./vp_data/models/trt/vehicle/vehicle_embedding_v8.5.trt", std::vector<int>{0, 1, 2});
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
auto cluster_0 = std::make_shared<vp_nodes::vp_cluster_node>("cluster_0", true, std::vector<std::string>{"red", "white", "black", "blue", "yellow", "bus", "small_truck", "van", "tanker"}, 1000);
auto fake_des_0 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_0", 0);
// construct pipeline
trt_vehicle_detector->attach_to({image_src_0});
//trt_vehicle_detector->attach_to({file_src_0});
trt_vehicle_color_classifier->attach_to({trt_vehicle_detector});
trt_vehicle_type_classifier->attach_to({trt_vehicle_color_classifier});
trt_vehicle_feature_encoder->attach_to({trt_vehicle_type_classifier});
// split into 2 branches automatically
/* branch of osd -> screen des*/
osd_0->attach_to({trt_vehicle_feature_encoder});
screen_des_0->attach_to({osd_0});
/* branch of cluster -> fake des*/
cluster_0->attach_to({trt_vehicle_feature_encoder});
fake_des_0->attach_to({cluster_0}); // to keep pipeline complete
// start pipeline
image_src_0->start();
//file_src_0->start();
// visualize pipeline for debug
//vp_utils::vp_analysis_board board({file_src_0});
vp_utils::vp_analysis_board board({image_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_trt_vehicle_detector.h"
#include "../nodes/osd/vp_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/track/vp_sort_track_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_stop.mp4", 0.5);
auto trt_vehicle_detector = std::make_shared<vp_nodes::vp_trt_vehicle_detector>("vehicle_detector", "./vp_data/models/trt/vehicle/vehicle_v8.5.trt");
auto track_0 = std::make_shared<vp_nodes::vp_sort_track_node>("track_0");
auto osd_0 = std::make_shared<vp_nodes::vp_osd_node>("osd_0", "./vp_data/font/NotoSansCJKsc-Medium.otf");
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
trt_vehicle_detector->attach_to({file_src_0});
track_0->attach_to({trt_vehicle_detector});
osd_0->attach_to({track_0});
screen_des_0->attach_to({osd_0});
// start pipeline
file_src_0->start();
// visualize pipeline for debug
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/vp_image_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_restoration_node.h"
#include "../nodes/osd/vp_face_osd_node.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_file_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## video_restoration_sample ##
* enhance for any video/images, no training need before running.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_LOGGER_INIT();
// create nodes
auto image_src_0 = std::make_shared<vp_nodes::vp_image_src_node>("image_file_src_0", 0, "./vp_data/test_images/restoration/1/%d.jpg", 3);
auto restoration_node = std::make_shared<vp_nodes::vp_restoration_node>("restoration_node", "./vp_data/models/restoration/realesrgan-x4.onnx");
auto screen_des_0_ori = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_ori", 0, false);
auto screen_des_0_osd = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0_osd", 0);
// construct pipeline
restoration_node->attach_to({image_src_0});
screen_des_0_ori->attach_to({restoration_node});
screen_des_0_osd->attach_to({restoration_node});
// start pipeline
image_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({image_src_0});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
image_src_0->detach_recursively();
}

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#include "../utils/vp_utils.h"
#include "../utils/logger/vp_logger.h"
#include <iostream>
#include <chrono>
#include <thread>
/*
* ## sample for vp_logger ##
* show how vp_logger works
*/
int main() {
// config for log content
// VP_SET_LOG_INCLUDE_THREAD_ID(false);
// VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
// VP_SET_LOG_INCLUDE_LEVEL(false);
// config for output
// VP_SET_LOG_TO_CONSOLE(false);
// VP_SET_LOG_TO_FILE(false);
// config for log folder
VP_SET_LOG_DIR("./log");
// config log level
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::DEBUG);
// config for kafka, ignored automatically if not prepared for kafka
VP_SET_LOG_TO_KAFKA(true); // false by default if not set
VP_SET_LOG_KAFKA_SERVERS_AND_TOPIC("192.168.77.87:9092/vp_log");
// init
VP_LOGGER_INIT();
// 6 threads logging separately
auto func1 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_ERROR(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(2));
}
};
auto func2 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_DEBUG(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(13));
}
};
auto func3 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_INFO(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(4));
}
};
auto func4 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_WARN(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(10));
}
};
auto func5 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_ERROR(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(10));
}
};
auto func6 = []() {
while (true) {
/* code */
auto id = std::this_thread::get_id();
std::stringstream ss;
ss << std::hex << id;
auto thread_id = ss.str();
VP_INFO(vp_utils::string_format("thread id: %s", thread_id.c_str()));
std::this_thread::sleep_for(std::chrono::milliseconds(10));
}
};
std::thread t1(func1);
std::thread t2(func2);
std::thread t3(func3);
std::thread t4(func4);
std::thread t5(func5);
std::thread t6(func6);
t1.join();
t2.join();
t3.join();
t4.join();
t5.join();
t6.join();
std::getchar();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/vp_rtsp_src_node.h"
#include "../nodes/infers/vp_yunet_face_detector_node.h"
#include "../nodes/infers/vp_sface_feature_encoder_node.h"
#include "../nodes/osd/vp_face_osd_node_v2.h"
#include "../nodes/vp_screen_des_node.h"
#include "../nodes/vp_rtmp_des_node.h"
#include "../nodes/vp_fake_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## vp_test ##
* test anything for videopipe in this cpp.
*/
int main() {
VP_SET_LOG_INCLUDE_CODE_LOCATION(false);
VP_SET_LOG_INCLUDE_THREAD_ID(false);
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto rtsp_src_0 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_0", 0, "rtsp://192.168.77.193:8554/stream/main", 1, "avdec_h264", 1);
auto fake_des_0 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_0", 0);
auto rtsp_src_1 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_1", 1, "rtsp://192.168.77.193:8554/stream/main", 1, "avdec_h264", 1);
auto fake_des_1 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_1", 1);
auto rtsp_src_2 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_2", 2, "rtsp://192.168.77.193:8554/stream/main", 1, "avdec_h264", 1);
auto fake_des_2 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_2", 2);
auto rtsp_src_3 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_3", 3, "rtsp://192.168.77.193:8554/stream/main", 1, "avdec_h264", 1);
auto fake_des_3 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_3", 3);
auto rtsp_src_4 = std::make_shared<vp_nodes::vp_rtsp_src_node>("rtsp_src_4", 4, "rtsp://192.168.77.193:8554/stream/main", 1, "avdec_h264", 1);
auto fake_des_4 = std::make_shared<vp_nodes::vp_fake_des_node>("fake_des_4", 4);
// construct pipeline
fake_des_0->attach_to({rtsp_src_0});
fake_des_1->attach_to({rtsp_src_1});
fake_des_2->attach_to({rtsp_src_2});
fake_des_3->attach_to({rtsp_src_3});
fake_des_4->attach_to({rtsp_src_4});
// start
rtsp_src_0->start();
rtsp_src_1->start();
rtsp_src_2->start();
rtsp_src_3->start();
rtsp_src_4->start();
// for debug purpose
vp_utils::vp_analysis_board board({rtsp_src_0, rtsp_src_1, rtsp_src_2, rtsp_src_3, rtsp_src_4});
board.display(1, false);
std::string wait;
std::getline(std::cin, wait);
rtsp_src_0->detach_recursively();
rtsp_src_1->detach_recursively();
rtsp_src_2->detach_recursively();
rtsp_src_3->detach_recursively();
rtsp_src_4->detach_recursively();
}

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#include "../nodes/vp_file_src_node.h"
#include "../nodes/infers/vp_yolo5_seg_node.h"
#include "../nodes/osd/vp_osd_node_v3.h"
#include "../nodes/vp_screen_des_node.h"
#include "../utils/analysis_board/vp_analysis_board.h"
/*
* ## yolov5-seg sample ##
* driving area segmentation(das) using yolov5-seg-v7.0.
*/
int main() {
VP_SET_LOG_LEVEL(vp_utils::vp_log_level::INFO);
VP_LOGGER_INIT();
// create nodes
auto file_src_0 = std::make_shared<vp_nodes::vp_file_src_node>("file_src_0", 0, "./vp_data/test_video/vehicle_count.mp4", 0.6);
// 2 classes using yolov5-seg
auto das_detector = std::make_shared<vp_nodes::vp_yolo5_seg_node>("das_detector", "./vp_data/models/lane/das.onnx", "./vp_data/models/lane/das_2classes.txt");
auto osd_v3_0 = std::make_shared<vp_nodes::vp_osd_node_v3>("osd_v3_0", "./vp_data/font/NotoSansCJKsc-Medium.otf", false);
auto screen_des_0 = std::make_shared<vp_nodes::vp_screen_des_node>("screen_des_0", 0);
// construct pipeline
das_detector->attach_to({file_src_0});
osd_v3_0->attach_to({das_detector});
screen_des_0->attach_to({osd_v3_0});
file_src_0->start();
// for debug purpose
vp_utils::vp_analysis_board board({file_src_0});
board.display();
}