VideoPipe/SAMPLES.md

## Samples Video（视频演示） ##
### Face Swap（AI换脸） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/aa1162f3-2f61-4ac7-8add-12d9f8b7ab23

### Vehicle CLustering（车辆分类聚合） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/867b981b-5d8c-4ee3-9831-9c755b520ad6

### Search Vehicle by Image（以图搜车） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/a0ae5422-904b-4ad1-8201-3e1a07477882

### Stop Detecting（停车检测） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/dd518798-6345-4121-a4d5-ad5bde18e3f3

### Vehicle Behavior Analysis（车辆行为分析） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/3c115d3b-45e4-4df9-8459-bfadca974e4c

### Jam Detecting（拥堵检测） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/b31612ae-6b44-4cbd-8439-610bd71834d5

### Face Recognition（人脸识别） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/7958c5e3-4e6e-453b-bde9-663779d960cb

### Dynamical Pipeline（动态管道） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/7fe3e45d-e528-4315-ba4f-21c3f11163e3

### License Plate Recognition（车牌识别相机） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/f680dccf-92c3-41eb-a472-7f0e27c28257

### Parallel Task & Synchronization（并行任务、数据同步） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/28a71383-8864-4a25-8da3-27922f0b5baf

### Math Review（口算检查） ###
https://github.com/sherlockchou86/video_pipe_c/assets/13251045/9c3c1a87-d9f7-4630-a541-96610d564f13


## Samples Screenshot（案例原型） ##

|id|sample|screenshot|
|--|--|--|
|1|1-1-1_sample|![](./doc//p10.png)|
|2|1-1-N_sample|![](./doc//p11.png)|
|3|1-N-N_sample|![](./doc//p12.png)|
|4|N-1-N_sample|![](./doc//p13.png)|
|5|N-N_sample|![](./doc//p14.png)|
|6|paddle_infer_sample|![](./doc//p15.png)|
|7|src_des_sample|![](./doc//p16.png)|
|8|trt_infer_sample|![](./doc//p17.png)|
|9|vp_logger_sample|-|
|10|face_tracking_sample|![](./doc//p18.png)|
|11|vehicle_tracking_sample|![](./doc//p22.png)|
|12|interaction with pipe sample|--|
|13|record_sample|--|
|14|message_broker_sample & message_broker_sample2|![](./doc//p21.png)|
|15|mask_rcnn_sample|![](./doc//p30.png)|
|16|openpose_sample|![](./doc//p31.png)|
|17|enet_seg_sample|![](./doc//p32.png)|
|18|multi detectors and classifiers sample|![](./doc//p33.png)|
|19|image_des_sample|![](./doc//p34.png)|
|20|image_src_sample|![](./doc//p35.png)|
|21|rtsp_des_sample|![](./doc//p36.png)|
|22|ba_crossline_sample|![](./doc//p37.png)|
|23|plate_recognize_sample|![](./doc//p38.png)|
|24|vehicle body scan sample|![](./doc/p40.png)|
|25|body scan and plate detect sample|![](./doc/p39.png)|
|26|app_src_sample|![](./doc/p41.png)|
|27|vehicle cluster based on classify encoding sample|![](./doc/p42.png)|
|28|ba_stop_sample|![](./doc/p49.png)|
|29|behaviour analysis|![](./doc/p48.png)|
|30|similiarity search|![](./doc/p44.png)![](./doc/p43.png)![](./doc/p45.png)|
|31|property and similiarity search|![](./doc/p46.png)![](./doc/p47.png)|
|32|ba_jam_sample|![](./doc/p50.png)|
|33|face recognize|![](./doc/p51.png)|
|34|license plate recognize(LPR) camera|![](./doc/p52.png)|
|35|math expression check|![](./doc/p53.png)|
|36|skip_sample|![](./doc/p54.png)|
|37|obstacle_detect_sample|![](./doc/p55.png)|
|38|firesmoke_detect_sample|![](./doc/p56.png)|
|39|face_swap_sample|![](./doc/p57.png)|
|40|video_restoration_sample|![](./doc/p58.png)|
|41|app_des_sample|![](./doc/p59.png)|
|42|app_src_des_sample|![](./doc/p60.png)|
|43|lane_detect_sample|![](./doc/p61.png)|
|44|frame_fusion_sample|![](./doc/p62.png)|
|45|1-N-1_sample|![](./doc/p65.png)|
|46|1-N-1_sample2|![](./doc/p64.png)|
|47|1-N-1_sample3|![](./doc/p63.png)|
|48|message_broker_kafka_sample|![](./doc/p66.png)|
|49|trt_yolov8_sample|![](./doc/p67.png)|
|50|trt_yolov8_sample2|![](./doc/p68.png)|
|51|mllm_analyse_sample|![](./doc/p69.png)|
|52|mllm_analyse_sample_openai|![](./doc/p70.png)|
|53|rtmp_src_sample|![](./doc/p71.png)|
|54|yolov5_seg_sample|![](./doc/p72.png)|