python3 exhibition_pipeline.py --help
usage: exhibition_pipeline.py [-h] [-wd CAMERA_WIDTH] [-ht CAMERA_HEIGHT]
[-numncs NUMBER_OF_NCS] [-vidfps FPS_OF_VIDEO]
[-skpfrm NUMBER_OF_FRAME_SKIP] [-o OUTPUT_FILE]
[-i INPUT_VIDEO_FILE]
[-r REIDENTIFICATION_ENABLED]
[-fa FACE_ANALYSIS_ENABLED]
optional arguments:
-h, --help show this help message and exit
-wd CAMERA_WIDTH, --width CAMERA_WIDTH
Width of the frames in the video stream. (USB Camera
Mode Only. Default=640)
-ht CAMERA_HEIGHT, --height CAMERA_HEIGHT
Height of the frames in the video stream. (USB Camera
Mode Only. Default=480)
-numncs NUMBER_OF_NCS, --numberofncs NUMBER_OF_NCS
Number of NCS. (Default=1)
-vidfps FPS_OF_VIDEO, --fpsofvideo FPS_OF_VIDEO
FPS of Video. (USB Camera Mode Only. Default=30)
-skpfrm NUMBER_OF_FRAME_SKIP, --skipframe NUMBER_OF_FRAME_SKIP
Number of frame skip. Default=0
-o OUTPUT_FILE, --output OUTPUT_FILE
Recording Output File
-i INPUT_VIDEO_FILE, --input INPUT_VIDEO_FILE
Input Video File
-r REIDENTIFICATION_ENABLED, --reidentification REIDENTIFICATION_ENABLED
Enable Pedestrian Re-Identification. Default=1 (1 -
Enabled; 0 - Disabled)
-fa FACE_ANALYSIS_ENABLED, --face-analysis FACE_ANALYSIS_ENABLED
Enable Face Analysis. Default=1 (1 - Enabled; 0 -
Disabled)
On each frame, person and face detection is performed, using face-person-detection-retail-0002 model Upon detecting people's bodies and faces, the body and face rectangles are passed to models to recognize age, gender, head pose, and emotions and perform person re-identification.