-n, --num: Number of classes the model trained on
-m, --model: Model type (choices: yolo_nas_s, yolo_nas_m, yolo_nas_l)
-w, --weight: path to trained model weight, for COCO model: coco-s, --source: video path/cam-id/RTSP
-c, --conf: model prediction confidence (0<conf<1)
--save: to save video
--hide: hide video window
Example:
# For COCO YOLO-NAS Model
python3 inference.py --model yolo_nas_s --weight coco --source 0 # Camera
python3 inference.py --model yolo_nas_m --weight coco --source /test/video.mp4 --conf 0.66 # video
added yolonas coco model inference
Args
-n
,--num
: Number of classes the model trained on-m
,--model
: Model type (choices:yolo_nas_s
,yolo_nas_m
,yolo_nas_l
)-w
,--weight
: path to trained model weight, for COCO model:coco
-s
,--source
: video path/cam-id/RTSP-c
,--conf
: model prediction confidence (0<conf<1)--save
: to save video--hide
: hide video windowExample: