CLI Reference

All commands are available through the yolonas entry point.

Global options

Flag	Description
--version	Show version and exit
--verbose / -v	Enable debug logging
--quiet / -q	Suppress logging output

yolonas detect

Run object detection on images or video.

yolonas detect --source image.jpg --model yolo_nas_s --conf 0.25
yolonas detect --source images/ --output results/
yolonas detect --source video.mp4 --skip-frames 2

Option	Default	Description
--source	required	Image file, directory, or video path
--model	yolo_nas_s	Model variant (s/m/l)
--conf	0.25	Confidence threshold
--iou	0.7	NMS IoU threshold
--device	cuda	Device (cuda or cpu)
--output	results	Output directory
--input-size	640	Model input size
--skip-frames	0	Process every N-th frame (video)
--codec	mp4v	Video output codec

yolonas train

Train a YOLO-NAS model.

yolonas train --data /path/to/dataset --format yolo --epochs 100

Option	Default	Description
--data	required	Path to dataset root
--model	yolo_nas_s	Model variant
--format	yolo	Dataset format (yolo/coco)
--epochs	300	Training epochs
--batch-size	32	Batch size per GPU
--lr	2e-4	Learning rate
--device	cuda	Device
--output	runs/train	Output directory
--resume	None	Checkpoint to resume from
--input-size	640	Input size
--workers	8	DataLoader workers
--pretrained/--no-pretrained	True	Use COCO pretrained weights

yolonas export

Export model to ONNX or OpenVINO format.

yolonas export --model yolo_nas_s --format onnx
yolonas export --model yolo_nas_s --format openvino --target frigate

Option	Default	Description
--model	yolo_nas_s	Model variant
--format	onnx	Export format (onnx/openvino)
--output	auto	Output file path
--input-size	640	Model input size
--opset	17	ONNX opset version
--checkpoint	None	Custom checkpoint path
--target	generic	Export target (generic/frigate)

yolonas eval

Evaluate model on COCO dataset.

yolonas eval --data /path/to/coco --split val2017

Option	Default	Description
--data	required	Path to COCO dataset root
--model	yolo_nas_s	Model variant
--split	val2017	Split name
--batch-size	32	Batch size
--device	cuda	Device
--conf	0.001	Confidence threshold
--iou	0.65	NMS IoU threshold