ultralytics/docs/en/macros/validation-args.md

Argument	Type	Default	Description
data	str	None	Specifies the path to the dataset configuration file (e.g., coco8.yaml). This file includes paths to validation data, class names, and number of classes.
imgsz	int	640	Defines the size of input images. All images are resized to this dimension before processing.
batch	int	16	Sets the number of images per batch. Use -1 for AutoBatch, which automatically adjusts based on GPU memory availability.
save_json	bool	False	If True, saves the results to a JSON file for further analysis or integration with other tools.
save_hybrid	bool	False	If True, saves a hybrid version of labels that combines original annotations with additional model predictions.
conf	float	0.001	Sets the minimum confidence threshold for detections. Detections with confidence below this threshold are discarded.
iou	float	0.6	Sets the Intersection Over Union (IoU) threshold for Non-Maximum Suppression (NMS). Helps in reducing duplicate detections.
max_det	int	300	Limits the maximum number of detections per image. Useful in dense scenes to prevent excessive detections.
half	bool	True	Enables half-precision (FP16) computation, reducing memory usage and potentially increasing speed with minimal impact on accuracy.
device	str	None	Specifies the device for validation (cpu, cuda:0, etc.). Allows flexibility in utilizing CPU or GPU resources.
dnn	bool	False	If True, uses the OpenCV DNN module for ONNX model inference, offering an alternative to PyTorch inference methods.
plots	bool	False	When set to True, generates and saves plots of predictions versus ground truth for visual evaluation of the model's performance.
rect	bool	False	If True, uses rectangular inference for batching, reducing padding and potentially increasing speed and efficiency.
split	str	val	Determines the dataset split to use for validation (val, test, or train). Allows flexibility in choosing the data segment for performance evaluation.