PaddleX Common Model Configuration File Parameter Explanation

Global

Parameter Name	Data Type	Description	Default Value
model	str	Specifies the model name	Model name specified in the YAML file
mode	str	Specifies the mode (check_dataset/train/evaluate/export/predict)	check_dataset
dataset_dir	str	Path to the dataset	Dataset path specified in the YAML file
device	str	Specifies the device to use	Device ID specified in the YAML file
output	str	Output path	"output"

CheckDataset

Parameter Name	Data Type	Description	Default Value
convert.enable	bool	Whether to convert the dataset format; Image classification, pedestrian attribute recognition, vehicle attribute recognition, document orientation classification, object detection, pedestrian detection, vehicle detection, face detection, anomaly detection, text detection, seal text detection, text recognition, table recognition, image rectification, and layout area detection do not support data format conversion; Image multi-label classification supports COCO format conversion; Image feature, semantic segmentation, and instance segmentation support LabelMe format conversion; Object detection and small object detection support VOC and LabelMe format conversion; Formula recognition supports PKL format conversion; Time series prediction, time series anomaly detection, and time series classification support xlsx and xls format conversion	False
convert.src_dataset_type	str	The source dataset format to be converted	null
split.enable	bool	Whether to re-split the dataset	False
split.train_percent	int	Sets the percentage of the training set, an integer between 0-100, ensuring the sum with val_percent is 100;	null
split.val_percent	int	Sets the percentage of the validation set, an integer between 0-100, ensuring the sum with train_percent is 100;	null
split.gallery_percent	int	Sets the percentage of gallery samples in the validation set, an integer between 0-100, ensuring the sum with train_percent and query_percent is 100; This parameter is only used in the image feature module	null
split.query_percent	int	Sets the percentage of query samples in the validation set, an integer between 0-100, ensuring the sum with train_percent and gallery_percent is 100; This parameter is only used in the image feature module	null

Train

Parameter Name	Data Type	Description	Default Value
num_classes	int	Number of classes in the dataset; If you need to train on a private dataset, you need to set this parameter; Image rectification, text detection, seal text detection, text recognition, formula recognition, table recognition, time series prediction, time series anomaly detection, and time series classification do not support this parameter	Number of classes specified in the YAML file
epochs_iters	int	Number of times the model repeats learning the training data	Number of iterations specified in the YAML file
batch_size	int	Training batch size	Training batch size specified in the YAML file
learning_rate	float	Initial learning rate	Initial learning rate specified in the YAML file
pretrain_weight_path	str	Pre-trained weight path	null
warmup_steps	int	Warm-up steps	Warm-up steps specified in the YAML file
resume_path	str	Model resume path after interruption	null
log_interval	int	Training log printing interval	Training log printing interval specified in the YAML file
eval_interval	int	Model evaluation interval	Model evaluation interval specified in the YAML file
save_interval	int	Model saving interval; not supported for anomaly detection, semantic segmentation, image rectification, time series forecasting, time series anomaly detection, and time series classification	Model saving interval specified in the YAML file

Evaluate

Parameter Name	Data Type	Description	Default Value
weight_path	str	Evaluation model path	Default local path from training output, when specified as None, indicates using official weights
log_interval	int	Evaluation log printing interval	Evaluation log printing interval specified in the YAML file

Export

Parameter Name	Data Type	Description	Default Value
weight_path	str	Dynamic graph weight path for exporting the model	Default local path from training output, when specified as None, indicates using official weights

Predict

Parameter Name	Data Type	Description	Default Value
batch_size	int	Prediction batch size	The prediction batch size specified in the YAML file
model_dir	str	Path to the prediction model	The default local inference model path produced by training. When specified as None, it indicates the use of official weights
input	str	Path to the prediction input	The prediction input path specified in the YAML file

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