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Deci-AI:master
deci-ai:feature/SG-761-yolo-nas
# Checkout the datasets at https://universe.roboflow.com/roboflow-100?ref=blog.roboflow.com # # `dataset_name` refers to the official name of the dataset. # You can find it in the url of the dataset: https://universe.roboflow.com/roboflow-100/digits-t2eg6 -> digits-t2eg6 # # Example: python -m super_gradients.train_from_recipe --config-name=roboflow_ppyoloe dataset_name=digits-t2eg6 defaults: - training_hyperparams: coco2017_ppyoloe_train_params - dataset_params: roboflow_detection_dataset_params - checkpoint_params: default_checkpoint_params - arch_params: ppyoloe_m_arch_params - _self_ - variable_setup dataset_name: ??? # Placeholder for the name of the dataset you want to use (e.g. "digits-t2eg6") dataset_params: dataset_name: ${dataset_name} num_classes: ${roboflow_dataset_num_classes:${dataset_name}} architecture: ppyoloe_m arch_params: num_classes: ${num_classes} train_dataloader: roboflow_train_yolox val_dataloader: roboflow_val_yolox load_checkpoint: False checkpoint_params: pretrained_weights: coco result_path: # By defaults saves results in checkpoints directory resume: False training_hyperparams: resume: ${resume} max_epochs: 100 mixed_precision: True criterion_params: num_classes: ${num_classes} phase_callbacks: - RoboflowResultCallback: dataset_name: ${dataset_name} output_path: ${result_path} loss: ppyoloe_loss: num_classes: ${num_classes} reg_max: ${arch_params.head.reg_max} valid_metrics_list: - DetectionMetrics: score_thres: 0.1 top_k_predictions: 300 num_cls: ${num_classes} normalize_targets: True post_prediction_callback: _target_: super_gradients.training.models.detection_models.pp_yolo_e.PPYoloEPostPredictionCallback score_threshold: 0.01 nms_top_k: 1000 max_predictions: 300 nms_threshold: 0.7 multi_gpu: DDP num_gpus: experiment_name: ${architecture}_roboflow_${dataset_name}
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