| """ | |
| Smoker Detection with LoRA Fine-Tuning | |
| A parameter-efficient approach to binary image classification using | |
| Low-Rank Adaptation (LoRA) on pretrained ResNet34. | |
| """ | |
| from .model import ( | |
| LoRALayer, | |
| get_model, | |
| apply_lora_to_model, | |
| count_parameters | |
| ) | |
| from .dataset import ( | |
| SmokerDataset, | |
| get_transforms, | |
| create_dataloaders | |
| ) | |
| from .train import ( | |
| train_one_epoch, | |
| validate, | |
| train_model, | |
| get_optimizer_and_criterion | |
| ) | |
| from .evaluate import ( | |
| evaluate_model, | |
| print_classification_report, | |
| plot_confusion_matrix, | |
| plot_training_history, | |
| get_predictions_with_confidence, | |
| analyze_errors | |
| ) | |
| from .utils import ( | |
| set_seed, | |
| get_device, | |
| save_checkpoint, | |
| load_checkpoint, | |
| visualize_samples, | |
| print_dataset_info, | |
| create_directories, | |
| count_dataset_images | |
| ) | |
| __version__ = '1.0.0' | |
| __author__ = 'Your Name' | |
| __all__ = [ | |
| # Model | |
| 'LoRALayer', | |
| 'get_model', | |
| 'apply_lora_to_model', | |
| 'count_parameters', | |
| # Dataset | |
| 'SmokerDataset', | |
| 'get_transforms', | |
| 'create_dataloaders', | |
| # Training | |
| 'train_one_epoch', | |
| 'validate', | |
| 'train_model', | |
| 'get_optimizer_and_criterion', | |
| # Evaluation | |
| 'evaluate_model', | |
| 'print_classification_report', | |
| 'plot_confusion_matrix', | |
| 'plot_training_history', | |
| 'get_predictions_with_confidence', | |
| 'analyze_errors', | |
| # Utils | |
| 'set_seed', | |
| 'get_device', | |
| 'save_checkpoint', | |
| 'load_checkpoint', | |
| 'visualize_samples', | |
| 'print_dataset_info', | |
| 'create_directories', | |
| 'count_dataset_images', | |
| ] |