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| """ | |
| Hybrid Document Forgery Detection & Localization System | |
| A robust hybrid (Deep Learning + Classical ML) system for multi-type | |
| document forgery detection and localization. | |
| Architecture: | |
| - Deep Learning: MobileNetV3-Small + UNet-Lite for pixel-level localization | |
| - Classical ML: LightGBM for interpretable forgery classification | |
| """ | |
| __version__ = "1.0.0" | |
| from .config import get_config | |
| from .models import get_model, get_loss_function | |
| from .data import get_dataset | |
| from .features import get_feature_extractor, get_mask_refiner, get_region_extractor | |
| from .training import get_trainer, get_metrics_tracker | |
| from .inference import get_pipeline | |
| __all__ = [ | |
| 'get_config', | |
| 'get_model', | |
| 'get_loss_function', | |
| 'get_dataset', | |
| 'get_feature_extractor', | |
| 'get_mask_refiner', | |
| 'get_region_extractor', | |
| 'get_trainer', | |
| 'get_metrics_tracker', | |
| 'get_pipeline' | |
| ] | |