""" CropDoctor-Semantic: AI-Powered Plant Disease Diagnosis ======================================================== A comprehensive pipeline for plant disease diagnosis using: - SAM 3 (Segment Anything Model 3) for concept-based segmentation - CNN-based severity classification - LLM-powered treatment recommendations Main Components: - SAM3Segmenter: Zero-shot disease region segmentation - SeverityClassifier: CNN for severity assessment - TreatmentRecommender: Claude API integration for treatment advice - CropDoctorPipeline: End-to-end diagnostic pipeline Quick Start: >>> from src.pipeline import CropDoctorPipeline >>> pipeline = CropDoctorPipeline() >>> result = pipeline.diagnose("path/to/leaf.jpg") >>> print(result.disease_name, result.severity_label) For more information, see the README.md or documentation. """ __version__ = "0.1.0" __author__ = "CropDoctor Team" from .sam3_segmentation import ( SAM3Segmenter, MockSAM3Segmenter, create_segmenter, SegmentationResult ) from .severity_classifier import ( SeverityClassifier, SeverityClassifierCNN, SeverityPrediction, SEVERITY_LABELS, SEVERITY_DESCRIPTIONS ) from .treatment_recommender import ( TreatmentRecommender, TreatmentRecommendation, DISEASE_DATABASE ) from .pipeline import ( CropDoctorPipeline, DiagnosticResult, quick_diagnose ) from .visualization import ( create_diagnostic_visualization, create_mask_overlay, create_severity_heatmap, create_comparison_view, create_treatment_card, save_visualization ) __all__ = [ # Version '__version__', # Segmentation 'SAM3Segmenter', 'MockSAM3Segmenter', 'create_segmenter', 'SegmentationResult', # Classification 'SeverityClassifier', 'SeverityClassifierCNN', 'SeverityPrediction', 'SEVERITY_LABELS', 'SEVERITY_DESCRIPTIONS', # Recommendations 'TreatmentRecommender', 'TreatmentRecommendation', 'DISEASE_DATABASE', # Pipeline 'CropDoctorPipeline', 'DiagnosticResult', 'quick_diagnose', # Visualization 'create_diagnostic_visualization', 'create_mask_overlay', 'create_severity_heatmap', 'create_comparison_view', 'create_treatment_card', 'save_visualization', ]