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"""
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',
]
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