ab0e9b973a
- Set up FastAPI project structure with SQLite database - Create database models for tomato images and severity classifications - Implement image upload and processing endpoints - Develop a segmentation model for tomato disease severity detection - Add API endpoints for analysis and results retrieval - Implement health check endpoint - Set up Alembic for database migrations - Update project documentation
69 lines
2.7 KiB
Python
69 lines
2.7 KiB
Python
import uuid
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from datetime import datetime
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from sqlalchemy import Column, String, DateTime, Float, Text, ForeignKey, Integer
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from sqlalchemy.orm import relationship
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from app.db.session import Base
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class TomatoImage(Base):
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__tablename__ = "tomato_images"
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id = Column(String(36), primary_key=True, index=True, default=lambda: str(uuid.uuid4()))
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filename = Column(String(255), nullable=False)
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file_path = Column(String(512), nullable=False, unique=True)
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file_size = Column(Integer, nullable=False)
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mime_type = Column(String(50), nullable=False)
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width = Column(Integer, nullable=True)
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height = Column(Integer, nullable=True)
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uploaded_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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# Relationships
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analysis_results = relationship("AnalysisResult", back_populates="image", cascade="all, delete-orphan")
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def __repr__(self):
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return f"<TomatoImage {self.filename}>"
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class AnalysisResult(Base):
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__tablename__ = "analysis_results"
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id = Column(String(36), primary_key=True, index=True, default=lambda: str(uuid.uuid4()))
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image_id = Column(String(36), ForeignKey("tomato_images.id", ondelete="CASCADE"), nullable=False)
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model_name = Column(String(255), nullable=False)
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model_version = Column(String(50), nullable=False)
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# Overall severity data
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primary_severity = Column(String(50), nullable=True)
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severity_confidence = Column(Float, nullable=True)
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# Segmentation data (stored as JSON string)
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segmentation_data = Column(Text, nullable=True)
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# Additional metadata
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processed_at = Column(DateTime, default=datetime.utcnow, nullable=False)
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processing_time_ms = Column(Integer, nullable=True)
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# Relationships
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image = relationship("TomatoImage", back_populates="analysis_results")
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severity_details = relationship("SeverityDetail", back_populates="analysis_result", cascade="all, delete-orphan")
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def __repr__(self):
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return f"<AnalysisResult {self.id} for image {self.image_id}>"
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class SeverityDetail(Base):
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__tablename__ = "severity_details"
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id = Column(String(36), primary_key=True, index=True, default=lambda: str(uuid.uuid4()))
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analysis_id = Column(String(36), ForeignKey("analysis_results.id", ondelete="CASCADE"), nullable=False)
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severity_class = Column(String(50), nullable=False)
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confidence = Column(Float, nullable=False)
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affected_area_percentage = Column(Float, nullable=True)
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# Relationships
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analysis_result = relationship("AnalysisResult", back_populates="severity_details")
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def __repr__(self):
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return f"<SeverityDetail {self.severity_class} ({self.confidence:.2f})>" |