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
112 lines
3.3 KiB
Python
112 lines
3.3 KiB
Python
from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, status
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from sqlalchemy.orm import Session
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from typing import List
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from pathlib import Path
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from app.db.session import get_db
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from app.db.crud_tomato import tomato_image
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from app.schemas.tomato import TomatoImage, TomatoImageCreate, UploadResponse
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from app.utils.image import save_uploaded_image
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from app.core.config import settings
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router = APIRouter()
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@router.post("/upload", response_model=UploadResponse, status_code=status.HTTP_201_CREATED)
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async def upload_tomato_image(
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file: UploadFile = File(...),
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db: Session = Depends(get_db)
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):
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"""
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Upload a tomato image for analysis.
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The image will be saved and registered in the database.
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It can then be analyzed using the analysis endpoint.
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"""
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# Validate file type
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if file.content_type not in settings.ALLOWED_IMAGE_TYPES:
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raise HTTPException(
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status_code=status.HTTP_415_UNSUPPORTED_MEDIA_TYPE,
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detail=f"Unsupported file type: {file.content_type}. Allowed types: {', '.join(settings.ALLOWED_IMAGE_TYPES)}"
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)
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# Read file content
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contents = await file.read()
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# Validate file size
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if len(contents) > settings.MAX_IMAGE_SIZE:
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raise HTTPException(
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status_code=status.HTTP_413_REQUEST_ENTITY_TOO_LARGE,
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detail=f"File too large. Maximum size allowed: {settings.MAX_IMAGE_SIZE / (1024 * 1024)}MB"
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)
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# Save file and get metadata
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image_data = save_uploaded_image(contents, file.filename)
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# Create database record
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image_in = TomatoImageCreate(**image_data)
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db_image = tomato_image.create(db=db, obj_in=image_in)
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return UploadResponse(
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image=db_image,
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message="Image uploaded successfully"
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)
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@router.get("/", response_model=List[TomatoImage])
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def list_tomato_images(
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skip: int = 0,
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limit: int = 100,
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db: Session = Depends(get_db)
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):
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"""
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List all uploaded tomato images.
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"""
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images = tomato_image.get_multi(db=db, skip=skip, limit=limit)
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return images
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@router.get("/{image_id}", response_model=TomatoImage)
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def get_tomato_image(
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image_id: str,
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db: Session = Depends(get_db)
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):
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"""
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Get a specific tomato image by ID.
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"""
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db_image = tomato_image.get(db=db, id=image_id)
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if db_image is None:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="Image not found"
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)
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return db_image
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@router.delete("/{image_id}", status_code=status.HTTP_204_NO_CONTENT, response_model=None)
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def delete_tomato_image(
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image_id: str,
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db: Session = Depends(get_db)
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):
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"""
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Delete a tomato image and its associated data.
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"""
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db_image = tomato_image.get(db=db, id=image_id)
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if db_image is None:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="Image not found"
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)
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# Delete the image file
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try:
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if db_image.file_path and Path(db_image.file_path).exists():
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Path(db_image.file_path).unlink()
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except Exception:
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# Log error but continue with database deletion
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pass
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# Delete database record (cascade will handle related records)
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tomato_image.remove(db=db, id=image_id)
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return None |