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6cc8ae1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | """
Prediction endpoints.
POST /predict/file - Upload image file
POST /predict/url - Predict from image URL
POST /predict/base64 - Predict from base64 image
"""
from fastapi import APIRouter, UploadFile, File, HTTPException, Query
from backend.app.schemas.predict import (
PredictResponse,
PredictURLRequest,
PredictBase64Request,
PredictionItem,
BreedInfo,
)
from backend.app.services.inference import inference_service
from backend.app.services.image_loader import (
load_image_from_upload,
load_image_from_url,
load_image_from_base64,
)
from backend.app.services.breed_info import breed_info_service
from backend.app.core.logging import logger
router = APIRouter(prefix="/predict", tags=["Prediction"])
def _build_response(result: dict) -> PredictResponse:
"""Build a PredictResponse from inference result dict."""
# Get breed info
breed_info = None
breed_summary = breed_info_service.get_breed_summary(result['predicted_breed'])
if breed_summary:
breed_info = BreedInfo(**breed_summary)
return PredictResponse(
predicted_breed=result['predicted_breed'],
confidence=result['confidence'],
top_k=[PredictionItem(**item) for item in result['top_k']],
breed_info=breed_info,
model_version=result.get('model_version', 'v1.0'),
inference_time_ms=result['inference_time_ms'],
warning=result.get('warning'),
)
@router.post("/file", response_model=PredictResponse)
async def predict_file(
file: UploadFile = File(...),
top_k: int = Query(default=3, ge=1, le=10),
):
"""Predict breed from uploaded image file."""
try:
contents = await file.read()
image = load_image_from_upload(contents)
result = inference_service.predict(image, top_k=top_k)
return _build_response(result)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Prediction error: {e}")
raise HTTPException(status_code=500, detail="Prediction failed")
@router.post("/url", response_model=PredictResponse)
async def predict_url(request: PredictURLRequest):
"""Predict breed from image URL."""
try:
image = load_image_from_url(request.url)
result = inference_service.predict(image, top_k=request.top_k)
return _build_response(result)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Prediction error: {e}")
raise HTTPException(status_code=500, detail="Prediction failed")
@router.post("/base64", response_model=PredictResponse)
async def predict_base64(request: PredictBase64Request):
"""Predict breed from base64-encoded image."""
try:
image = load_image_from_base64(request.image)
result = inference_service.predict(image, top_k=request.top_k)
return _build_response(result)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Prediction error: {e}")
raise HTTPException(status_code=500, detail="Prediction failed")
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