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import io
import logging
from fastapi import APIRouter, HTTPException, status, UploadFile, Depends
from PIL import Image
from src.dependencies import get_model, get_preprocessor
from src.schema import MushroomClassification
from src.services import classify_mushroom_in_image_svc
logger = logging.getLogger(__name__)
router = APIRouter()
@router.post(
"/classify", response_model=MushroomClassification, status_code=status.HTTP_200_OK
)
async def classify_mushroom_in_image(
image_file: UploadFile,
model=Depends(get_model),
preprocessor=Depends(get_preprocessor),
):
"""Open uploaded image file and call mushroom classification
service.
:param image_file: the uploaded image file
:type image_file: UploadFile
:param model: the pretrained model, defaults to Depends(get_model)
:type model: PreTrainedModel, optional
:param preprocessor: the preprocessor for image input transforms, defaults to Depends(get_preprocessor)
:type preprocessor: BaseImageProcessor, optional
:raises HTTPException: Internal Server Error in case of model/preprocessor loading failure or some uknown error,
or Bad Request Error in case of corrupted or invalid uploaded file
:return: mushroom_type, toxicity_profile, classification_confidence
:rtype: MushroomClassification
"""
logger.info(f"Classify image: {image_file.filename}")
try:
request_object_content = await image_file.read()
img = Image.open(io.BytesIO(request_object_content))
if img.mode != "RGB":
img = img.convert("RGB")
except Exception as e:
logger.error(f"Error reading file: {str(e)}")
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Failed to read uploaded file. The file may be corrupted or invalid.",
)
# Get class_name predicted and prediction probability
class_name, toxicity, confidence = await classify_mushroom_in_image_svc(
img, model, preprocessor
)
return MushroomClassification(
mushroom_type=class_name, toxicity_profile=toxicity, confidence=confidence
)
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