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Feat: 에러핸들러 슬랙메세징 구현

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김진현 2024-09-25 21:24:30 +09:00
parent 82381a5292
commit 7fcc0d9c28
2 changed files with 55 additions and 42 deletions
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78
ai/app/api/yolo/detection.py
View File

@ -20,7 +20,7 @@ router = APIRouter()
@router.post("/predict")
async def detection_predict(request: PredictRequest):
send_slack_message(f"predict 요청{request}", status="success")
send_slack_message(f"predict 요청: {request}", status="success")
# 모델 로드
model = get_model(request)
@ -31,25 +31,19 @@ async def detection_predict(request: PredictRequest):
# 이미지 데이터 정리
url_list = list(map(lambda x:x.image_url, request.image_list))
# 추론
try:
results = run_predictions(model, url_list, request, classes)
response = [process_prediction_result(result, image, request.label_map) for result, image in zip(results,request.image_list)]
send_slack_message(f"predict 성공{response}", status="success")
return response
results = run_predictions(model, url_list, request, classes)
except Exception as e:
# 실패했을 때 Slack 알림
send_slack_message(f"프로젝트 ID: {request.project_id} - 실패! 에러: {str(e)}",status="error")
raise HTTPException(status_code=500, detail="Prediction process failed")
# 추론 결과 변환
response = [process_prediction_result(result, image, request.label_map) for result, image in zip(results,request.image_list)]
send_slack_message(f"predict 성공{response}", status="success")
return response
# 모델 로드
def get_model(request: PredictRequest):
try:
return load_detection_model(request.project_id, request.m_key)
except Exception as e:
send_slack_message(f"프로젝트 ID: {request.project_id} - 실패! 에러: {str(e)}",status="error")
raise HTTPException(status_code=500, detail="load model exception: " + str(e))
# 추론 실행 함수
@ -62,37 +56,39 @@ def run_predictions(model, image, request, classes):
classes=classes
)
except Exception as e:
send_slack_message(f"프로젝트 ID: {request.project_id} - 실패! 에러: {str(e)}",status="error")
raise HTTPException(status_code=500, detail="model predict exception: " + str(e))
# 추론 결과 처리 함수
def process_prediction_result(result, image, label_map):
random_number = random.randint(0, 0xFFFFFF)
color = f"{random_number:06X}"
try:
random_number = random.randint(0, 0xFFFFFF)
color = f"{random_number:06X}"
label_data = LabelData(
version="0.0.0",
task_type="det",
shapes=[
{
"label": summary['name'],
"color": color,
"points": [
[summary['box']['x1'], summary['box']['y1']],
[summary['box']['x2'], summary['box']['y2']]
],
"group_id": label_map[summary['class']] if label_map else summary['class'],
"shape_type": "rectangle",
"flags": {}
}
for summary in result.summary()
],
split="none",
imageHeight=result.orig_img.shape[0],
imageWidth=result.orig_img.shape[1],
imageDepth=result.orig_img.shape[2]
)
label_data = LabelData(
version="0.0.0",
task_type="det",
shapes=[
{
"label": summary['name'],
"color": color,
"points": [
[summary['box']['x1'], summary['box']['y1']],
[summary['box']['x2'], summary['box']['y2']]
],
"group_id": label_map[summary['class']] if label_map else summary['class'],
"shape_type": "rectangle",
"flags": {}
}
for summary in result.summary()
],
split="none",
imageHeight=result.orig_img.shape[0],
imageWidth=result.orig_img.shape[1],
imageDepth=result.orig_img.shape[2]
)
except Exception as e:
raise HTTPException(status_code=500, detail="model predict exception: " + str(e))
return PredictResponse(
image_id=image.image_id,
@ -103,13 +99,13 @@ def process_prediction_result(result, image, label_map):
@router.post("/train")
async def detection_train(request: TrainRequest, http_request: Request):
# Authorization 헤더에서 Bearer 토큰 추출
auth_header = http_request.headers.get("Authorization")
token = auth_header.split(" ")[1] if auth_header and auth_header.startswith("Bearer ") else None
send_slack_message(f"train 요청{request}", status="success")
# Authorization 헤더에서 Bearer 토큰 추출
auth_header = http_request.headers.get("Authorization")
token = auth_header.split(" ")[1] if auth_header and auth_header.startswith("Bearer ") else None
# 데이터셋 루트 경로 얻기
dataset_root_path = get_dataset_root_path(request.project_id)

19
ai/app/main.py
View File

@ -1,7 +1,11 @@
from fastapi import FastAPI
from fastapi import FastAPI, Request
from fastapi.exception_handlers import http_exception_handler, request_validation_exception_handler
from fastapi.exceptions import RequestValidationError
from starlette.exceptions import HTTPException
from api.yolo.detection import router as yolo_detection_router
from api.yolo.segmentation import router as yolo_segmentation_router
from api.yolo.model import router as yolo_model_router
from utils.slackMessage import send_slack_message
app = FastAPI()
@ -10,6 +14,19 @@ app.include_router(yolo_detection_router, prefix="/api/detection", tags=["Detect
app.include_router(yolo_segmentation_router, prefix="/api/segmentation", tags=["Segmentation"])
app.include_router(yolo_model_router, prefix="/api/model", tags=["Model"])
# 예외 처리기
@app.exception_handler(HTTPException)
async def custom_http_exception_handler(request:Request, exc):
body = await request.json()
send_slack_message(f"프로젝트 ID: {body['project_id']} - 실패! 에러: {str(exc)}", status="error")
return await http_exception_handler(request, exc)
@app.exception_handler(RequestValidationError)
async def validation_exception_handler(request:Request, exc):
send_slack_message(f"{request.url} - 요청 실패! 에러: {str(exc)}", status="error")
return await request_validation_exception_handler(request, exc)
# # 애플리케이션 실행
# if __name__ == "__main__":
# import uvicorn