/tesseract & /tesstrain 추가
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2
.gitignore
vendored
2
.gitignore
vendored
@@ -171,3 +171,5 @@ venv2
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/workspace/audio
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/workspace/results
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.venv_stt
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config/model
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@@ -19,3 +19,4 @@ flower
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minio
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opencv-python-headless
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python-dotenv
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pytesseract
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@@ -8,9 +8,11 @@ from config.setting import MINIO_BUCKET_NAME
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from fastapi import APIRouter, File, HTTPException, UploadFile
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from fastapi.responses import JSONResponse
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from tasks import (
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call_paddle_ocr,
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call_tesseract_ocr,
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call_tesstrain_ocr,
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call_upstage_ocr_api,
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celery_app,
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parse_ocr_text,
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store_ocr_result,
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)
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from utils.checking_keys import create_key
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@@ -73,7 +75,7 @@ async def _process_ocr_request(file: UploadFile, ocr_task):
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@router.post("/paddle", summary="[Paddle] 파일 업로드 기반 비동기 OCR")
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async def ocr_paddle_endpoint(file: UploadFile = File(...)):
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return await _process_ocr_request(file, parse_ocr_text)
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return await _process_ocr_request(file, call_paddle_ocr)
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@router.post("/upstage", summary="[Upstage] 파일 업로드 기반 비동기 OCR")
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@@ -81,6 +83,16 @@ async def ocr_upstage_endpoint(file: UploadFile = File(...)):
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return await _process_ocr_request(file, call_upstage_ocr_api)
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@router.post("/tesseract", summary="[Tesseract] 기본 모델 비동기 OCR")
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async def ocr_tesseract_endpoint(file: UploadFile = File(...)):
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return await _process_ocr_request(file, call_tesseract_ocr)
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@router.post("/tesstrain", summary="[Tesseract] 훈련된 모델 비동기 OCR")
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async def ocr_tesstrain_endpoint(file: UploadFile = File(...)):
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return await _process_ocr_request(file, call_tesstrain_ocr)
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@router.get("/progress/{request_id}", summary="OCR 진행 상태 및 결과 조회")
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async def check_progress(request_id: str):
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task_id = redis_client.hget("ocr_task_mapping", request_id)
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86
tasks.py
86
tasks.py
@@ -5,8 +5,10 @@ import os
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import tempfile
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import time
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from datetime import datetime, timezone
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from io import BytesIO
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import httpx
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import pytesseract
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import redis
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from celery import Task
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from config.setting import (
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@@ -15,6 +17,8 @@ from config.setting import (
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REDIS_PORT,
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UPSTAGE_API_KEY,
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)
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from PIL import Image
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from pdf2image import convert_from_path
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from utils.celery_utils import celery_app
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from utils.ocr_processor import ocr_process
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from utils.text_extractor import extract_text_from_file
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@@ -70,7 +74,7 @@ async def download_file_from_presigned_url(file_url: str, save_path: str):
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# (Paddle) OCR + 후처리
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@celery_app.task(bind=True, base=BaseTaskWithProgress)
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def parse_ocr_text(self, presigned_url: str, request_id: str, file_name: str):
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def call_paddle_ocr(self, presigned_url: str, request_id: str, file_name: str):
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self.update_progress(request_id, "Paddle OCR 작업 시작")
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suffix = os.path.splitext(file_name)[-1]
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@@ -220,6 +224,86 @@ def call_upstage_ocr_api(self, presigned_url: str, request_id: str, file_name: s
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os.remove(tmp_path)
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# (Tesseract) 기본 모델 OCR
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@celery_app.task(bind=True, base=BaseTaskWithProgress)
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def call_tesseract_ocr(self, presigned_url: str, request_id: str, file_name: str):
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self.update_progress(request_id, "Tesseract (기본) OCR 작업 시작")
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suffix = os.path.splitext(file_name)[-1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp_file:
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tmp_path = tmp_file.name
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try:
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self.update_progress(request_id, "파일 다운로드 중")
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asyncio.run(download_file_from_presigned_url(presigned_url, tmp_path))
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self.update_progress(request_id, "파일 다운로드 완료")
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start_time = time.time()
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if file_name.lower().endswith(".pdf"):
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images = convert_from_path(tmp_path)
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text = ""
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for image in images:
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text += pytesseract.image_to_string(image, lang="kor")
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else:
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with open(tmp_path, "rb") as f:
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image_bytes = f.read()
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image = Image.open(BytesIO(image_bytes))
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text = pytesseract.image_to_string(image, lang="kor")
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end_time = time.time()
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self.update_progress(request_id, "Tesseract OCR 완료")
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# 좌표(coord) 정보는 pytesseract 기본 출력에서 얻기 어려우므로 빈 리스트로 처리
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result_json = ocr_process(
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file_name, "tesseract_default", [], text, start_time, end_time
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)
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return result_json
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finally:
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if os.path.exists(tmp_path):
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os.remove(tmp_path)
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# (Tesseract) 훈련된 모델 OCR
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@celery_app.task(bind=True, base=BaseTaskWithProgress)
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def call_tesstrain_ocr(self, presigned_url: str, request_id: str, file_name: str):
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self.update_progress(request_id, "Tesseract (훈련 모델) OCR 작업 시작")
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TESSDATA_DIR = "/tesseract_trainer/tesstrain/workspace/"
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MODEL_NAME = "kor_fonts"
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suffix = os.path.splitext(file_name)[-1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp_file:
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tmp_path = tmp_file.name
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try:
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self.update_progress(request_id, "파일 다운로드 중")
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asyncio.run(download_file_from_presigned_url(presigned_url, tmp_path))
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self.update_progress(request_id, "파일 다운로드 완료")
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start_time = time.time()
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if file_name.lower().endswith(".pdf"):
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images = convert_from_path(tmp_path)
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text = ""
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custom_config = f"--tessdata-dir {TESSDATA_DIR} -l {MODEL_NAME}"
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for image in images:
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text += pytesseract.image_to_string(image, config=custom_config)
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else:
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with open(tmp_path, "rb") as f:
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image_bytes = f.read()
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image = Image.open(BytesIO(image_bytes))
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custom_config = f"--tessdata-dir {TESSDATA_DIR} -l {MODEL_NAME}"
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text = pytesseract.image_to_string(image, config=custom_config)
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end_time = time.time()
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self.update_progress(request_id, "Tesseract (훈련 모델) OCR 완료")
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result_json = ocr_process(
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file_name, f"tesstrain_{MODEL_NAME}", [], text, start_time, end_time
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)
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return result_json
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finally:
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if os.path.exists(tmp_path):
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os.remove(tmp_path)
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# 결과 Redis 저장 (체인의 두 번째 스텝)
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# router 체인: store_ocr_result.s(request_id=request_id, task_id=task_id)
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@celery_app.task(bind=True, base=BaseTaskWithProgress, ignore_result=True)
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