feat: 모바일 반응형 + 변환 타임아웃 설정
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@@ -1,8 +1,5 @@
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"""
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OCR Celery Tasks
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- PaddleOCR 3.x 호환 (use_gpu/show_log/cls 파라미터 제거, 결과구조 변경 반영)
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- backend="paddle" → PaddleOCR 로컬 실행
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- backend="ollama" → Ollama Vision API 호출
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OCR Celery Tasks — PaddleOCR 3.x + Ollama Vision
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"""
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import os
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import base64
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@@ -16,7 +13,7 @@ REDIS_URL = os.getenv("REDIS_URL", "redis://redis:6379/0")
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OUTPUT_DIR = os.getenv("OUTPUT_DIR", "/data/outputs")
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OCR_LANG = os.getenv("OCR_LANG", "korean")
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OLLAMA_URL = os.getenv("OLLAMA_URL", "http://192.168.0.126:11434")
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OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "180"))
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OLLAMA_TIMEOUT = int(os.getenv("OLLAMA_TIMEOUT", "600"))
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celery_app = Celery("ocr_tasks", broker=REDIS_URL, backend=REDIS_URL)
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celery_app.conf.update(
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@@ -27,7 +24,6 @@ celery_app.conf.update(
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result_expires=3600,
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)
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# PaddleOCR 싱글톤
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_ocr_engine = None
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_struct_engine = None
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@@ -36,7 +32,6 @@ def get_ocr():
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if _ocr_engine is None:
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from paddleocr import PaddleOCR
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print(f"[PaddleOCR] 로딩 (lang={OCR_LANG})")
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# PaddleOCR 3.x: use_gpu/show_log 파라미터 제거됨
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_ocr_engine = PaddleOCR(use_angle_cls=True, lang=OCR_LANG)
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print("[PaddleOCR] 완료")
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return _ocr_engine
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@@ -51,9 +46,6 @@ def get_structure():
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return _struct_engine
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# ════════════════════════════════════════════════════════════════
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# 메인 Task
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# ════════════════════════════════════════════════════════════════
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@celery_app.task(bind=True, name="tasks.ocr_task", queue="ocr")
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def ocr_task(self, file_id, image_path, mode="text",
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backend="paddle", ollama_model="granite3.2-vision", custom_prompt=""):
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@@ -72,9 +64,6 @@ def ocr_task(self, file_id, image_path, mode="text",
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raise Exception(f"OCR 실패: {str(e)}")
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# ════════════════════════════════════════════════════════════════
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# Ollama 백엔드
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# ════════════════════════════════════════════════════════════════
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_OLLAMA_PROMPTS = {
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"text": "이 이미지에서 모든 텍스트를 정확하게 추출해줘. 원본의 줄 구분과 단락 구조를 유지해줘.",
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"structure": "이 이미지를 분석해서 표는 마크다운 표 형식으로, 나머지 텍스트는 원본 구조를 유지하며 추출해줘.",
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@@ -91,8 +80,7 @@ def _run_ollama(task, file_id, image_path, mode, ollama_model, custom_prompt):
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resp = httpx.post(f"{OLLAMA_URL}/api/chat", json={
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"model": ollama_model,
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"messages": [{"role": "user", "content": prompt, "images": [img_b64]}],
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"stream": False,
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"options": {"temperature": 0.1},
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"stream": False, "options": {"temperature": 0.1},
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}, timeout=float(OLLAMA_TIMEOUT))
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resp.raise_for_status()
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except httpx.ConnectError:
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@@ -121,16 +109,12 @@ def _run_ollama(task, file_id, image_path, mode, ollama_model, custom_prompt):
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"mode": mode, "backend": "ollama", "ollama_model": ollama_model,
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"full_text": full_text, "lines": lines, "line_count": len(lines),
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"txt_file": txt_file,
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"tables": [{"html": h, "rows": len(t),
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"cols": max(len(r) for r in t) if t else 0}
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"tables": [{"html": h, "rows": len(t), "cols": max(len(r) for r in t) if t else 0}
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for h, t in zip(tables_html, tables)],
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"xlsx_file": xlsx_file,
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}
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# ════════════════════════════════════════════════════════════════
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# PaddleOCR 백엔드
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# ════════════════════════════════════════════════════════════════
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def _run_paddle(task, file_id, image_path, mode):
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import cv2
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img = cv2.imread(image_path)
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@@ -140,50 +124,38 @@ def _run_paddle(task, file_id, image_path, mode):
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return _paddle_structure(task, file_id, img) if mode == "structure" \
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else _paddle_text(task, file_id, img)
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def _paddle_text(task, file_id, img):
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task.update_state(state="PROGRESS", meta={"progress": 30, "message": "텍스트 인식 중..."})
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# PaddleOCR 3.x: cls 파라미터 제거, 결과 구조 변경
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result = get_ocr().ocr(img)
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task.update_state(state="PROGRESS", meta={"progress": 80, "message": "결과 정리 중..."})
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lines = []
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if result and len(result) > 0:
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r = result[0]
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# PaddleOCR 3.x 결과 구조: dict with rec_texts, rec_scores
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if isinstance(r, dict):
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texts = r.get("rec_texts", [])
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scores = r.get("rec_scores", [])
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for text, conf in zip(texts, scores):
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if text.strip():
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lines.append({"text": text,
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"confidence": round(float(conf), 3),
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"bbox": []})
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# 구버전 호환 (list of [bbox, (text, conf)])
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lines.append({"text": text, "confidence": round(float(conf), 3), "bbox": []})
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elif isinstance(r, list):
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for item in r:
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if item and len(item) == 2:
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_, (text, conf) = item
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if text.strip():
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lines.append({"text": text,
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"confidence": round(float(conf), 3),
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"bbox": []})
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lines.append({"text": text, "confidence": round(float(conf), 3), "bbox": []})
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full_text = "\n".join(l["text"] for l in lines)
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txt_file = f"{file_id}_ocr.txt"
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with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
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f.write(full_text)
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return {"mode": "text", "backend": "paddle",
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return {"mode": "text", "backend": "paddle", "ollama_model": "",
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"full_text": full_text, "lines": lines,
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"line_count": len(lines), "txt_file": txt_file,
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"tables": [], "xlsx_file": None}
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def _paddle_structure(task, file_id, img):
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task.update_state(state="PROGRESS", meta={"progress": 20, "message": "레이아웃 분석 중..."})
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result = get_structure()(img)
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task.update_state(state="PROGRESS", meta={"progress": 60, "message": "표 구조 추출 중..."})
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text_blocks, tables_html, tables_data = [], [], []
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for region in result:
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rtype = region.get("type", "").lower()
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@@ -197,32 +169,24 @@ def _paddle_structure(task, file_id, img):
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if isinstance(line, (list, tuple)) and len(line) == 2:
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_, (text, _conf) = line
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text_blocks.append(text)
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full_text = "\n".join(text_blocks)
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task.update_state(state="PROGRESS", meta={"progress": 80, "message": "Excel 생성 중..."})
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xlsx_file = None
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if tables_data:
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xlsx_file = f"{file_id}_tables.xlsx"
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_save_excel(tables_data, os.path.join(OUTPUT_DIR, xlsx_file))
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txt_file = f"{file_id}_ocr.txt"
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with open(os.path.join(OUTPUT_DIR, txt_file), "w", encoding="utf-8") as f:
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f.write("# 텍스트\n\n" + full_text)
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lines = [{"text": t, "confidence": 1.0, "bbox": []} for t in text_blocks]
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tables_meta = [{"html": h, "rows": len(d),
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"cols": max(len(r) for r in d) if d else 0}
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lines = [{"text": t, "confidence": 1.0, "bbox": []} for t in text_blocks]
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tables_meta = [{"html": h, "rows": len(d), "cols": max(len(r) for r in d) if d else 0}
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for h, d in zip(tables_html, tables_data)]
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return {"mode": "structure", "backend": "paddle",
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return {"mode": "structure", "backend": "paddle", "ollama_model": "",
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"full_text": full_text, "lines": lines,
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"line_count": len(lines), "txt_file": txt_file,
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"tables": tables_meta, "xlsx_file": xlsx_file}
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# ════════════════════════════════════════════════════════════════
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# 공통 유틸
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# ════════════════════════════════════════════════════════════════
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def _parse_md_tables(text):
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tables, current = [], []
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for line in text.splitlines():
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@@ -241,8 +205,7 @@ def _md_table_to_html(table):
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rows = ""
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for i, row in enumerate(table):
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tag = "th" if i == 0 else "td"
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cells = "".join(f"<{tag}>{c}</{tag}>" for c in row)
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rows += f"<tr>{cells}</tr>"
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rows += "<tr>" + "".join(f"<{tag}>{c}</{tag}>" for c in row) + "</tr>"
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return f"<table>{rows}</table>"
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def _html_table_to_list(html):
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@@ -252,11 +215,10 @@ def _html_table_to_list(html):
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super().__init__()
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self.rows, self._row, self._cell, self._in = [], [], [], False
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def handle_starttag(self, tag, attrs):
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if tag == "tr": self._row = []
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if tag == "tr": self._row = []
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elif tag in ("td","th"): self._cell = []; self._in = True
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def handle_endtag(self, tag):
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if tag in ("td","th"):
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self._row.append("".join(self._cell).strip()); self._in = False
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if tag in ("td","th"): self._row.append("".join(self._cell).strip()); self._in = False
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elif tag == "tr":
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if self._row: self.rows.append(self._row)
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def handle_data(self, data):
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@@ -264,18 +226,16 @@ def _html_table_to_list(html):
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p = P(); p.feed(html); return p.rows
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def _save_excel(tables, path):
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wb = openpyxl.Workbook()
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wb.remove(wb.active)
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wb = openpyxl.Workbook(); wb.remove(wb.active)
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for i, table in enumerate(tables, 1):
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ws = wb.create_sheet(f"표 {i}")
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ws = wb.create_sheet(f"표 {i}")
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thin = Side(style="thin", color="2A2A33")
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bdr = Border(left=thin, right=thin, top=thin, bottom=thin)
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for r_idx, row in enumerate(table, 1):
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for c_idx, val in enumerate(row, 1):
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cell = ws.cell(row=r_idx, column=c_idx, value=val)
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cell.border = bdr
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cell.alignment = Alignment(horizontal="center",
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vertical="center", wrap_text=True)
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cell.border = bdr
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cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=True)
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if r_idx == 1:
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cell.fill = PatternFill("solid", fgColor="1A1A2E")
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cell.font = Font(color="00E5A0", bold=True, size=10)
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