加速错题 OCR：上传压缩、识别缩放、启动预热与 MKL-DNN。

backend/app/core/config.py

@@ -19,9 +19,12 @@ class Settings(BaseSettings):
     FRONTEND_DIST: str = "../frontend/dist"
     ADMIN_DEFAULT_USERNAME: str = "admin"
     ADMIN_DEFAULT_PASSWORD: str = "admin123"
-    OCR_TIMEOUT_SECONDS: int = 300
+    OCR_TIMEOUT_SECONDS: int = 180
     AI_TIMEOUT_SECONDS: int = 600
     PROCESS_STALE_MINUTES: int = 20
+    OCR_MAX_SIDE: int = 1280
+    UPLOAD_MAX_SIDE: int = 2048
+    OCR_WARMUP: bool = True
 
     class Config:
         env_file = ".env"

backend/app/main.py

@@ -9,6 +9,7 @@ from fastapi.staticfiles import StaticFiles
 from app.core.config import settings
 from app.core.database import Base, SessionLocal, engine
 from app.routers import admin, auth, exams, export, settings as settings_router, students, subjects, wrong_questions
+from app.services import ocr as ocr_service
 from app.services.migrate import run_migrations
 from app.services.seed import seed_admin_and_settings, seed_subjects
 
@@ -34,6 +35,7 @@ async def lifespan(app: FastAPI):
         seed_admin_and_settings(db)
     finally:
         db.close()
+    ocr_service.warmup_ocr_engine()
     yield
 
 

backend/app/routers/wrong_questions.py

@@ -157,8 +157,7 @@ def _process_wrong_question(question_id: uuid.UUID):
         except FuturesTimeout:
             wq.status = WrongQuestionStatus.failed
             wq.error_message = (
-                f"OCR 识别超时（>{settings.OCR_TIMEOUT_SECONDS}秒）。"
-                " 首次加载模型较慢，请稍后点「重新识别标注」重试"
+                f"OCR 识别超时（>{settings.OCR_TIMEOUT_SECONDS}秒），请点「重新识别标注」重试"
             )
             db.commit()
             return

backend/app/services/ocr.py

@@ -1,6 +1,9 @@
-from pathlib import Path
-
+import logging
 import os
+import tempfile
+import threading
+from io import BytesIO
+from pathlib import Path
 
 from PIL import Image
 
@@ -9,7 +12,10 @@ from app.core.config import settings
 # 无图形界面服务器：避免 OpenCV/Paddle 依赖 X11
 os.environ.setdefault("OPENCV_IO_ENABLE_OPENEXR", "0")
 
+logger = logging.getLogger(__name__)
+
 _ocr_engine = None
+_ocr_warmup_started = False
 
 
 def get_ocr_engine():
@@ -17,20 +23,103 @@ def get_ocr_engine():
     if _ocr_engine is None:
         from paddleocr import PaddleOCR
 
-        _ocr_engine = PaddleOCR(use_angle_cls=True, lang="ch", show_log=False)
+        _ocr_engine = PaddleOCR(
+            use_angle_cls=False,
+            lang="ch",
+            show_log=False,
+            use_gpu=False,
+            enable_mkldnn=True,
+            det_limit_side_len=min(settings.OCR_MAX_SIDE, 1280),
+            rec_batch_num=8,
+        )
     return _ocr_engine
 
 
+def warmup_ocr_engine() -> None:
+    """后台预加载 OCR 模型，避免首张图片等待数分钟。"""
+    global _ocr_warmup_started
+    if _ocr_warmup_started or not settings.OCR_WARMUP:
+        return
+    _ocr_warmup_started = True
+
+    def _run() -> None:
+        try:
+            engine = get_ocr_engine()
+            with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp:
+                Image.new("RGB", (120, 40), color=(255, 255, 255)).save(tmp.name, format="JPEG")
+                tmp_path = tmp.name
+            try:
+                engine.ocr(tmp_path, cls=False)
+                logger.info("OCR engine warmed up")
+            finally:
+                Path(tmp_path).unlink(missing_ok=True)
+        except Exception as exc:
+            logger.warning("OCR warmup failed: %s", exc)
+
+    threading.Thread(target=_run, daemon=True, name="ocr-warmup").start()
+
+
 def _bbox_from_box(box: list) -> list[float]:
     xs = [float(p[0]) for p in box]
     ys = [float(p[1]) for p in box]
     return [min(xs), min(ys), max(xs), max(ys)]
 
 
+def _scale_bbox(bbox: list[float], scale_x: float, scale_y: float) -> list[float]:
+    return [bbox[0] * scale_x, bbox[1] * scale_y, bbox[2] * scale_x, bbox[3] * scale_y]
+
+
+def _scale_box(box: list, scale_x: float, scale_y: float) -> list:
+    return [[float(p[0]) * scale_x, float(p[1]) * scale_y] for p in box]
+
+
+def _normalize_image_bytes(content: bytes, max_side: int) -> bytes:
+    with Image.open(BytesIO(content)) as img:
+        img = img.convert("RGB")
+        width, height = img.size
+        longest = max(width, height)
+        if longest > max_side:
+            ratio = max_side / longest
+            img = img.resize((int(width * ratio), int(height * ratio)), Image.Resampling.LANCZOS)
+        buf = BytesIO()
+        img.save(buf, format="JPEG", quality=88, optimize=True)
+        return buf.getvalue()
+
+
+def _prepare_ocr_image(image_path: str) -> tuple[str, float, float, int, int, Path | None]:
+    """若图片过大则生成临时缩小图供 OCR，返回缩放比例与原始尺寸。"""
+    with Image.open(image_path) as img:
+        orig_w, orig_h = img.size
+
+    max_side = settings.OCR_MAX_SIDE
+    longest = max(orig_w, orig_h)
+    if longest <= max_side:
+        return image_path, 1.0, 1.0, orig_w, orig_h, None
+
+    with Image.open(image_path) as img:
+        img = img.convert("RGB")
+        ratio = max_side / longest
+        new_w = max(1, int(orig_w * ratio))
+        new_h = max(1, int(orig_h * ratio))
+        resized = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
+        tmp = Path(tempfile.gettempdir()) / f"ocr_{Path(image_path).stem}_{os.getpid()}.jpg"
+        resized.save(tmp, format="JPEG", quality=85, optimize=True)
+
+    scale_x = orig_w / new_w
+    scale_y = orig_h / new_h
+    return str(tmp), scale_x, scale_y, orig_w, orig_h, tmp
+
+
 def run_ocr_with_regions(image_path: str) -> dict:
     """Return OCR text plus line-level bounding boxes for annotation."""
     engine = get_ocr_engine()
-    result = engine.ocr(image_path, cls=True)
+    ocr_path, scale_x, scale_y, orig_w, orig_h, tmp_path = _prepare_ocr_image(image_path)
+    try:
+        result = engine.ocr(ocr_path, cls=False)
+    finally:
+        if tmp_path is not None:
+            tmp_path.unlink(missing_ok=True)
+
     lines: list[dict] = []
     if result and result[0]:
         for item in result[0]:
@@ -41,27 +130,23 @@ def run_ocr_with_regions(image_path: str) -> dict:
             conf = float(rec[1]) if rec and len(rec) > 1 else 0.0
             if not text:
                 continue
+            if scale_x != 1.0 or scale_y != 1.0:
+                box = _scale_box(box, scale_x, scale_y)
+            bbox = _bbox_from_box(box)
             lines.append(
                 {
                     "text": text,
                     "confidence": conf,
                     "box": box,
-                    "bbox": _bbox_from_box(box),
+                    "bbox": bbox,
                 }
             )
 
-    width, height = 0, 0
-    try:
-        with Image.open(image_path) as img:
-            width, height = img.size
-    except OSError:
-        pass
-
     return {
         "text": "\n".join(line["text"] for line in lines),
         "lines": lines,
-        "width": width,
-        "height": height,
+        "width": orig_w,
+        "height": orig_h,
     }
 
 
@@ -77,7 +162,8 @@ def save_upload_file(user_id: str, question_id: str, filename: str, content: byt
     user_dir.mkdir(parents=True, exist_ok=True)
     rel_path = f"{user_id}/{question_id}{ext}"
     full_path = Path(settings.UPLOAD_DIR) / rel_path
-    full_path.write_bytes(content)
+    normalized = _normalize_image_bytes(content, settings.UPLOAD_MAX_SIDE)
+    full_path.write_bytes(normalized)
     return rel_path
 
 

frontend/dist/index.html

@@ -9,7 +9,7 @@
     <meta name="author" content="马建军" />
     <meta name="copyright" content="Copyright (c) 马建军. All rights reserved." />
     <title>中学成绩档案</title>
-    <script type="module" crossorigin src="/assets/index-_1CtLpiP.js"></script>
+    <script type="module" crossorigin src="/assets/index-DzzkB1zh.js"></script>
     <link rel="stylesheet" crossorigin href="/assets/index-GY2etMYN.css">
   </head>
   <body>

frontend/src/pages/WrongQuestionDetail.tsx

@@ -37,7 +37,7 @@ export default function WrongQuestionDetail({
     try {
       const { data } = await wrongQuestionApi.get(questionId)
       setWq(data)
-      setQuestionText(data.question_text || '')
+      setQuestionText(data.question_text || data.ocr_raw_text || '')
       setApproachText(data.solution_approach || '')
       setSolutionText(data.solution_text || '')
       setImageMode(data.has_annotated_image ? 'annotated' : 'original')
@@ -56,7 +56,7 @@ export default function WrongQuestionDetail({
       try {
         const { data } = await wrongQuestionApi.get(questionId)
         setWq(data)
-        setQuestionText(data.question_text || '')
+        setQuestionText(data.question_text || data.ocr_raw_text || '')
         setApproachText(data.solution_approach || '')
         setSolutionText(data.solution_text || '')
         if (data.has_annotated_image) setImageMode('annotated')
@@ -88,7 +88,7 @@ export default function WrongQuestionDetail({
     try {
       const { data } = await wrongQuestionApi.regenerate(questionId)
       setWq(data)
-      setQuestionText(data.question_text || '')
+      setQuestionText(data.question_text || data.ocr_raw_text || '')
       setApproachText(data.solution_approach || '')
       setSolutionText(data.solution_text || '')
       message.success('解题思路已重新生成')

frontend/src/utils/wqProcessing.ts

@@ -9,10 +9,10 @@ export function isWrongQuestionProcessing(wq: WrongQuestion): boolean {
 
 export function processingHint(wq: WrongQuestion): string {
   if (wq.status === 'pending') {
-    return '正在 OCR 识别（首次约 1–5 分钟，请稍候）…'
+    return '正在识别文字（约 10–30 秒）…'
   }
   if (wq.status === 'ocr_done') {
-    return '正在标注错题并生成解题思路…'
+    return '正在标注错题并生成解题思路（约 30–90 秒）…'
   }
   return '正在识别、标注并生成解题思路…'
 }