init

.gitattributes

@@ -1,4 +1,8 @@
+data/**/* filter=lfs diff=lfs merge=lfs -text
 *.7z filter=lfs diff=lfs merge=lfs -text
+*.mdx filter=lfs diff=lfs merge=lfs -text
+*.pdf filter=lfs diff=lfs merge=lfs -text
+*.ttf filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
 *.avro filter=lfs diff=lfs merge=lfs -text
 *.bin filter=lfs diff=lfs merge=lfs -text
@@ -58,3 +62,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+ocr/out/** filter=lfs diff=lfs merge=lfs -text
+ocr/out2/** filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,5 @@
+__pycache__/
+*.pdf
+!戚蓼生序本石头记.pdf
+
+

ocr/.vscode/launch.json

@@ -0,0 +1,12 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python Debugger: Current File",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal"
+        }
+    ]
+}

ocr/draw_box.py

@@ -0,0 +1,48 @@
+
+import json
+import glob
+from pathlib import Path
+import cv2
+import numpy as np
+
+def draw_box(pth_webp, pth_boxs):
+
+    with open(pth_boxs, encoding='utf-8') as fp:
+        boxs = json.load(fp)
+        fp.close()
+
+    imgData = np.fromfile(pth_webp, dtype=np.uint8)
+    img = cv2.imdecode(imgData, cv2.IMREAD_UNCHANGED)
+
+    if len(img.shape) != 3:  # 转彩图
+        img_color = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)  # DBNet 原版只能处理彩图，这里转一下
+    else:
+        img_color = img.copy()
+
+
+    for box in boxs:
+        charPoly = box["charPoly"]
+        lu = [charPoly["x0"], charPoly["y0"]]
+        ru = [charPoly["x1"], charPoly["y1"]]
+        rd = [charPoly["x2"], charPoly["y2"]]
+        ld = [charPoly["x3"], charPoly["y3"]]
+        points = np.array([lu, ru, rd, ld])
+
+        cv2.polylines(img_color, [points], isClosed=True, color=(  # 多边形，框得比较全
+            100, 0, 255), thickness=2)  # 只画线，不填充
+        
+        # cv2.imshow("box", img_color)
+        # cv2.waitKey(0)
+
+    path_jpg = pth_webp.replace(".webp", ".jpg")
+    cv2.imwrite(path_jpg, img_color)
+
+def do_drawbox():
+    webps = glob.glob('./out2/*.webp', recursive=False)
+    for pth_webp in webps:
+        pth_box = pth_webp.replace(".webp", ".boxs")
+        draw_box(pth_webp, pth_box)
+
+if __name__ == "__main__":
+    do_drawbox()

ocr/find_paragraph.py

@@ -0,0 +1,56 @@
+"""
+Find paragraphs in loader response
+"""
+import time
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.support.ui import WebDriverWait
+import json
+
+options = webdriver.ChromeOptions()
+options.add_argument("--headless=new")
+options.add_argument("--no-sandbox")
+options.add_argument("--disable-dev-shm-usage")
+options.add_argument("--disable-blink-features=AutomationControlled")
+options.add_argument("user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36")
+options.add_experimental_option("excludeSwitches", ["enable-automation"])
+options.add_experimental_option("useAutomationExtension", False)
+options.set_capability("goog:loggingPrefs", {"performance": "ALL"})
+driver = webdriver.Chrome(options=options)
+driver.set_window_size(1400, 900)
+driver.execute_cdp_cmd("Network.enable", {})
+
+driver.get("https://www.shidianguji.com/zh/book/SWX0005")
+time.sleep(5)
+wait = WebDriverWait(driver, 10)
+try:
+    els = driver.find_elements(By.XPATH, "//*[contains(text(), '第二回')]")
+    if els:
+        print("Clicking 第二回")
+        driver.execute_script("arguments[0].click();", els[0])
+except Exception as e:
+    pass
+
+time.sleep(5)
+logs = driver.get_log("performance")
+for entry in logs:
+    msg = json.loads(entry["message"])["message"]
+    method = msg.get("method")
+    if method == "Network.responseReceived":
+        req_id = msg.get("params", {}).get("requestId")
+        url = msg.get("params", {}).get("response", {}).get("url", "")
+        if "__loader=__session" in url:
+            try:
+                body = driver.execute_cdp_cmd("Network.getResponseBody", {"requestId": req_id})
+                data = json.loads(body.get("body", ""))
+                print("Loader Response JSON keys:", list(data.keys()))
+                if "paragraphList" in data:
+                    print("Found paragraphList in Loader!")
+                    print("Type:", type(data["paragraphList"]))
+                    if isinstance(data["paragraphList"], list) and len(data["paragraphList"]) > 0:
+                        print("First item keys:", list(data["paragraphList"][0].keys()))
+                        print("First item content snippet:", str(data["paragraphList"][0])[:150])
+            except:
+                pass
+driver.quit()

ocr/gendatav2.py

@@ -0,0 +1,139 @@
+"""
+转换一章数据
+"""
+
+import os
+import shutil
+import json
+import glob
+from pathlib import Path
+import cv2
+import numpy as np
+
+from draw_box import do_drawbox
+
+
+def main():
+    dir_out2 = "out2"
+    if Path(dir_out2).exists():
+        shutil.rmtree(dir_out2)
+
+    if not Path(dir_out2).exists():
+        os.makedirs(dir_out2)
+
+    pageIds_pageNames = {}
+
+    raw_jsons = glob.glob('./out/raw/**/*.json', recursive=True)
+    box_jsons = {}
+    paragraphs = []
+    texts = ""
+    text_pages = {}
+    pages = []
+    for raw_json in raw_jsons:
+        if 'pages_200' in raw_json:
+            with open(raw_json, encoding='utf-8') as fp:
+                pages_json = json.load(fp)
+                page = pages_json["data"]["pages"]
+                pages += page
+                fp.close()
+        if 'paragraphs_200' in raw_json:
+            with open(raw_json, encoding='utf-8') as fp:
+                paragraphs_json = json.load(fp)
+                paragraphs += paragraphs_json["data"]["paragraphs"]
+                fp.close()
+        
+        if 'word_box_200' in raw_json:
+            with open(raw_json, encoding='utf-8') as fp:
+                word_box_json = json.load(fp)
+                box_jsons = {**box_jsons, **word_box_json["data"]["pageId2WordBoxContent"]}
+                fp.close()
+        
+    currPageId = -1
+    lastPageId = -1
+    currPageText = ""
+
+    for i, js in enumerate(paragraphs):
+        startPageId = js["startPageId"]
+        endPageId = js["endPageId"]
+        content = js["content"]
+        content = json.loads(content, strict=False )
+        lines = content["lines"]
+        lastLineNum = -1
+        for line in lines:
+            lineNum = line["lineNum"]
+            lineType = line["lineType"]
+            content_line = line["content"].replace('\ufeff', '').replace("\u3000", " ") #.replace(" ", "")   
+            if 'pagePass' in line:
+                pagePass = line["pagePass"]
+                PageId = pagePass["PageId"]
+
+                if currPageId == -1:
+                    currPageId = PageId
+
+                if currPageText:  # 页切换，保存上一页文本
+                    text_pages[currPageId] = currPageText
+                    currPageText = ""
+                    currPageId = PageId
+
+            
+            currPageText += content_line
+
+            texts += content_line
+
+        if i == len(paragraphs) - 1:
+            if currPageText:  # 最后一个段落，保存上一页文本
+                if currPageId not in text_pages:
+                    text_pages[currPageId] = currPageText
+                    currPageText = ""
+                    currPageId = PageId
+        else:
+            currPageText += " "
+            texts += " "
+        
+
+    # pages = pages_json["data"]["pages"]
+
+    for page in pages:
+        pageId = page["pageId"]
+        pageNum = page["pageNum"]
+        uri = page["uri"]
+        imageName = uri.split("-")[-1]
+        baseName = Path(imageName).stem
+        pth_img = Path("out/images") / imageName
+        if not pth_img.exists():
+            raise Exception(f"image {imageName} not found")
+        if pageId not in box_jsons:
+            raise Exception(f"pageId {pageId} no box_json")
+
+        pageIds_pageNames[pageId] = baseName
+        boxs = box_jsons[pageId]['wordBoxList']
+        pth_boxs = str( dir_out2 / Path( imageName.replace(".webp", ".boxs") ) )
+
+        shutil.copy(pth_img, str( dir_out2 / Path(imageName) ) )
+        with open(pth_boxs, 'w', encoding='utf-8') as fp:
+            json.dump(boxs, fp, indent=4, ensure_ascii=False)
+            fp.close()
+
+    pth_text_pages = str(Path(dir_out2) / "page_texts.json")
+    with open(pth_text_pages, 'w', encoding='utf-8') as fp:
+        json.dump(text_pages, fp, indent=4, ensure_ascii=False)
+        fp.close()
+
+    pth_pageIds_pageNames = str(Path(dir_out2) / "pageIds_pageNames.json")
+    with open(pth_pageIds_pageNames, 'w', encoding='utf-8') as fp:
+        json.dump(pageIds_pageNames, fp, indent=4, ensure_ascii=False)
+        fp.close()
+
+
+    pth_paragraphs = str(Path(dir_out2) / "paragraphs.json")
+    with open(pth_paragraphs, 'w', encoding='utf-8') as fp:
+        json.dump(paragraphs, fp, indent=4, ensure_ascii=False)
+        fp.close()
+    
+    do_drawbox()
+
+def do_gendata():
+    main()
+
+if __name__ == "__main__":
+    do_gendata()

ocr/getdata.py

@@ -0,0 +1,718 @@
+"""
+取一章数据
+"""
+import argparse
+import base64
+import json
+import re
+import time
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Dict, Iterable, List, Optional, Tuple
+
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.support.ui import WebDriverWait
+
+TARGET_PATTERNS = {
+    "paragraphs": re.compile(r"/api/ancientlib/read/book/paragraphs/v2(?:\?|$)"),
+    "pages": re.compile(r"/api/ancientlib/read/book/pages/v3/(?:\?|$)"),
+    "word_box": re.compile(r"/api/ancientlib/read/word-box-page-content/m-get/(?:\?|$)"),
+    "loader": re.compile(r"__loader=__session"),
+}
+
+IMAGE_URL_RE = re.compile(r"https?://[^ ]+(?:\.webp|\.image|\.png|\.jpe?g|\.bmp)(?:\?.*)?$", re.IGNORECASE)
+
+
+def _safe_name(s: str) -> str:
+    s = re.sub(r"[^a-zA-Z0-9._-]+", "_", s)
+    return s[:180] if len(s) > 180 else s
+
+
+def _json_loads_maybe(data: str) -> Optional[Any]:
+    try:
+        return json.loads(data)
+    except Exception:
+        return None
+
+
+def _iter_strings(obj: Any) -> Iterable[str]:
+    if isinstance(obj, str):
+        yield obj
+        return
+    if isinstance(obj, list):
+        for it in obj:
+            yield from _iter_strings(it)
+        return
+    if isinstance(obj, dict):
+        for v in obj.values():
+            yield from _iter_strings(v)
+
+
+def _extract_text_from_json(payload: Any) -> str:
+    if not isinstance(payload, (dict, list)):
+        return ""
+    chunks: List[str] = []
+
+    def walk(o: Any) -> None:
+        if isinstance(o, dict):
+            for k, v in o.items():
+                lk = str(k).lower()
+                if lk in {"text", "content", "paragraph", "para", "value", "word"} and isinstance(v, str):
+                    chunks.append(v)
+                else:
+                    walk(v)
+        elif isinstance(o, list):
+            for it in o:
+                walk(it)
+
+    walk(payload)
+    out = "\n".join(x.strip() for x in chunks if x and x.strip())
+    out = re.sub(r"\n{3,}", "\n\n", out)
+    return out.strip()
+
+
+def _find_image_urls(payload: Any) -> List[str]:
+    urls: List[str] = []
+    for s in _iter_strings(payload):
+        if s.startswith("http") and (".webp" in s or ".image" in s or "/page/" in s):
+            urls.append(s)
+    dedup: List[str] = []
+    seen = set()
+    for u in urls:
+        if u not in seen:
+            seen.add(u)
+            dedup.append(u)
+    return dedup
+
+
+def _maybe_decode_url(s: str) -> List[str]:
+    if not isinstance(s, str) or len(s) < 16:
+        return []
+    out: List[str] = []
+    try:
+        raw = base64.b64decode(s, validate=False)
+        txt = raw.decode("utf-8", errors="ignore")
+    except Exception:
+        return []
+    for m in re.finditer(r"https?://[^\\s\"']+", txt):
+        u = m.group(0)
+        if IMAGE_URL_RE.match(u) and ("byteimg.com" in u or "bytednsdoc.com" in u):
+            out.append(u)
+    return out
+
+
+def _extract_image_urls_from_pages(payload: Any) -> List[str]:
+    urls: List[str] = []
+    if not isinstance(payload, dict):
+        return urls
+    data = payload.get("data")
+    if not isinstance(data, dict):
+        return urls
+    pages = data.get("pages")
+    if not isinstance(pages, list):
+        return urls
+    for p in pages:
+        if not isinstance(p, dict):
+            continue
+        for key in ("picUrl", "thumbUrl"):
+            v = p.get(key)
+            if isinstance(v, str):
+                urls.extend(_maybe_decode_url(v))
+        for v in p.values():
+            if isinstance(v, str) and IMAGE_URL_RE.match(v) and ("byteimg.com" in v or "bytednsdoc.com" in v):
+                urls.append(v)
+    return list(dict.fromkeys(urls))
+
+
+def _guess_page_keys(payload: Any) -> List[Tuple[str, Any]]:
+    hits: List[Tuple[str, Any]] = []
+    if isinstance(payload, dict):
+        for k, v in payload.items():
+            lk = str(k).lower()
+            if lk in {"pageid", "page_id", "page"} and isinstance(v, (str, int)):
+                hits.append((str(k), v))
+            hits.extend(_guess_page_keys(v))
+    elif isinstance(payload, list):
+        for it in payload:
+            hits.extend(_guess_page_keys(it))
+    return hits
+
+
+@dataclass
+class CapturedResponse:
+    kind: str
+    url: str
+    request_id: str
+    status: int
+    mime_type: str
+    body_text: str
+
+    def json(self) -> Optional[Any]:
+        return _json_loads_maybe(self.body_text)
+
+
+def _make_driver(headless: bool) -> webdriver.Chrome:
+    options = webdriver.ChromeOptions()
+    if headless:
+        options.add_argument("--headless=new")
+    options.add_argument("--no-sandbox")
+    options.add_argument("--disable-dev-shm-usage")
+    options.add_argument("--disable-blink-features=AutomationControlled")
+    options.add_argument("user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36")
+    options.add_experimental_option("excludeSwitches", ["enable-automation"])
+    options.add_experimental_option("useAutomationExtension", False)
+    options.set_capability("goog:loggingPrefs", {"performance": "ALL"})
+    driver = webdriver.Chrome(options=options)
+    driver.execute_cdp_cmd("Network.enable", {})
+    return driver
+
+
+def _drain_network(
+    driver: webdriver.Chrome,
+    tracked: Dict[str, Tuple[str, str, int, str]],
+    ready: List[CapturedResponse],
+    image_urls: List[str],
+    img_dir: Path,
+    max_images: int,
+    img_saved: List[Dict[str, Any]],
+) -> None:
+    try:
+        logs = driver.get_log("performance")
+    except Exception:
+        return
+    for entry in logs:
+        try:
+            msg = json.loads(entry["message"])["message"]
+        except Exception:
+            continue
+        method = msg.get("method")
+        params = msg.get("params", {})
+        if method == "Network.requestWillBeSent":
+            request = params.get("request", {})
+            url = request.get("url", "")
+            if "00015" in url:
+                print(f"[DEBUG] Network.requestWillBeSent for 00015: url={url}")
+            if IMAGE_URL_RE.match(url) and ("byteimg.com" in url or "bytednsdoc.com" in url):
+                image_urls.append(url)
+        elif method == "Network.responseReceived":
+            response = params.get("response", {})
+            url = response.get("url", "")
+            mime_type = str(response.get("mimeType", "") or "")
+            if IMAGE_URL_RE.match(url) and ("byteimg.com" in url or "bytednsdoc.com" in url):
+                image_urls.append(url)
+            request_id = params.get("requestId")
+            if request_id and mime_type.startswith("image/") and IMAGE_URL_RE.match(url) and ("byteimg.com" in url or "bytednsdoc.com" in url):
+                status = int(response.get("status", 0) or 0)
+                tracked[request_id] = ("image", url, status, mime_type)
+                print(f"[DEBUG] Tracked image response: request_id={request_id}, url={url}, status={status}")
+                continue
+            elif request_id and "00015" in url:
+                print(f"[DEBUG] Found 00015 in url but didn't track as image. mime_type={mime_type}, url={url}, request_id={request_id}")
+            kind = None
+            for k, pat in TARGET_PATTERNS.items():
+                if pat.search(url):
+                    kind = k
+                    break
+            if not kind:
+                continue
+            request_id = params.get("requestId")
+            if not request_id:
+                continue
+            status = int(response.get("status", 0) or 0)
+            tracked[request_id] = (kind, url, status, mime_type)
+        elif method == "Network.loadingFinished":
+            request_id = params.get("requestId")
+            if not request_id or request_id not in tracked:
+                continue
+            kind, url, status, mime_type = tracked.pop(request_id)
+            try:
+                body = driver.execute_cdp_cmd("Network.getResponseBody", {"requestId": request_id})
+            except Exception as e:
+                if kind == "image":
+                    print(f"[DEBUG] Failed to get response body for image {url}: {e}")
+                continue
+            if kind == "image":
+                if max_images > 0 and len(img_saved) >= max_images:
+                    print(f"[DEBUG] Max images reached, skipping {url}")
+                    continue
+                raw = body.get("body", "")
+                if not raw:
+                    print(f"[DEBUG] Empty body for image {url}")
+                    continue
+                if body.get("base64Encoded"):
+                    try:
+                        data = base64.b64decode(raw)
+                    except Exception as e:
+                        print(f"[DEBUG] Failed to decode base64 for image {url}: {e}")
+                        continue
+                else:
+                    data = raw.encode("utf-8", errors="ignore")
+                ext = ".bin"
+                if "webp" in (mime_type or "").lower():
+                    ext = ".webp"
+                elif "png" in (mime_type or "").lower():
+                    ext = ".png"
+                elif "jpeg" in (mime_type or "").lower() or "jpg" in (mime_type or "").lower():
+                    ext = ".jpg"
+                
+                page_id = ""
+                m = re.search(r"/page/([^/]+)/", url)
+                if m:
+                    page_id = f"_{m.group(1)}"
+                else:
+                    m2 = re.search(r"1k[a-z0-9]{11}", url)
+                    if m2:
+                        page_id = f"_{m2.group(0)}"
+                
+                # Default file name format
+                file_name = f"{len(img_saved):04d}{page_id}{ext}"
+                
+                # Try to extract actual filename from URL, e.g. SWX0005_00001_00001.webp
+                m_name = re.search(r"-([a-zA-Z0-9_]+\.(?:webp|png|jpe?g|jpg|bmp))", url, re.IGNORECASE)
+                if m_name:
+                    file_name = m_name.group(1)
+                else:
+                    m_name2 = re.search(r"/([^/]+?\.(?:webp|png|jpe?g|jpg|bmp))(?:[?~]|$)", url, re.IGNORECASE)
+                    if m_name2:
+                        name_part = m_name2.group(1)
+                        if "-" in name_part:
+                            file_name = name_part.split("-", 1)[-1]
+                        else:
+                            file_name = name_part
+                
+                out_path = img_dir / file_name
+                try:
+                    out_path.write_bytes(data)
+                    print(f"[DEBUG] Saved image: {file_name} from {url}")
+                except Exception as e:
+                    print(f"[DEBUG] Failed to save image {file_name} from {url}: {e}")
+                    continue
+                img_saved.append({"url": url, "mimeType": mime_type, "path": str(out_path)})
+                continue
+
+            body_text = body.get("body", "")
+            if body.get("base64Encoded"):
+                try:
+                    body_text = base64.b64decode(body_text).decode("utf-8", errors="replace")
+                except Exception:
+                    body_text = ""
+                    
+            if kind == "loader":
+                try:
+                    data = json.loads(body_text)
+                    if "paragraphList" in data:
+                        para_payload = {
+                            "errorCode": 0,
+                            "errorMsg": "",
+                            "data": {
+                                "paragraphs": data["paragraphList"]
+                            }
+                        }
+                        body_text = json.dumps(para_payload, ensure_ascii=False)
+                        kind = "paragraphs"
+                        url = "https://www.shidianguji.com/api/ancientlib/read/book/paragraphs/v2?mock=from_loader"
+                        print(f"[DEBUG] Transformed loader response to paragraphs format")
+                except Exception as e:
+                    print(f"[DEBUG] Failed to parse loader JSON: {e}")
+
+            ready.append(
+                CapturedResponse(
+                    kind=kind,
+                    url=url,
+                    request_id=request_id,
+                    status=status,
+                    mime_type=mime_type,
+                    body_text=body_text,
+                )
+            )
+
+
+def _collect_dom_image_urls(driver: webdriver.Chrome) -> List[str]:
+    try:
+        urls = driver.execute_script(
+            "return Array.from(document.images||[]).map(i=>i.currentSrc||i.src).filter(Boolean);"
+        )
+    except Exception:
+        return []
+    if not isinstance(urls, list):
+        return []
+    out: List[str] = []
+    for u in urls:
+        if isinstance(u, str) and IMAGE_URL_RE.match(u) and ("byteimg.com" in u or "bytednsdoc.com" in u):
+            out.append(u)
+    return list(dict.fromkeys(out))
+
+
+def _try_click_by_text(driver: webdriver.Chrome, text: str, timeout_s: float = 2.5) -> bool:
+    xp = (
+        f"//*[self::button or self::a or @role='button' or self::div]"
+        f"[contains(normalize-space(.), {json.dumps(text, ensure_ascii=False)})]"
+    )
+    try:
+        els = driver.find_elements(By.XPATH, xp)
+    except Exception:
+        return False
+    for el in els[:5]:
+        try:
+            if not el.is_displayed() or not el.is_enabled():
+                continue
+            el.click()
+            return True
+        except Exception:
+            continue
+    return False
+
+
+def _enter_image_mode(driver: webdriver.Chrome) -> None:
+    for t in ("原图", "影印", "图片", "图像", "掃圖", "扫描", "切换"):
+        if _try_click_by_text(driver, t, timeout_s=0):
+            time.sleep(0.8)
+            break
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--book-id", default="SWX0005")
+    ap.add_argument("--chapter", default="第八十回")
+    ap.add_argument("--out", default="out")
+    ap.add_argument("--headless", action="store_true")
+    ap.add_argument("--timeout", type=int, default=20000)
+    ap.add_argument("--max-images", type=int, default=1000)
+    args = ap.parse_args()
+
+    out_dir = Path(args.out).resolve()
+    raw_dir = out_dir / "raw"
+    img_dir = out_dir / "images"
+    coord_dir = out_dir / "coords"
+    text_dir = out_dir / "text"
+    for d in (raw_dir, img_dir, coord_dir, text_dir):
+        d.mkdir(parents=True, exist_ok=True)
+
+    driver = _make_driver(headless=args.headless)
+    driver.set_window_size(1400, 900)
+    captured: List[CapturedResponse] = []
+    tracked: Dict[str, Tuple[str, str, int, str]] = {}
+    image_urls: List[str] = []
+    img_saved: List[Dict[str, Any]] = []
+    try:
+        url = f"https://www.shidianguji.com/zh/book/{args.book_id}"
+        driver.get(url)
+        
+        # Drain network to capture the initial chapter data
+        for _ in range(5):
+            time.sleep(1)
+            before = len(captured)
+            _drain_network(driver, tracked, captured, image_urls, img_dir, int(args.max_images), img_saved)
+            if len(captured) == before and any(c.kind in ("paragraphs", "pages") for c in captured):
+                break
+
+        initial_captured = list(captured)
+        initial_img_saved = list(img_saved)
+        initial_image_urls = list(image_urls)
+        
+        captured.clear()
+        img_saved.clear()
+        image_urls.clear()
+        tracked.clear()
+
+        clicked = False
+        no_scroll_count = 0
+        for scroll_attempts in range(400):
+            try:
+                els = driver.find_elements(By.LINK_TEXT, args.chapter)
+                if not els:
+                    els = driver.find_elements(By.PARTIAL_LINK_TEXT, args.chapter)
+                if not els:
+                    xp = f"//*[contains(normalize-space(.), {json.dumps(args.chapter, ensure_ascii=False)}) and not(.//*[contains(normalize-space(.), {json.dumps(args.chapter, ensure_ascii=False)})])]"
+                    els = driver.find_elements(By.XPATH, xp)
+                    
+                for el in els:
+                    try:
+                        driver.execute_script("arguments[0].scrollIntoView({block: 'center'});", el)
+                        time.sleep(0.2)
+                        try:
+                            el.click()
+                            clicked = True
+                            break
+                        except Exception:
+                            # Try JS click as fallback if standard click fails
+                            driver.execute_script("arguments[0].click();", el)
+                            clicked = True
+                            break
+                    except Exception:
+                        continue
+            except Exception:
+                pass
+                
+            if clicked:
+                break
+                
+            # 如果没找到或没点击成功，滚动所有可滚动的 div，尝试让章节列表显示出来
+            try:
+                scrolled = driver.execute_script('''
+                    var els = document.querySelectorAll("div, ul, main, nav, section, aside");
+                    var scrolledAny = false;
+                    for (var i = 0; i < els.length; i++) {
+                        var d = els[i];
+                        if (d.scrollHeight > d.clientHeight && window.getComputedStyle(d).overflowY !== "hidden") {
+                            var before = d.scrollTop;
+                            d.scrollBy(0, 250);
+                            if (d.scrollTop > before) {
+                                scrolledAny = true;
+                            }
+                        }
+                    }
+                    return scrolledAny;
+                ''')
+                if not scrolled:
+                    no_scroll_count += 1
+                    if no_scroll_count >= 20:
+                        print(f"[DEBUG] Reached the bottom of the list (tried 20 times). {args.chapter} not found.")
+                        break
+                else:
+                    no_scroll_count = 0
+            except Exception:
+                pass
+            time.sleep(0.5)
+        
+        if clicked:
+            print(f"[DEBUG] Clicked {args.chapter}, waiting for new network data...")
+            # Wait until we see new 'paragraphs' or 'pages' in captured
+            for _ in range(15):
+                time.sleep(1)
+                _drain_network(driver, tracked, captured, image_urls, img_dir, int(args.max_images), img_saved)
+                if any(c.kind in ("paragraphs", "pages") for c in captured):
+                    print(f"[DEBUG] New data captured for {args.chapter}")
+                    break
+        else:
+            print(f"[DEBUG] {args.chapter} not clicked (not found).")
+            
+        has_new_data = any(c.kind in ("paragraphs", "pages") for c in captured)
+        
+        if not has_new_data:
+            if clicked:
+                print(f"[DEBUG] No new data loaded after clicking {args.chapter}. Using initial chapter data.")
+            else:
+                print(f"[DEBUG] Using initial chapter data because {args.chapter} was not found.")
+            captured.extend(initial_captured)
+            img_saved.extend(initial_img_saved)
+            image_urls.extend(initial_image_urls)
+        else:
+            print(f"[DEBUG] Successfully loaded new chapter {args.chapter}. Discarding initial chapter data.")
+            for img in initial_img_saved:
+                try:
+                    Path(img["path"]).unlink(missing_ok=True)
+                except Exception as e:
+                    print(f"[DEBUG] Failed to delete initial image {img['path']}: {e}")
+
+        time.sleep(0.8)
+        _enter_image_mode(driver)
+
+        deadline = time.time() + max(10, int(args.timeout))
+        last_activity = time.time()
+        no_activity_count = 0
+        print(f"Starting loop, deadline in {deadline - time.time()} seconds")
+        
+        # Try to find a scrollable container
+        from selenium.webdriver.common.keys import Keys
+        
+        while time.time() < deadline:
+            before_cap = len(captured)
+            before_img = len(img_saved)
+            _drain_network(driver, tracked, captured, image_urls, img_dir, int(args.max_images), img_saved)
+            if len(captured) != before_cap or len(img_saved) != before_img:
+                print(f"Activity! captured: {len(captured)} (+{len(captured)-before_cap}), img_saved: {len(img_saved)} (+{len(img_saved)-before_img})")
+                last_activity = time.time()
+                no_activity_count = 0
+            
+            # Send PAGE_DOWN to body
+            try:
+                driver.find_element(By.TAG_NAME, "body").send_keys(Keys.PAGE_DOWN)
+            except Exception:
+                pass
+                
+            # Click next page if possible
+            try:
+                # The user indicated: <div class="vik-toolbox-btn click act" type="page-next">
+                next_btn = driver.find_element(By.XPATH, "//div[@type='page-next' or contains(@class, 'page-next') or contains(text(), '下一张')]")
+                # Add a small delay to prevent clicking too fast which might skip pages
+                # Check if we're not loading something
+                if next_btn.is_displayed():
+                    # Check if button is disabled (has disable class)
+                    cls = next_btn.get_attribute("class") or ""
+                    if "disable" not in cls:
+                        # Find current page text to ensure we only click once page changes
+                        page_text_el = driver.find_elements(By.XPATH, "//div[contains(text(), '/')]")
+                        curr_text = ""
+                        for p in page_text_el:
+                            if "/" in p.text:
+                                curr_text = p.text
+                                break
+                        driver.execute_script("arguments[0].click();", next_btn)
+                        # Wait for page to change
+                        for _ in range(10):
+                            time.sleep(0.2)
+                            new_text = ""
+                            for p in driver.find_elements(By.XPATH, "//div[contains(text(), '/')]"):
+                                if "/" in p.text:
+                                    new_text = p.text
+                                    break
+                            if new_text != curr_text:
+                                break
+            except Exception:
+                pass
+                
+            # Also try to scroll window and any potential scrollable divs
+            driver.execute_script('''
+                window.scrollBy(0, 900);
+                var divs = document.querySelectorAll("div");
+                for (var i = 0; i < divs.length; i++) {
+                    if (divs[i].scrollHeight > divs[i].clientHeight && window.getComputedStyle(divs[i]).overflowY !== "hidden") {
+                        divs[i].scrollBy(0, 900);
+                    }
+                }
+            ''')
+            
+            time.sleep(0.6)
+            image_urls.extend(_collect_dom_image_urls(driver))
+            if time.time() - last_activity > 15:
+                no_activity_count += 1
+                print(f"No activity for 15 seconds (count: {no_activity_count}).")
+                if no_activity_count >= 3:
+                    print("Too many consecutive periods of no activity, breaking loop.")
+                    break
+                    
+                # Check if next button is actually disabled
+                try:
+                    next_btn = driver.find_element(By.XPATH, "//div[@type='page-next' or contains(@class, 'page-next') or contains(text(), '下一张')]")
+                    cls = next_btn.get_attribute("class") or ""
+                    if "disable" in cls:
+                        print("Reached end of chapter (next button disabled).")
+                        break
+                    else:
+                        print("Next button not disabled, but no network activity. Try clicking again.")
+                        driver.execute_script("arguments[0].click();", next_btn)
+                        last_activity = time.time() - 10 # give it 5 more seconds before checking again
+                        continue
+                except Exception:
+                    print("Could not find next button, breaking loop.")
+                    break
+                break
+        print(f"Loop finished. time.time() < deadline: {time.time() < deadline}")
+        
+        for i, c in enumerate(captured):
+            ext = "json" if "json" in (c.mime_type or "") or c.body_text.strip().startswith("{") else "txt"
+            name = _safe_name(f"{i:04d}_{c.kind}_{c.status}_{c.url}")
+            (raw_dir / f"{name}.{ext}").write_text(c.body_text, encoding="utf-8", errors="replace")
+
+        img_urls = list(dict.fromkeys([u for u in image_urls if u.startswith("http")]))
+        pages_payloads = [c.json() for c in captured if c.kind == "pages" and c.status == 200]
+        
+        page_id_to_hash = {}
+        for p in pages_payloads:
+            if p is not None:
+                img_urls.extend(_extract_image_urls_from_pages(p))
+                # Build pageId -> hash mapping
+                if isinstance(p, dict) and isinstance(p.get("data"), dict):
+                    pages_list = p["data"].get("pages", [])
+                    if isinstance(pages_list, list):
+                        for page in pages_list:
+                            if isinstance(page, dict):
+                                pid = str(page.get("pageId", ""))
+                                uri = str(page.get("uri", ""))
+                                if pid and uri:
+                                    m = re.search(r"/page/([^/]+)/", uri)
+                                    if m:
+                                        page_id_to_hash[pid] = m.group(1)
+                                    else:
+                                        m2 = re.search(r"1k[a-z0-9]{11}", uri)
+                                        if m2:
+                                            page_id_to_hash[pid] = m2.group(0)
+
+        img_urls = list(dict.fromkeys(img_urls))
+
+        coords: Dict[str, Any] = {}
+        for c in captured:
+            if c.kind != "word_box" or c.status != 200:
+                continue
+            payload = c.json()
+            if payload is None:
+                continue
+            
+            page_id = None
+            # Extract pageId directly from pageId2WordBoxContent if available
+            if isinstance(payload, dict) and isinstance(payload.get("data"), dict):
+                content = payload["data"].get("pageId2WordBoxContent")
+                if isinstance(content, dict) and content:
+                    page_id = str(next(iter(content.keys())))
+            
+            if not page_id:
+                page_keys = _guess_page_keys(payload)
+                for _, v in page_keys:
+                    if isinstance(v, (str, int)):
+                        page_id = str(v)
+                        break
+                        
+            hash_suffix = ""
+            if page_id and page_id in page_id_to_hash:
+                hash_suffix = f"_{page_id_to_hash[page_id]}"
+                
+            key = f"wordbox_{len(coords):04d}{hash_suffix}"
+            coords[key] = payload
+            (coord_dir / f"{_safe_name(key)}.json").write_text(
+                json.dumps(payload, ensure_ascii=False),
+                encoding="utf-8",
+                errors="replace",
+            )
+
+        paragraph_texts: List[str] = []
+        for c in captured:
+            if c.kind != "paragraphs" or c.status != 200:
+                continue
+            payload = c.json()
+            if payload is None:
+                continue
+            t = _extract_text_from_json(payload)
+            if t:
+                paragraph_texts.append(t)
+        full_text = "\n\n".join(paragraph_texts).strip()
+        if not full_text and coords:
+            fallback_chunks: List[str] = []
+            for v in coords.values():
+                t = _extract_text_from_json(v)
+                if t:
+                    fallback_chunks.append(t)
+            full_text = "\n\n".join(fallback_chunks).strip()
+
+        if full_text:
+            (text_dir / "text.txt").write_text(full_text, encoding="utf-8", errors="replace")
+
+        summary = {
+            "bookId": args.book_id,
+            "chapter": args.chapter,
+            "captured": [
+                {"kind": c.kind, "status": c.status, "mimeType": c.mime_type, "url": c.url}
+                for c in captured
+            ],
+            "imageUrls": img_urls[: max(0, int(args.max_images))],
+            "imagesSaved": img_saved,
+            "coords_keys": list(coords.keys()),
+            "out": str(out_dir),
+        }
+        (out_dir / "summary.json").write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
+        return 0
+    finally:
+        try:
+            driver.quit()
+            from gendatav2 import do_gendata
+            do_gendata()
+        except Exception:
+            pass
+
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
+

ocr/kandianguji_ocr.py

@@ -0,0 +1,98 @@
+import os
+import base64
+import json
+import requests
+
+API_URL = "https://ocr.kandianguji.com/ocr_api"
+TOKEN = "8be3d75a-8a66-4b5d-9047-d4895e4c8000"
+EMAIL = "13788325535"
+
+def get_kandianguji_ocr_result(image_path: str, **kwargs):
+    """
+    调用看典古籍OCR API识别图像。
+    
+    参数:
+        image_path (str): 需要识别的图像文件路径。
+        **kwargs: 其他可选API参数 (如 version='v2', det_layout=True 等)。
+                  详细参数请参考 readme.txt 文档。
+                  
+    返回:
+        dict: API响应的JSON数据。
+    """
+    if not os.path.exists(image_path):
+        raise FileNotFoundError(f"指定的图像文件不存在: {image_path}")
+
+    # 1. 将图像转换为base64编码
+    with open(image_path, "rb") as img_file:
+        image_base64 = base64.b64encode(img_file.read()).decode('utf-8')
+
+    # 2. 构建基础请求数据
+    payload = {
+        "token": TOKEN,
+        "email": EMAIL,
+        "image": image_base64
+    }
+    
+    # 3. 合并可选参数
+    # 根据 readme.txt 提取的默认可选参数
+    default_options = {
+        "char_ocr": True,
+        "det_mode": "sp",
+        "det_layout": True,
+        "image_size": 0,
+        "return_position": True,
+        "return_choices": True,
+        "version": "v2",
+        "only_plain_text": False,
+        "return_layout": True,
+        "auto_insert_space": False,
+        "hp_line_words_angel": "left2right",
+        "sp_line_words_angel": "top2bottom"
+    }
+    
+    # 更新默认参数（如果 kwargs 中提供了新的值）
+    for key, value in default_options.items():
+        payload[key] = kwargs.get(key, value)
+
+    # 4. 发送POST请求
+    headers = {
+        "Content-Type": "application/json"
+    }
+    
+    try:
+        response = requests.post(API_URL, json=payload, headers=headers)
+        # 检查响应状态码
+        response.raise_for_status()
+        return response.json()
+    except requests.exceptions.RequestException as e:
+        print(f"API请求失败: {e}")
+        # 如果有响应体，打印出来以便调试
+        if 'response' in locals() and response is not None:
+            print(f"响应内容: {response.text}")
+        return None
+
+if __name__ == "__main__":
+    # 测试用例 (请替换为真实的古籍图片路径)
+    sample_image = "0375.jpg"
+    
+    print("看典古籍OCR API 接口测试")
+    print("-" * 30)
+    
+    if os.path.exists(sample_image):
+        print(f"正在识别图片: {sample_image}")
+        # 调用示例，可按需传入 v2 版本的特有参数
+        result = get_kandianguji_ocr_result(
+            sample_image, 
+            version="v2", 
+            det_layout=True
+        )
+        
+        if result:
+            print("\n识别结果:")
+            s = json.dumps(result, indent=2, ensure_ascii=False)
+            with open("out.json", 'w', encoding='utf-8') as f:
+                f.write(s)  
+            print(s)
+    else:
+        print(f"提示: 请在当前目录下放置一张名为 '{sample_image}' 的图片用于测试。")
+        print("或者修改 sample_image 变量的值指向有效的图片路径。")

ocr/ppcor_aliocr_convert.py

@@ -0,0 +1,501 @@
+"""
+# pip install numpy==1.23.5 opencv-python==4.10.0.84 -i https://mirrors.aliyun.com/pypi/simple/
+
+PPOCRLabel --lang ch  # 启动标注工具
+
+cp autodl-tmp/train_data.zip . && \
+unzip train_data.zip -d PaddleOCR
+
+# https://github.com/PaddlePaddle/PaddleOCR/blob/static/doc/doc_ch/FAQ.md
+
+# 7za a -t7z -m0=lzma -mx=9 -mfb=64 -md=32m -ms=on data.7z data/
+
+新建文件夹 train_data, 要标注的图片全部放在里面
+
+新建 train_data/Label.txt 内容如下
+行中用 \t 分隔 , points 的标记顺序是 左上 右上  右下 左下
+train_data/0093.bmp	[{"transcription":"参考答案及解析","points":[[525,179],[1295,167],[1295,268],[521,292]],"difficult":false}]
+train_data/0094.bmp	[{"transcription":"其他内容","points":[[525,179],[1295,167],[1295,268],[521,292]],"difficult":false}]
+
+
+给 PaddleOCR 用，前面是坐标和图片都变换；这里图像不变，坐标不变
+
+
+将阿里OCR 的识别结果（图片和标注）转换成 icdar2015 格式 (注意：它的文本是含 utf8 bom 的)
+
+给 mmocr 训练用。格式是 icdar2015 的格式，文件夹的组织方式是按照 mmocr 的要求创建的
+
+"""
+
+
+"""
+
+! unzip ./GD500.zip -d DB/datasets
+
+icdar2015 文本检测数据集
+标注格式: x1,y1,x2,y2,x3,y3,x4,y4,text
+
+其中, x1,y1为左上角坐标,x2,y2为右上角坐标,x3,y3为右下角坐标,x4,y4为左下角坐标。
+
+# 表示text难以辨认。
+"""
+
+import random
+from pathlib import Path
+import os
+import shutil
+import glob
+import base64
+from importlib.resources import path
+import math
+import numpy as np
+import cv2
+import json
+import decimal
+import datetime
+from pickletools import uint8
+class DecimalEncoder(json.JSONEncoder):
+    def default(self, o):
+        if isinstance(o, decimal.Decimal):
+            return float(o)
+        elif isinstance(o, datetime.datetime):
+            return str(o)
+        super(DecimalEncoder, self).default(o)
+
+
+def save_json(filename, dics):
+    with open(filename, 'w', encoding='utf-8') as fp:
+        json.dump(dics, fp, indent=4, cls=DecimalEncoder, ensure_ascii=False)
+        fp.close()
+
+
+def load_json(filename):
+    with open(filename, encoding='utf-8') as fp:
+        js = json.load(fp)
+        fp.close()
+        return js
+
+# convert string to json
+
+
+def parse(s):
+    return json.loads(s, strict=False)
+
+# convert dict to string
+
+
+def string(d):
+    return json.dumps(d, cls=DecimalEncoder, ensure_ascii=False)
+
+
+def transform(points, M):
+    # points 算出四个点变换后移动到哪里了
+    # points = np.array([[word_x,  word_y],              # 左上
+    #                    [word_x + word_width, word_y],                 # 右上
+    #                    [word_x + word_width, word_y + word_height],  # 右下
+    #                    [word_x, word_y + word_height],  # 左下
+    #                    ])
+    # add ones
+    ones = np.ones(shape=(len(points), 1))
+
+    points_ones = np.hstack([points, ones])
+
+    # transform points
+    transformed_points = M.dot(points_ones.T).T
+
+    transformed_points_int = np.round(
+        transformed_points, decimals=0).astype(np.int32)  # 批量四舍五入
+
+    return transformed_points_int
+
+
+def cutPoly(img, pts):
+    # img = cv2.imdecode(np.fromfile('./t.png', dtype=np.uint8), -1)
+    # pts = np.array([[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]])
+
+    # (1) Crop the bounding rect
+    rect = cv2.boundingRect(pts)
+    x, y, w, h = rect
+    croped = img[y:y+h, x:x+w].copy()
+
+    # (2) make mask
+    pts = pts - pts.min(axis=0)
+
+    mask = np.zeros(croped.shape[:2], np.uint8)
+    cv2.drawContours(mask, [pts], -1, (255, 255, 255), -1, cv2.LINE_AA)
+
+    # (3) do bit-op
+    dst = cv2.bitwise_and(croped, croped, mask=mask)
+
+    # (4) add the white background
+    bg = np.ones_like(croped, np.uint8)*255
+    cv2.bitwise_not(bg, bg, mask=mask)
+    dst2 = bg + dst
+
+    # cv2.imwrite("croped.png", croped)
+    # cv2.imwrite("mask.png", mask)
+    # cv2.imwrite("dst.png", dst)
+    # cv2.imwrite("dst2.png", dst2)
+
+    return dst2
+
+
+def md5(fname):
+    import hashlib
+    hash_md5 = hashlib.md5()
+    with open(fname, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+def get_all_md5():
+    m5s = []
+    import glob
+    jpgs = glob.glob('./bookimage/**/*.jpg', recursive=True)
+    for jpg in jpgs:
+       m5 = md5(jpg)
+       m5s.append( m5 )
+    return m5s
+
+def get_json_paths():
+    json_paths = []
+    m5s = get_all_md5()
+    for m5 in m5s:
+        j_pth = f"/yingedu/project/ocr_server_test/data/json/{m5.lower()}.json"
+        if os.path.exists(j_pth):
+            json_paths.append(j_pth)
+    return json_paths
+
+def do_convert_aliocr():
+
+    # 24HLZYZG64/0001.jpg c04d111ef69b9892d39f9430b6906047 md5是这个
+        # ls /yingedu/project/ocr_server_test/data/json/0bf0383ece9a533683e615bf57525812.json  aliocr 原始识别结果
+        # ls /yingedu/project/ocr_server_test/data/img/0bf0383ece9a533683e615bf57525812.txt    aliocr 原始识别图像（二值化降燥后压缩成2M）
+
+
+
+    root = 'train_data'
+    tmp = 'tmp'
+    label_path = os.path.join(root, 'Label.txt')
+    
+    key_path = os.path.join(root, 'keys.txt')
+
+    fileState_path = os.path.join(root, 'fileState.txt')
+
+    if os.path.exists(root):
+        shutil.rmtree(root)
+        # os.rmdir(root)
+    if os.path.exists(tmp):
+        shutil.rmtree(tmp)
+
+    if not os.path.exists(root):
+        os.makedirs(root)
+
+    if not os.path.exists(tmp):
+        os.makedirs(tmp)
+
+    label = ''
+    keys = ''
+    states = ''
+
+
+    dic_words = {}  # 所有词
+
+    # 开始转换
+
+    # https://help.aliyun.com/document_detail/294540.html 阿里云ocr结果字段定义
+    # prism-wordsInfo 里的 angle 文字块的角度，这个角度只影响width和height，当角度为-90、90、-270、270，width和height的值需要自行互换
+
+    dir_json = './测试图片/json' # '/yingedu/project/ocr_server_test/data/json' # './data/json'  
+    dir_img = './测试图片/img' # '/yingedu/project/ocr_server_test/data/img'        # './data/img'  
+
+    g_count = 1
+    g_count2 = 1
+
+
+    json_paths = glob.glob('{}/*.json'.format(dir_json), recursive=False)
+
+
+    #json_paths = get_json_paths()
+
+    for json_path in json_paths:
+
+        arr = []
+
+        base = Path(json_path).stem
+
+        # if base == '0bf0383ece9a533683e615bf57525812':
+        #     continue
+
+        img_path = os.path.join(dir_img, '{}.txt'.format(base))
+
+        if not os.path.exists(img_path):  # 没有相应的图片，可能被删除了
+            print(f'Warnnig: no image {img_path}')
+            continue
+
+        jsn = load_json(json_path)
+
+        if not ('prism_wordsInfo' in jsn):
+            print(f'Warning: no charater in {img_path}')
+            continue
+
+        with open(img_path, "r", encoding="utf-8") as fp:
+            imgdata = fp.read()
+            imgdata = base64.b64decode(imgdata)
+            imgdata = np.frombuffer(imgdata, np.uint8)
+            img = cv2.imdecode(imgdata, cv2.IMREAD_UNCHANGED)
+
+            # cv2.imshow('img', img)
+            # cv2.waitKey(0)
+
+        if len(img.shape) != 3:  # 转彩图
+            img_color = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+            img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)  # DBNet 原版只能处理彩图，这里转一下
+
+        else:
+            img_color = img.copy()
+
+        img_color_origin = img_color.copy()
+        img_color_origin2 = img_color.copy()
+
+        name = f'{g_count}.jpg'
+        dst_img_path = f'{root}/{name}'
+        states += f'G:\\train_data\\{name}\t1\n'
+        g_count += 1
+
+        cv2.imwrite(dst_img_path, img)
+
+        wordsInfo = jsn['prism_wordsInfo']
+        for j in range(len(wordsInfo)):
+            jo = wordsInfo[j]
+            word = jo["word"]
+
+            for w in list(word):
+                if not (w in dic_words):
+                    dic_words[w] = True
+
+            # prism-wordsInfo 里的 angle 文字块的角度，这个角度只影响width和height，当角度为-90、90、-270、270，width和height的值需要自行互换
+            angle = jo['angle']
+
+            img_color = img_color_origin.copy()
+
+            word_x = jo['x']
+            word_y = jo['y']
+            word_width = jo['width']
+            word_height = jo['height']
+
+            if abs(angle) == 90 or abs(angle) == 270:
+                word_width = jo['height']
+                word_height = jo['width']
+            elif angle != 0:
+
+                # 变换前画出绿框，方便追踪点的前后变化
+                # img_color = cv2.rectangle(img_color, (word_x, word_y), (
+                #     word_x + word_width, word_y + word_height), (0, 255, 0), 2)  # 矩形的左上角, 矩形的右下角
+
+                # cv2.imshow("green", img_color)
+                # cv2.waitKey(0)
+
+                # 变换前的多边形蓝框
+                points = np.array([
+                    [word_x,  word_y],                             # 左上
+                    [word_x + word_width, word_y],                 # 右上
+                    [word_x + word_width, word_y + word_height],  # 右下
+                    [word_x, word_y + word_height],                # 左下
+                ])
+
+                # # cv2.fillPoly(img_color, pts=[points], color=(255, 0, 0)) # 填充
+                # cv2.polylines(img_color, [points], isClosed=True, color=(
+                #     255, 0, 0), thickness=1)  # 只画线，不填充
+
+                # cv2.imshow("polys", img_color)
+                # cv2.waitKey(0)
+
+                # 获取图像的维度，并计算中心
+                (h, w) = img_color.shape[:2]
+                (cX, cY) = (w // 2, h // 2)
+
+                # - (cX,cY): 旋转的中心点坐标
+                # - 180: 旋转的度数，正度数表示逆时针旋转，而负度数表示顺时针旋转。
+                # - 1.0：旋转后图像的大小，1.0原图，2.0变成原来的2倍，0.5变成原来的0.5倍
+                # 1° = π/180弧度   1 弧度 =  180 / 3.1415926   // 0.0190033 是Mathematica 算出来的弧度，先转换成角度  // -0.0190033 * (180 / 3.1415926)
+                M = cv2.getRotationMatrix2D((cX, cY), angle, 1.0)
+                img_color = cv2.warpAffine(img_color, M, (w, h))
+                img_color_transform = img_color.copy()
+
+                # cv2.imshow("after trans", img_color)
+                # cv2.waitKey(0)
+
+                # https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.html  # 原理
+                # https://stackoverflow.com/questions/30327659/how-can-i-remap-a-point-after-an-image-rotation # How can I remap a point after an image rotation?
+                # 如何得到移动后的坐标点
+
+                # points 算出四个点变换后移动到哪里了
+                points = np.array([[word_x,  word_y],              # 左上
+                                   # 右上
+                                   [word_x + word_width, word_y],
+                                   [word_x + word_width, word_y + \
+                                       word_height],  # 右下
+                                   [word_x, word_y + word_height],  # 左下
+                                   ])
+                # add ones
+                ones = np.ones(shape=(len(points), 1))
+
+                points_ones = np.hstack([points, ones])
+
+                # transform points
+                transformed_points = M.dot(points_ones.T).T
+
+                transformed_points_int = np.round(
+                    transformed_points, decimals=0).astype(np.int32)  # 批量四舍五入
+
+                # cv2.polylines(img_color, [transformed_points_int], isClosed=True, color=(
+                #     0, 0, 255), thickness=2)  # 画转换后的点
+
+                # cv2.polylines(img_color_origin, [points], isClosed=True, color=(
+                #     random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)), thickness=2)  # 画转换前的点
+
+                # cv2.imshow("orgin", img_color_origin)
+                # cv2.waitKey(0)
+
+            # 四个角的位置 # 左上、右上、右下、左下，当NeedRotate为true时，如果最外层的angle不为0，需要按照angle矫正图片后，坐标才准确（错，经验证不需要）
+            pos = jo["pos"]
+            x = int(pos[0]["x"])  # 左上
+            y = int(pos[0]["y"])
+
+            x2 = int(pos[2]["x"])  # 右下
+            y2 = int(pos[2]["y"])
+
+            lu = [pos[0]['x'], pos[0]['y']]  # left up  四个角顺时针方向数
+            ru = [pos[1]['x'], pos[1]['y']]
+            rd = [pos[2]['x'], pos[2]['y']]
+            ld = [pos[3]['x'], pos[3]['y']]
+
+            # 生成 icdar2015 格式的人工标记训练数据（用于训练 mmocr）
+            # gt_txt_list.append( "{},{},{},{},{},{},{},{},{}".format(lu[0], lu[1], ru[0], ru[1], rd[0], rd[1], ld[0], ld[1], word) )
+
+            # 绘制矩形
+            start_point = (x, y)  # 矩形的左上角
+
+            end_point = (x2, y2)  # 矩形的右下角
+
+            color = (0, 0, 255)  # BGR
+
+            thickness = 2
+
+            # 逐行画框
+            # img_color_origin2 = cv2.rectangle(img_color_origin2, start_point, end_point, color, thickness)
+            # cv2.imshow("box", img_color_origin2)
+
+            # cv2.waitKey(0)
+
+            points = [lu, ru, rd, ld]
+
+            points0 = np.array([[word_x,  word_y],              # 左上
+                                  # 右上
+                                  [word_x + word_width, word_y],
+                                    [word_x + word_width, word_y + \
+                                     word_height],  # 右下
+                                    [word_x, word_y + word_height],  # 左下
+                                  ])
+            points1 = np.array([lu, ru, rd, ld])
+
+            if not (abs(angle) == 90 or abs(angle) == 270) and angle != 0:
+                points = transform(points, M)
+            else:
+                points = np.array(points)
+
+            ps3 = np.array(
+                [
+                    [min(points[0][0], points1[0][0]), min(
+                        points[0][1], points1[0][1])],  # 左上(取最两者中最小的)
+
+                    [max(points[1][0], points1[1][0]), min(
+                        points[1][1], points1[1][1])],  # 右上
+
+                    [max(points[2][0], points1[2][0]), max(
+                        points[2][1], points1[2][1])],  # 右下
+
+                    [min(points[3][0], points1[3][0]), max(
+                        points[3][1], points1[3][1])]  # 左下
+                ]
+            )
+
+            # img_cuted = cutPoly(img, points1)
+            # cv2.imwrite(f'./tmp/{g_count2}.jpg', img_cuted)
+            # with open(f'./tmp/{g_count2}.txt', 'w', encoding='utf-8') as f:
+            #     f.write(word)
+            # g_count2 += 1
+
+            # cv2.polylines(img_color_origin, [points], isClosed=True, color=(   # 多边形，框得比较全
+            #     100, 0, 255), thickness=2)  # 只画线，不填充
+
+            
+            arr.append( {"transcription":f"{word}","points":[lu, ru, rd, ld],"difficult":False} )
+
+
+            cv2.polylines(img_color_origin, [points1], isClosed=True, color=(
+                random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)), thickness=2)  # 画转换前的点
+
+            # cv2.polylines(img_color_origin, [ps3], isClosed=True, color=(255, 0, 0), thickness=2)
+
+            # cv2.imshow("orgin", img_color_origin)
+            # cv2.waitKey(0)
+
+            # break
+
+
+        arr_str = string(arr)
+        line = f'{dst_img_path}\t{arr_str}\n'
+        label += line
+
+        print( f'{g_count - 1} / {len(json_paths)} task done.' )
+
+    ks = list( dic_words.keys() )
+
+    keys = '\n'.join(ks)
+
+    with open(label_path, "w", encoding='utf-8') as fp:
+        fp.write(label)
+
+    with open(key_path, "w", encoding='utf-8') as fp:
+        fp.write(keys)
+
+    with open(fileState_path, "w", encoding='utf-8') as fp:
+        fp.write(states)
+
+    print('all task done.')
+
+def show_box_shidianguji(pth_img):
+    imgData = np.fromfile(pth_img, dtype=np.uint8)
+    img = cv2.imdecode(imgData, cv2.IMREAD_UNCHANGED)
+    
+    if len(img.shape) != 3:  # 转彩图
+        img_color = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)  # DBNet 原版只能处理彩图，这里转一下
+    else:
+        img_color = img.copy()
+
+
+    charPoly = {
+        "x0": 537, "y0": 67, "x1": 578, "y1": 66, "x2": 578, "y2": 122, "x3": 537,"y3": 123
+    }
+    
+    lu = [charPoly["x0"], charPoly["y0"]]
+    ru = [charPoly["x1"], charPoly["y1"]]
+    rd = [charPoly["x2"], charPoly["y2"]]
+    ld = [charPoly["x3"], charPoly["y3"]]
+    points = np.array([lu, ru, rd, ld])
+
+    cv2.polylines(img_color, [points], isClosed=True, color=(  # 多边形，框得比较全
+        100, 0, 255), thickness=2)  # 只画线，不填充
+
+    cv2.imshow("box", img_color)
+    cv2.waitKey(0)
+
+    pass
+
+if __name__ == "__main__":
+    # do_convert_aliocr()
+    show_box_shidianguji("out/images/0000_1kzz90e16h5ic.webp")
+    pass

ocr/qwen_ocr.py

@@ -0,0 +1,43 @@
+# 如果没有安装OpenAI Python SDK，可使用命令安装：pip install OpenAI
+
+import base64
+from openai import OpenAI
+
+# 读取图片并转为 base64
+image_path = "0375.jpg"
+with open(image_path, "rb") as f:
+    image_data = base64.b64encode(f.read()).decode("utf-8")
+
+# 初始化客户端
+client = OpenAI(
+    base_url="https://www.autodl.art/api/v1",
+    api_key="7bPZpONEQgxsP7kniD1AzmP3Tr0e84nmfExGroS1v11CBUKi",
+)
+
+# 调用接口（这里使用了stream=True进行流式响应）
+stream = client.chat.completions.create(
+    model="qwen3.6-plus",
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "提取图片中的文字，按阅读顺序输出"
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/jpeg;base64,{image_data}"
+                    }
+                }
+            ]
+        }
+    ],
+    stream=True,
+)
+
+# 流式打印输出
+for chunk in stream:
+    if chunk.choices and chunk.choices[0].delta.content:
+        print(chunk.choices[0].delta.content, end="")

ocr/readme.txt

@@ -0,0 +1,243 @@
+
+see huggingface_echodict\typst_hlm
+
+https://www.shidianguji.com/zh/book/TPM0001
+
+
+Python 3.13.12
+  
+
+python getdata.py
+  先修改第几章，运行下载文本和坐标画框转换格式
+
+duckdb + ducklake + readest + typst
+
+针对竖排/繁体/异体字与旧书噪声，选型
+
+**推荐选型（你的场景：竖排 + 繁体/异体字 + 旧书噪声）**
+
+- 首选检测：`CRAFT` 或 `DBNet++`
+- 首选识别：`SVTR-LCNet` / `PARSeq`（中文词表可扩）
+- 实战最稳组合：`CRAFT(检测) + SVTR(识别)` 或 `DBNet++(检测) + PARSeq(识别)`
+
+**为什么这样选**
+
+- `CRAFT` 优势：
+  - 对字符级与复杂排版（竖排、密集、非规则间距）通常更稳。
+  - 对旧书里断笔、脏污、背景纹理干扰有较好容错。
+  - 缺点是后处理和部署复杂度较高，速度一般。
+
+- `DBNet++` 优势：
+  - 工业成熟、训练和部署相对标准化。
+  - 对低对比、模糊页表现好。
+  - 缺点是天然偏“文本区域”，若你要严格“单字框”，需更细后处理或字符级训练策略。
+
+- `YOLO` 在你这个特定场景的定位：
+  - 可作为强基线（快、易训），但在旧书噪声+极小字+竖排密集时，通常上限不如 `CRAFT/DBNet++` 体系稳定。
+
+**针对“繁体/异体字”最关键点（比模型更重要）**
+
+- 字典必须扩展到繁体与常见异体字（否则识别上限被词表卡死）。
+- 训练数据要覆盖旧字形、破损字、弱印刷样式。
+- 识别模型建议用可扩词表的 Transformer 系（`PARSeq`、`SVTR`）而不是仅固定简体词集模型。
+
+**给你一个直接可执行的决策**
+
+- 要“最高鲁棒性”（不太在乎部署复杂）：`CRAFT + PARSeq/SVTR`
+- 要“精度和工程平衡”：`DBNet++ + SVTR`
+- 要“快速上线先跑通”：`YOLOv8字符检测 + SVTR`，后续再切 `CRAFT/DBNet++`
+
+**一句话结论**
+- 你的场景优先从 `DBNet++` 和 `CRAFT` 二选一做检测，识别端用 `SVTR/PARSeq` 并扩繁体异体词表；这比单纯换更大检测器更能提升最终效果。
+
+
+https://github.com/wkentaro/labelme
+  文本标注
+
+https://borninfreedom.github.io/posts/2024/07/blog-post-1/ 
+    论文解析——Character Region Awareness for Text Detection，字符级文本检测CRAFT算法
+
+https://arxiv.org/abs/1912.04561  A Feasible Framework for Arbitrary-Shaped Scene Text Recognition
+    https://github.com/zhang0jhon/AttentionOCR 代码
+    ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text Competition的冠军
+    它具有以下几个优点：中英文通用、准确性高、代码开源和有预训练模型。简而言之，亲测好用！
+        https://zhuanlan.zhihu.com/p/138589087
+
+
+https://www.shuge.org/meet/topic/78721/
+    https://www.ancientbooks.cn/
+    书格
+
+https://wenyuan.aliyun.com/
+    汉典重光
+
+
+https://www.shidianguji.com/zh/book/SWX0005 这网页的顶部有一个按钮 “原本影像”，点一下能出图片。最右边是正文，最左边是章节目录。正文里每一个字符都有一组坐标值能与对应的图片中的字符框对应。看看它在前端是怎样建立对应关系的，相应 api 是什么，怎么下载相关数据，包括文字，坐标，原图
+    https://solo.trae.ai/
+
+<div class="vik-toolbox-btn click act" type="page-next">  这里有一个"下一张" 按钮，点击会切换到下一张图片，看看它是怎来得到下一张图片的，把后面的图片都下载下来
+
+
+A）最快：Network 里 “Copy as fetch” → 粘贴到 Console 执行
+对每个接口都能用（paragraphs / word-box）：
+
+打开书页（比如 https://www.shidianguji.com/zh/book/SWX0005 进入阅读）
+F12 → Network
+过滤 paragraphs/v2 或 word-box-page-content/m-get
+点开一条真实请求（确保 Preview/Response 有数据，不是 0 bytes）
+右键该请求 → Copy → Copy as fetch
+粘贴到 Console 回车执行
+返回的就是 JSON（then(r=>r.json())...）
+如果你遇到 bdturing-verify（滑块验证），先在网页上完成验证后再复制那条“成功返回数据”的请求。
+
+(() => {
+  window.__cap = { fetch: [], xhr: [] };
+
+  // hook fetch
+  const _fetch = window.fetch;
+  window.fetch = async function(input, init = {}) {
+    try {
+      const url = typeof input === "string" ? input : input.url;
+      const method = (init.method || "GET").toUpperCase();
+      const body = init.body;
+      if (url.includes("/api/ancientlib/read/")) {
+        window.__cap.fetch.push({ t: Date.now(), url, method, init: { ...init, body } });
+        console.log("[CAP fetch]", method, url, body ? "(has body)" : "");
+      }
+    } catch (e) {}
+    return _fetch.apply(this, arguments);
+  };
+
+  // hook XHR
+  const _open = XMLHttpRequest.prototype.open;
+  const _send = XMLHttpRequest.prototype.send;
+  XMLHttpRequest.prototype.open = function(method, url) {
+    this.__cap_info = { t: Date.now(), method, url, body: null };
+    return _open.apply(this, arguments);
+  };
+  XMLHttpRequest.prototype.send = function(body) {
+    try {
+      if (this.__cap_info && String(this.__cap_info.url).includes("/api/ancientlib/read/")) {
+        this.__cap_info.body = body;
+        window.__cap.xhr.push(this.__cap_info);
+        console.log("[CAP xhr]", this.__cap_info.method, this.__cap_info.url, body ? "(has body)" : "");
+      }
+    } catch (e) {}
+    return _send.apply(this, arguments);
+  };
+
+  console.log("抓包器已安装：现在请在页面里翻页/滚动/点击“原本影像”等触发接口请求。");
+})();
+
+
+function lastReq(match) {
+  const all = [...window.__cap.fetch, ...window.__cap.xhr]
+    .filter(x => x.url && x.url.includes(match))
+    .sort((a,b) => b.t - a.t);
+  return all[0];
+}
+
+async function replay(req) {
+  if (!req) throw new Error("没抓到请求，请先触发一次页面请求。");
+  const url = req.url;
+  const method = (req.method || "GET").toUpperCase();
+  const body = req.init?.body ?? req.body ?? null;
+
+  const res = await fetch(url, {
+    method,
+    // 不要乱加 Origin/Referer（浏览器会自己带）；关键是带登录态：
+    credentials: "include",
+    headers: { "content-type": "application/json" },
+    body
+  });
+
+  const text = await res.text();
+  if (!text) {
+    console.warn("响应为空，可能触发滑块验证(bdturing)。请先在网页上完成验证后再抓一次。");
+    return null;
+  }
+  try { return JSON.parse(text); } catch (e) {
+    console.log("非 JSON 文本前200：", text.slice(0, 200));
+    throw e;
+  }
+}
+
+// 1） 拿 paragraphs
+(async () => {
+  const req = lastReq("/book/paragraphs/v2");
+  console.log("使用请求：", req?.method, req?.url);
+  const data = await replay(req);
+  console.log("paragraphs:", data);
+  window.__paragraphs = data; // 缓存
+})();
+
+// 2） 拿 word-box
+(async () => {
+  const req = lastReq("/word-box-page-content/m-get/");
+  console.log("使用请求：", req?.method, req?.url);
+  const data = await replay(req);
+  console.log("wordbox:", data);
+  window.__wordbox = data; // 缓存
+})();
+
+
+
+https://ocr.kandianguji.com/ocr_api
+
+token：8be3d75a-8a66-4b5d-9047-d4895e4c8000
+
+email：13788325535
+
+请求参数：
+
+token：您所申请的API Token，点此申请 必传
+
+email：申请API Token的账号，看典古籍网站的注册账号（参数名为email，手机号注册的传手机号） 必传
+
+image：需要识别的古籍图像，base64编码后的字符串类型，您可以在此处转换您的图像为base64编码 必传
+
+char_ocr：是否进行单字符检测识别，不检测文本行，只检测图像上的字符，文本行顺序可能会出错；布尔类型；默认值：False
+
+det_mode：文字内容排版样式，目前有三种可选：auto（自动识别）、sp（竖向排版）、hp（横向排版）；字符串类型，默认值：auto
+
+image_size：识别前图像尺寸调整，图像越小识别速度越快，0为不调整，设置指定值将按照设置对图像最长边进行等比例调整；整数类型，默认值：0
+
+return_position：是否返回文本行坐标信息和字符坐标信息；布尔类型，默认值：False
+
+return_choices：是否返回每个字符的其它候选字；布尔类型，默认值：False
+
+version：指定识别算法版本；字符串类型，可选：default（v1标准版本）、beta（古籍语序优化版本）、v2（最新版本），默认值：default
+
+det_layout（v2）：是否开启版面识别（对图像上的内容进行判断是否是正文、页眉页脚/版心等），对分栏式、多栏式文档识别效果较好；布尔类型（开启True、关闭False），默认值：False
+
+only_plain_text（v2）：是否只识别返回正文内容，仅当版面识别开启时生效，不识别页眉/页脚/版心等；布尔类型（开启True、关闭False），默认值：False
+
+return_layout（v2）：是否返回版面信息，仅当版面识别开启时生效；布尔类型（开启True、关闭False），默认值：False
+
+auto_insert_space（v2）：按照字符间距自动插入空格；布尔类型（开启True、关闭False），默认值：False
+
+hp_line_words_angel（v2）：指定横排句子文字排序方向；字符串类型（从左到右left2right、从右到左right2left），默认值：left2right
+
+sp_line_words_angel（v2）：指定竖排句子文字排序方向；字符串类型（从上到下top2bottom、从下到上bottom2top），默认值：top2bottom
+
+请求方式：
+
+POST请求，请求体可以为Form Data或JSON两种方式均可接受
+
+
+
+
+duckdb + ducklake + readest + typst see huggingface_echodict\typst_hlm\ocr\readme.txt
+
+https://aistudio.baidu.com/projectdetail/4438534?channelType=0&channel=0 真实 ocr 项目经验
+
+
+https://huggingface.co/datasets/ByteDance/AncientDoc 字节的数据集
+
+![img](深入理解神经网络：从逻辑回归到CNN.assets/b5ec48e89a6402434386c3479c641e7b.png)
+
+https://aistudio.baidu.com/datasetdetail/165369 真可以下载的 **古籍数据集**
+
+https://huggingface.co/datasets/Teklia/CASIA-HWDB2-line
+
+https://github.com/esun-ai/traditional-chinese-text-recogn-dataset

ocr/requirements.txt

@@ -0,0 +1,4 @@
+requests
+selenium==4.40.0
+numpy<2.0.0
+opencv-python==4.10.0.84