KoOCR-Bench / code /engines /api_koocr_v12.py
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v1.2: request block boxes from Gemini/Mistral/CLOVA (official prompt + adapters, FORMAT.md); add gemini-3.5-flash-lite
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#!/usr/bin/env python3
"""KoOCR-Bench v1.2 API runs with block boxes (owner 2026-10-05: every engine must be asked for coordinates).
Output per block: <|det|>TYPE [x0, y0, x1, y1]<|/det|>CONTENT, coordinates normalised to 0..999 of the page.
gemini-* : PROMPT below (published verbatim in the benchmark README); temperature 0, lowest thinking setting
(3.1: thinkingBudget 0; 3.5 rejects budget 0, so thinkingLevel "minimal"). A det header the model closed
with <|det|> or <|/det/> instead of <|/det|> is repaired (CLOSE_FIX) so the block text is not swallowed by the next tag.
mistral : mistral-ocr-latest, table_format=html; uses the response's `blocks` (top_left/bottom_right px) in API order,
table blocks replaced by the returned HTML table.
clova : CLOVA OCR V2 general + table detection; words grouped into lines by lineBreak, line box = union of word
boundingPoly; lines whose centre falls inside a detected table are replaced by that table (HTML) as one
block; blocks ordered by top y then x.
Raw API responses are kept next to OUT (OUT.raw.jsonl).
Keys/endpoints come from env: GEMINI_API_KEY, MISTRAL_API_KEY, CLOVA_OCR_URL, CLOVA_OCR_SECRET.
Usage: api_run_v3.py ENGINE MANIFEST_JSONL IMG_ROOT OUT_JSONL [THREADS]"""
import base64, html, io, json, os, re, sys, time, uuid, urllib.request
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from PIL import Image
eng, man, root, out = sys.argv[1], sys.argv[2], Path(sys.argv[3]), Path(sys.argv[4])
threads = int(sys.argv[5]) if len(sys.argv) > 5 else 8
rawf = Path(str(out) + ".raw.jsonl")
M = [json.loads(l) for l in open(man)]
done = (
{json.loads(l)["id"] for l in out.open() if not json.loads(l).get("error")}
if out.exists()
else set()
)
todo = [r for r in M if r["id"] not in done]
PROMPT = "\n".join(
[
"이 문서 페이지를 OCR 하라. 페이지를 읽는 순서대로 블록(문단, 제목, 표, 그림, 머리말, 꼬리말, 쪽번호, 수식, 캡션) 단위로 나눠 출력하라.",
"- 각 블록은 반드시 `<|det|>종류 [x0, y0, x1, y1]<|/det|>내용` 형식으로 한 블록씩 출력하라.",
"- 종류는 title, text, table, image, header, footer, page_number, equation, caption 중 하나다.",
"- 좌표는 페이지 왼쪽 위가 (0, 0), 오른쪽 아래가 (999, 999)인 정수다. x0,y0은 블록 왼쪽 위, x1,y1은 오른쪽 아래다.",
"- 원문 표현은 그대로 보존하라(요약·바꿔쓰기·날조 금지). 보이는 텍스트만.",
"- 한 문단 안에서 줄이 끊긴 것은 이어 붙여라.",
"- 표는 HTML <table><tr><td>로 출력하라. 셀 병합은 rowspan/colspan으로 표시하라. Markdown 표 금지.",
"- 그림은 내용 없이 `<|det|>image [x0, y0, x1, y1]<|/det|>`만 출력하라.",
]
)
CLOSE_FIX = re.compile(r"(<\|det\|>\s*\w+\s*\[\s*\d+\s*,\s*\d+\s*,\s*\d+\s*,\s*\d+\s*\])\s*<\|?/?det[|/]?>") # <|det|>, <|/det/> ...
def norm_box(x0, y0, x1, y1, w, h):
f = lambda v, s: max(0, min(999, int(round(v / max(1, s) * 999))))
return f(x0, w), f(y0, h), f(x1, w), f(y1, h)
def det(kind, box, content):
return f"<|det|>{kind} [{box[0]}, {box[1]}, {box[2]}, {box[3]}]<|/det|>{content}"
if eng.startswith("gemini"):
KEY = os.environ["GEMINI_API_KEY"]
URL = f"https://generativelanguage.googleapis.com/v1beta/models/{eng}:generateContent?key="
elif eng == "mistral":
KEY = os.environ["MISTRAL_API_KEY"]
elif eng == "clova":
CURL, CSEC = os.environ["CLOVA_OCR_URL"], os.environ["CLOVA_OCR_SECRET"]
else:
raise SystemExit("engine?")
def post(url, body, headers):
req = urllib.request.Request(
url,
data=json.dumps(body).encode(),
headers={"Content-Type": "application/json", **headers},
)
return json.loads(urllib.request.urlopen(req, timeout=300).read())
def call(r):
raw = (root / r["image"].lstrip("/")).read_bytes()
im = Image.open(io.BytesIO(raw))
W, H = im.size
fmt = (
"webp"
if raw[8:12] == b"WEBP"
else ("jpeg" if raw[:2] == b"\xff\xd8" else "png")
)
if eng.startswith("gemini"):
body = {
"contents": [
{
"parts": [
{"text": PROMPT},
{
"inline_data": {
"mime_type": f"image/{fmt}",
"data": base64.b64encode(raw).decode(),
}
},
]
}
],
"generationConfig": {
"temperature": 0,
"thinkingConfig": {"thinkingLevel": "minimal"} if eng.startswith("gemini-3.5") else {"thinkingBudget": 0},
"maxOutputTokens": 60000,
},
}
d = post(URL + KEY, body, {})
c = d["candidates"][0]
return (
CLOSE_FIX.sub(r"\1<|/det|>", "".join(p.get("text", "") for p in c.get("content", {}).get("parts", []))),
d,
c.get("finishReason"),
)
if eng == "mistral":
body = {
"model": "mistral-ocr-latest",
"table_format": "html",
"include_image_base64": False,
"document": {
"type": "image_url",
"image_url": f"data:image/{fmt};base64,"
+ base64.b64encode(raw).decode(),
},
}
d = post(
"https://api.mistral.ai/v1/ocr", body, {"Authorization": "Bearer " + KEY}
)
parts = []
for p in d.get("pages", []):
dw, dh = p["dimensions"]["width"], p["dimensions"]["height"]
tabs = {t["id"]: t.get("content") or "" for t in p.get("tables") or []}
for b in p.get("blocks") or []:
box = norm_box(
b["top_left_x"],
b["top_left_y"],
b["bottom_right_x"],
b["bottom_right_y"],
dw,
dh,
)
content = (
tabs.get(b.get("table_id") or "", None)
if b.get("table_id")
else None
)
if content is None:
content = b.get("content") or ""
parts.append(det(b.get("type") or "text", box, content))
return "\n".join(parts), d, "ok"
# clova
if fmt == "webp" or fmt == "jpeg":
b = io.BytesIO()
im.convert("RGB").save(b, "PNG")
raw = b.getvalue()
body = {
"version": "V2",
"requestId": str(uuid.uuid4()),
"timestamp": int(time.time() * 1000),
"lang": "ko",
"images": [
{"format": "png", "name": "p", "data": base64.b64encode(raw).decode()}
],
"enableTableDetection": True,
}
d = post(CURL, body, {"X-OCR-SECRET": CSEC})
ci = d["images"][0]
if ci.get("inferResult") != "SUCCESS":
raise RuntimeError(f"inferResult {ci.get('inferResult')} {ci.get('message')}")
poly = lambda bp: (
[v.get("x", 0) for v in bp["vertices"]],
[v.get("y", 0) for v in bp["vertices"]],
)
tables = []
for t in ci.get("tables", []):
xs, ys = poly(t["boundingPoly"])
rows = {}
for c in t.get("cells", []):
txt = " ".join(
w["inferText"]
for tl in c.get("cellTextLines", [])
for w in tl.get("cellWords", [])
)
rows.setdefault(c["rowIndex"], []).append(
(c["columnIndex"], c.get("columnSpan", 1), c.get("rowSpan", 1), txt)
)
h = (
"<table>"
+ "".join(
"<tr>"
+ "".join(
"<td"
+ (f' colspan="{cs}"' if cs > 1 else "")
+ (f' rowspan="{rs}"' if rs > 1 else "")
+ f">{html.escape(tx)}</td>"
for _, cs, rs, tx in sorted(rows[k])
)
+ "</tr>"
for k in sorted(rows)
)
+ "</table>"
)
tables.append(((min(xs), min(ys), max(xs), max(ys)), h))
blocks, line, lxs, lys = [], [], [], []
def flush():
if line:
x0, y0, x1, y1 = min(lxs), min(lys), max(lxs), max(lys)
cx, cy = (x0 + x1) / 2, (y0 + y1) / 2
if not any(a <= cx <= c_ and b <= cy <= d_ for (a, b, c_, d_), _ in tables):
blocks.append(
(
(y0, x0),
det("text", norm_box(x0, y0, x1, y1, W, H), " ".join(line)),
)
)
line.clear()
lxs.clear()
lys.clear()
for f in ci.get("fields", []):
xs, ys = poly(f["boundingPoly"])
line.append(f["inferText"])
lxs.extend(xs)
lys.extend(ys)
if f.get("lineBreak"):
flush()
flush()
for (a, b, c_, d_), h in tables:
blocks.append(((b, a), det("table", norm_box(a, b, c_, d_, W, H), h)))
return "\n".join(x for _, x in sorted(blocks)), d, "SUCCESS"
def work(r):
t0 = time.time()
err = None
for a in range(3):
try:
text, d, fin = call(r)
return {
"id": r["id"],
"text": text,
"finish": fin,
"error": None,
"seconds": round(time.time() - t0, 1),
}, d
except Exception as e:
err = repr(e)[:200]
if hasattr(e, "read"):
try:
err += " " + e.read().decode()[:300]
except Exception:
pass
time.sleep(5 * (a + 1))
return {
"id": r["id"],
"text": "",
"finish": None,
"error": err,
"seconds": round(time.time() - t0, 1),
}, None
print(eng, "todo", len(todo), "done", len(done), flush=True)
with out.open("a") as f, rawf.open("a") as fr, ThreadPoolExecutor(threads) as ex:
for k, (row, d) in enumerate(ex.map(work, todo), 1):
f.write(json.dumps(row, ensure_ascii=False) + "\n")
f.flush()
if d is not None:
fr.write(
json.dumps({"id": row["id"], "response": d}, ensure_ascii=False) + "\n"
)
fr.flush()
if k % 50 == 0 or row["error"]:
print(
k, row["id"], row["error"] or row["finish"], row["seconds"], flush=True
)
print("API_DONE", eng, flush=True)