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4ead231 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 | """Review-only FastAPI app for OmniSTG annotation feedback.
Design:
- One public URL, anyone can open it. We auto-mint an anonymous reviewer id
on first visit and store it in a cookie. Returning visitors keep the same
id and resume.
- Every annotation is shown read-only with: video link + 3 reference images +
bbox-overlaid keyframes + the 3 questions (TG/SG/QA) and the existing
answers.
- Reviewer fills 3 score fields (1=red/delete, 2=yellow/needs_fix, 3=green/keep)
+ 3 ref_type tags + 1 qa_type + optional comment.
- On submit we serialize the answer into a single JSON file and push it to a
HF Dataset (REVIEW_DATASET_REPO). Each submission is its own file so we
never have to lock or merge.
Env vars (set in HF Space):
HF_TOKEN write token
REVIEW_DATASET_REPO e.g. VCLab-PolyU/omnistg-reviews
ANNO_PER_USER_TARGET default 0 (no per-user cap)
ANNO_REVIEWS_TARGET default 3 (each anno needs at most N reviews)
"""
from __future__ import annotations
import json
import os
import random
import secrets
import sys
import time
from io import BytesIO
from pathlib import Path
from threading import Lock
# ensure sibling modules are importable regardless of how uvicorn is invoked
_SCRIPTS_DIR = Path(__file__).resolve().parent
if str(_SCRIPTS_DIR) not in sys.path:
sys.path.insert(0, str(_SCRIPTS_DIR))
from fastapi import FastAPI, Form, HTTPException, Request
from fastapi.responses import HTMLResponse, JSONResponse, RedirectResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
BASE = Path(__file__).resolve().parent.parent
STATIC = BASE / "static"
TEMPLATES = BASE / "templates"
DATA = BASE / "data"
REVIEW_DATASET_REPO = os.environ.get("REVIEW_DATASET_REPO", "")
HF_TOKEN = os.environ.get("HF_TOKEN", "")
TARGET_REVIEWS_PER_ANNO = int(os.environ.get("ANNO_REVIEWS_TARGET", "3"))
app = FastAPI(title="OmniSTG Review")
app.mount("/static", StaticFiles(directory=str(STATIC)), name="static")
templates = Jinja2Templates(directory=str(TEMPLATES))
# ---------- in-memory state ----------
#
# We keep two pieces of state in memory:
# ANNOTATIONS list of all annotations loaded from data/annotations.jsonl
# REVIEW_COUNT { anno_id: int } how many submissions we've forwarded so far
# (best-effort; rebuilt from HF Dataset on
# startup so it survives restarts)
# USER_DONE { user_id: set[anno_id] } what each user has already reviewed
# (rebuilt from HF Dataset on startup)
ANNOTATIONS: list[dict] = []
REVIEW_COUNT: dict[str, int] = {}
USER_DONE: dict[str, set[str]] = {}
_state_lock = Lock()
def load_annotations() -> None:
"""Read data/annotations.jsonl into memory."""
global ANNOTATIONS
f = DATA / "annotations.jsonl"
if not f.exists():
print(f"[startup] {f} missing — no annotations to serve")
ANNOTATIONS = []
return
items = []
with f.open(encoding="utf-8") as fh:
for line in fh:
line = line.strip()
if not line:
continue
try:
items.append(json.loads(line))
except Exception as e:
print(f"[startup] bad jsonl line: {e}")
ANNOTATIONS = items
print(f"[startup] loaded {len(items)} annotations")
def restore_review_state() -> None:
"""Pull existing reviews from HF Dataset to rebuild REVIEW_COUNT and USER_DONE.
Each review file lives at reviews/<reviewer_id>/<anno_id>__<ts>.json in the
dataset repo. We list them and update counters.
"""
if not (HF_TOKEN and REVIEW_DATASET_REPO):
print("[startup] HF_TOKEN/REVIEW_DATASET_REPO not set — skipping state restore")
return
try:
from huggingface_hub import HfApi, hf_hub_download
api = HfApi(token=HF_TOKEN)
try:
files = api.list_repo_files(repo_id=REVIEW_DATASET_REPO, repo_type="dataset")
except Exception as e:
print(f"[startup] can't list review repo (probably empty): {e}")
return
n = 0
for path in files:
# reviews/<reviewer_id>/<anno_id>__<ts>.json
parts = path.split("/")
if len(parts) != 3 or parts[0] != "reviews" or not parts[2].endswith(".json"):
continue
reviewer_id = parts[1]
stem = parts[2][:-5] # drop .json
anno_id = stem.rsplit("__", 1)[0]
REVIEW_COUNT[anno_id] = REVIEW_COUNT.get(anno_id, 0) + 1
USER_DONE.setdefault(reviewer_id, set()).add(anno_id)
n += 1
print(f"[startup] restored {n} prior reviews from {REVIEW_DATASET_REPO}")
except Exception as e:
print(f"[startup] restore_review_state failed: {e}")
@app.on_event("startup")
def _on_startup():
load_annotations()
restore_review_state()
# Make sure the dataset repo exists so the first push doesn't 404.
if HF_TOKEN and REVIEW_DATASET_REPO:
try:
from huggingface_hub import HfApi
HfApi(token=HF_TOKEN).create_repo(
repo_id=REVIEW_DATASET_REPO,
repo_type="dataset",
exist_ok=True,
private=True,
)
print(f"[startup] review dataset ready: {REVIEW_DATASET_REPO}")
except Exception as e:
print(f"[startup] create_repo failed: {e}")
# ---------- anonymous identity ----------
COOKIE = "rid" # reviewer id cookie
def _set_rid_cookie(resp, rid: str) -> None:
# SameSite=None+Secure so the cookie survives HF iframe wrappers.
resp.set_cookie(
COOKIE, rid,
max_age=180 * 86400,
samesite="none", secure=True, httponly=False, path="/",
)
def _ensure_rid(request: Request) -> tuple[str, RedirectResponse | None]:
"""Return (rid, redirect-or-None). If no cookie present, mint one and
return a redirect that re-loads the same URL with the cookie set."""
rid = request.cookies.get(COOKIE)
if rid:
return rid, None
rid = "anon_" + secrets.token_urlsafe(6)[:8]
# Redirect to the same path so the new cookie goes round-trip.
target = str(request.url)
resp = RedirectResponse(target, status_code=303)
_set_rid_cookie(resp, rid)
return rid, resp
# ---------- task picking ----------
def pick_next(rid: str) -> dict | None:
"""Pick the annotation with the FEWEST existing reviews that the user
hasn't seen yet. Random tiebreaker."""
with _state_lock:
done_by_me = USER_DONE.get(rid, set())
candidates = []
min_count = 10**9
for a in ANNOTATIONS:
if a["anno_id"] in done_by_me:
continue
c = REVIEW_COUNT.get(a["anno_id"], 0)
if c >= TARGET_REVIEWS_PER_ANNO:
continue
if c < min_count:
min_count = c
candidates = [a]
elif c == min_count:
candidates.append(a)
if not candidates:
return None
return random.choice(candidates)
def push_review(payload: dict) -> bool:
"""Push one review JSON to the HF Dataset.
Each submission gets its own file under reviews/<rid>/<anno>__<ts>.json so
concurrent writes never collide.
"""
if not (HF_TOKEN and REVIEW_DATASET_REPO):
# Locally we still want to persist. Drop into data/local_reviews/.
out = DATA / "local_reviews" / payload["reviewer_id"]
out.mkdir(parents=True, exist_ok=True)
ts = int(time.time() * 1000)
(out / f"{payload['anno_id']}__{ts}.json").write_text(
json.dumps(payload, ensure_ascii=False, indent=2),
encoding="utf-8",
)
return True
try:
from huggingface_hub import HfApi
api = HfApi(token=HF_TOKEN)
ts = int(time.time() * 1000)
path = f"reviews/{payload['reviewer_id']}/{payload['anno_id']}__{ts}.json"
body = json.dumps(payload, ensure_ascii=False, indent=2).encode("utf-8")
api.upload_file(
path_or_fileobj=BytesIO(body),
path_in_repo=path,
repo_id=REVIEW_DATASET_REPO,
repo_type="dataset",
commit_message=f"review {payload['anno_id']} by {payload['reviewer_id']}",
)
return True
except Exception as e:
print(f"[push_review] failed: {e}")
return False
# ---------- routes ----------
@app.get("/healthz")
def healthz():
return {"ok": True, "annos": len(ANNOTATIONS)}
@app.get("/", response_class=HTMLResponse)
def root(request: Request):
rid, redirect = _ensure_rid(request)
if redirect is not None:
return redirect
return RedirectResponse("/review", status_code=303)
@app.get("/review", response_class=HTMLResponse)
def review_page(request: Request):
rid, redirect = _ensure_rid(request)
if redirect is not None:
return redirect
anno = pick_next(rid)
done_by_me = len(USER_DONE.get(rid, set()))
total = len(ANNOTATIONS)
fully_done = sum(1 for a in ANNOTATIONS if REVIEW_COUNT.get(a["anno_id"], 0) >= TARGET_REVIEWS_PER_ANNO)
return templates.TemplateResponse(
"review.html",
{
"request": request,
"rid": rid,
"anno": anno,
"done_by_me": done_by_me,
"total": total,
"fully_done": fully_done,
"target_per_anno": TARGET_REVIEWS_PER_ANNO,
},
)
@app.post("/review/submit")
def review_submit(
request: Request,
anno_id: str = Form(...),
tg_score: int = Form(...),
tg_ref_type: str = Form(""),
sg_score: int = Form(...),
sg_ref_type: str = Form(""),
qa_score: int = Form(...),
qa_ref_type: str = Form(""),
qa_type: str = Form(""),
comment: str = Form(""),
):
rid, redirect = _ensure_rid(request)
if redirect is not None:
return redirect
# Reject obviously bogus inputs
if not any(a["anno_id"] == anno_id for a in ANNOTATIONS):
raise HTTPException(400, "unknown anno_id")
for s in (tg_score, sg_score, qa_score):
if s not in (1, 2, 3):
raise HTTPException(400, "scores must be 1, 2, or 3")
# If any sub-score is 1 or 2, the reviewer must justify it.
lowest = min(tg_score, sg_score, qa_score)
if lowest <= 2 and len((comment or "").strip()) < 5:
raise HTTPException(
400,
"1 分或 2 分必须在备注里写明原因(至少 5 个字符)"
" — please include a comment explaining why you gave a 1/2 score",
)
payload = {
"reviewer_id": rid,
"anno_id": anno_id,
"ts": int(time.time()),
"tg": {"score": tg_score, "ref_type": tg_ref_type},
"sg": {"score": sg_score, "ref_type": sg_ref_type},
"qa": {"score": qa_score, "ref_type": qa_ref_type, "qa_type": qa_type},
"comment": comment,
}
ok = push_review(payload)
if not ok:
raise HTTPException(500, "failed to persist review; please retry")
with _state_lock:
USER_DONE.setdefault(rid, set()).add(anno_id)
REVIEW_COUNT[anno_id] = REVIEW_COUNT.get(anno_id, 0) + 1
return RedirectResponse("/review", status_code=303)
@app.get("/stats")
def stats(request: Request):
"""Lightweight JSON stats endpoint (public)."""
return {
"annos_total": len(ANNOTATIONS),
"annos_fully_done": sum(
1 for a in ANNOTATIONS
if REVIEW_COUNT.get(a["anno_id"], 0) >= TARGET_REVIEWS_PER_ANNO
),
"reviews_total": sum(REVIEW_COUNT.values()),
"unique_reviewers": len(USER_DONE),
"target_per_anno": TARGET_REVIEWS_PER_ANNO,
}
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