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"""
Smoke Signal β Stage 5: Region Detection & Reading Order Resolver
==================================================================
Takes OCR raw output from Stage 4 and:
1. Classifies each detected region (narration, speech bubble, caption, etc.)
2. Assigns reading order using picture-book page logic
3. Detects two-page spreads and handles them correctly
4. Flags uncertain ordering rather than forcing false certainty
5. Saves ordered_regions.json per book
6. Creates visual overlay metadata for human review
Region classes:
narration | dialogue-speech-bubble | title | subtitle | caption |
sign-label | page-number | copyright-legal | publisher-imprint | decorative-uncertain
Usage:
python scripts/04_region_detector.py
python scripts/04_region_detector.py --book-id SS-BOOK-0001
python scripts/04_region_detector.py --dry-run
"""
import argparse
import csv
import json
import sys
import time
from datetime import datetime
from pathlib import Path
from typing import Optional
# ββ Paths ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
ROOT = Path(__file__).resolve().parents[1]
MANIFEST_CSV = ROOT / "manifest" / "source_manifest.csv"
PROFILES_DIR = ROOT / "manifest" / "page_profiles"
OCR_RAW_DIR = ROOT / "ocr_raw"
REGIONS_DIR = ROOT / "regions"
LOGS_DIR = ROOT / "logs"
REVIEW_DIR = ROOT / "review"
REGIONS_DIR.mkdir(parents=True, exist_ok=True)
LOGS_DIR.mkdir(parents=True, exist_ok=True)
# ββ Config ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
CONFIG = {
"config_version": "ss_regions_v0.1",
"page_number_max_chars": 4, # regions with <= 4 chars near top/bottom = page number
"copyright_keywords": ["Β©", "copyright", "all rights reserved", "isbn", "printed in"],
"publisher_keywords": ["published by", "first published", "edition", "press", "publishers"],
"title_y_threshold": 0.20, # top 20% of page = likely title zone
"footer_y_threshold": 0.85, # bottom 15% of page = likely footer zone
"spread_gap_threshold": 0.45, # x-center between 0.45-0.55 = possible spread gutter
"min_story_chars": 10, # below this = not story text
"eligible_statuses": ["ocred"],
}
REGION_CLASSES = [
"narration", "dialogue-speech-bubble", "title", "subtitle",
"caption", "sign-label", "page-number", "copyright-legal",
"publisher-imprint", "decorative-uncertain",
]
# ββ Manifest I/O βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def load_manifest() -> dict:
records = {}
if not MANIFEST_CSV.exists():
return records
with open(MANIFEST_CSV, newline="", encoding="utf-8") as f:
for row in csv.DictReader(f):
if row.get("book_id"):
records[row["book_id"]] = row
return records
def save_manifest(records: dict) -> None:
fields = [
"book_id", "source_id", "filename", "sha256", "file_size_bytes",
"page_count", "rights_class", "source_location", "acquisition_date",
"status", "allowed_use", "notes"
]
rows = sorted(records.values(), key=lambda r: r.get("book_id", ""))
with open(MANIFEST_CSV, "w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=fields)
writer.writeheader()
writer.writerows(rows)
def load_page_profile(book_id: str) -> Optional[dict]:
path = PROFILES_DIR / f"{book_id}_page_profile.json"
return json.load(open(path)) if path.exists() else None
def load_ocr_raw(book_id: str) -> Optional[dict]:
path = OCR_RAW_DIR / book_id / f"{book_id}_ocr_raw.json"
return json.load(open(path)) if path.exists() else None
# ββ Region classifier βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def classify_region(region: dict, page_height: float, page_width: float) -> str:
"""
Heuristic region classification based on:
- Text content (keywords)
- Position on page (y-coordinate normalised 0-1)
- Text length
"""
text = region.get("text", "").strip()
lower = text.lower()
bbox = region.get("bbox", [0, 0, 0, 0]) # [x0, y0, x1, y1]
if not text:
return "decorative-uncertain"
# Normalise bbox to 0-1 relative to page dimensions
if page_height > 0 and page_width > 0:
y_center = ((bbox[1] + bbox[3]) / 2) / page_height
x_center = ((bbox[0] + bbox[2]) / 2) / page_width
else:
y_center = 0.5
x_center = 0.5
char_count = len(text)
# ββ Page number ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
if (char_count <= CONFIG["page_number_max_chars"] and text.strip().isdigit() and
(y_center < 0.12 or y_center > CONFIG["footer_y_threshold"])):
return "page-number"
# ββ Copyright / legal ββββββββββββββββββββββββββββββββββββββββββββββββββββ
if any(kw in lower for kw in CONFIG["copyright_keywords"]):
return "copyright-legal"
# ββ Publisher imprint βββββββββββββββββββββββββββββββββββββββββββββββββββββ
if any(kw in lower for kw in CONFIG["publisher_keywords"]):
return "publisher-imprint"
# ββ Title zone (top of page, short text) βββββββββββββββββββββββββββββββββ
if y_center < CONFIG["title_y_threshold"] and char_count < 60:
return "title"
# ββ Speech bubble heuristic βββββββββββββββββββββββββββββββββββββββββββββββ
# Dialogue typically has quotes, said verbs, or is short and mid-page
has_quotes = any(c in text for c in ('"', '"', '"', "'", "Β«", "Β»"))
if has_quotes and char_count < 120:
return "dialogue-speech-bubble"
# ββ Caption (short, bottom portion of page) βββββββββββββββββββββββββββββββ
if y_center > 0.75 and char_count < 80 and not text.isdigit():
return "caption"
# ββ Sign / label (very short, anywhere) ββββββββββββββββββββββββββββββββββ
if char_count < 20 and not text.isdigit():
return "sign-label"
# ββ Decorative / uncertain (too short for story) βββββββββββββββββββββββββ
if char_count < CONFIG["min_story_chars"]:
return "decorative-uncertain"
# ββ Default: narration ββββββββββββββββββββββββββββββββββββββββββββββββββββ
return "narration"
# ββ Reading order resolver ββββββββββββββββββββββββββββββββββββββββββββββββββββ
def resolve_reading_order(regions: list, page_width: float, is_spread: bool) -> list:
"""
Sort regions into picture-book reading order.
Rules:
- Standard page: top-to-bottom, left-to-right within same y-band
- Two-page spread: left page top-to-bottom, then right page top-to-bottom
- Page numbers and copyright always last
- Uncertain order is flagged, not forced
"""
LAST_CLASSES = {"page-number", "copyright-legal", "publisher-imprint"}
story_regions = [r for r in regions if r.get("region_class") not in LAST_CLASSES]
footer_regions = [r for r in regions if r.get("region_class") in LAST_CLASSES]
if is_spread and page_width > 0:
# Split into left and right page
mid_x = page_width / 2
left = [r for r in story_regions if ((r["bbox"][0] + r["bbox"][2]) / 2) < mid_x]
right = [r for r in story_regions if ((r["bbox"][0] + r["bbox"][2]) / 2) >= mid_x]
def sort_key(r):
return (r["bbox"][1], r["bbox"][0]) # y then x
ordered = sorted(left, key=sort_key) + sorted(right, key=sort_key)
else:
# Standard: top-to-bottom with left-to-right tiebreak
y_band_size = 50 # points β regions within this y-band are on same "line"
def sort_key(r):
y_top = r["bbox"][1]
band = round(y_top / y_band_size)
return (band, r["bbox"][0]) # band then x
ordered = sorted(story_regions, key=sort_key)
# Add reading order index
full_ordered = []
for i, region in enumerate(ordered + footer_regions):
region = dict(region)
region["reading_order"] = i + 1
region["reading_order_uncertain"] = False
full_ordered.append(region)
# Flag uncertainty for overlapping regions
for i in range(1, len(full_ordered)):
prev = full_ordered[i - 1]
curr = full_ordered[i]
# If bboxes overlap significantly in y, order is uncertain
prev_y_bottom = prev["bbox"][3]
curr_y_top = curr["bbox"][1]
if curr_y_top < prev_y_bottom - 10: # significant overlap
curr["reading_order_uncertain"] = True
return full_ordered
# ββ Per-page region processing ββββββββββββββββββββββββββββββββββββββββββββββββ
def process_page_regions(
book_id: str,
page_num: int,
ocr_page: dict,
page_profile: dict,
) -> dict:
"""Process regions for a single page."""
page_width = page_profile.get("width_pt", 595)
page_height = page_profile.get("height_pt", 842)
is_spread = page_profile.get("is_spread", False)
route = page_profile.get("route", "ocr")
raw_regions = ocr_page.get("regions", [])
# Classify each region
classified = []
for region in raw_regions:
region = dict(region)
region["region_class"] = classify_region(region, page_height, page_width)
region["region_id"] = f"{book_id}_p{page_num:04d}_r{len(classified)+1:03d}"
region["source_book"] = book_id
region["page_number"] = page_num
classified.append(region)
# Resolve reading order
ordered = resolve_reading_order(classified, page_width, is_spread)
# Page-level stats
story_text = " ".join(
r["text"] for r in ordered
if r.get("region_class") in ("narration", "dialogue-speech-bubble", "caption")
)
return {
"book_id": book_id,
"page_number": page_num,
"route": route,
"is_spread": is_spread,
"page_width_pt": page_width,
"page_height_pt": page_height,
"region_count": len(ordered),
"story_char_count": len(story_text),
"page_confidence": ocr_page.get("page_confidence", 0),
"confidence_class": ocr_page.get("confidence_class", "review-required"),
"regions": ordered,
"warnings": page_profile.get("warnings", []),
"config_version": CONFIG["config_version"],
"processed_at": datetime.utcnow().isoformat() + "Z",
}
# ββ Per-book region detection βββββββββββββββββββββββββββββββββββββββββββββββββ
def detect_regions_for_book(record: dict, dry_run: bool = False) -> tuple:
book_id = record["book_id"]
filename = record["filename"]
print(f"\n [{book_id}] {filename}")
if record.get("rights_class") in ("unknown", "excluded"):
return record, None, {"error": "rights_blocked"}
page_profile_data = load_page_profile(book_id)
if page_profile_data is None:
print(f" β No page profile. Run 02_profile_pdfs.py first.")
return record, None, {"error": "no_page_profile"}
ocr_data = load_ocr_raw(book_id)
if ocr_data is None:
print(f" β No OCR data. Run 03_ocr_bakeoff.py first.")
return record, None, {"error": "no_ocr_data"}
# Index page profiles by page number
page_profiles_by_num = {p["page_number"]: p for p in page_profile_data["pages"]}
# Index OCR pages by page number
ocr_pages_by_num = {p["page_number"]: p for p in ocr_data.get("pages", [])}
all_page_results = []
uncertain_pages = []
empty_pages = []
total_pages = page_profile_data["page_count"]
for page_num in range(1, total_pages + 1):
page_prof = page_profiles_by_num.get(page_num, {})
route = page_prof.get("route", "embedded_text")
if route == "embedded_text":
# For embedded text pages, create minimal region record
all_page_results.append({
"book_id": book_id,
"page_number": page_num,
"route": "embedded_text",
"region_count": 0,
"story_char_count": 0,
"regions": [],
"note": "embedded_text_page_regions_not_processed_here",
})
continue
ocr_page = ocr_pages_by_num.get(page_num)
if ocr_page is None:
empty_pages.append(page_num)
continue
if not dry_run:
page_result = process_page_regions(book_id, page_num, ocr_page, page_prof)
else:
page_result = {
"book_id": book_id, "page_number": page_num,
"route": route, "region_count": 0,
"regions": [], "note": "dry-run",
}
# Check for uncertain ordering
uncertain = [r for r in page_result.get("regions", []) if r.get("reading_order_uncertain")]
if uncertain:
uncertain_pages.append(page_num)
if page_result.get("story_char_count", 0) == 0 and route != "embedded_text":
empty_pages.append(page_num)
all_page_results.append(page_result)
region_count = page_result.get("region_count", 0)
conf = page_result.get("page_confidence", 0)
print(f" Page {page_num:3d}: {region_count} regions | conf={conf:.2f} | route={route}")
# ββ Save ordered_regions.json βββββββββββββββββββββββββββββββββββββββββββββ
book_regions = {
"book_id": book_id,
"filename": filename,
"source_hash": record.get("sha256", ""),
"page_count": total_pages,
"config_version": CONFIG["config_version"],
"processed_at": datetime.utcnow().isoformat() + "Z",
"uncertain_pages": uncertain_pages,
"empty_story_pages": empty_pages,
"pages": all_page_results,
}
if not dry_run:
regions_path = REGIONS_DIR / f"{book_id}_ordered_regions.json"
with open(regions_path, "w", encoding="utf-8") as f:
json.dump(book_regions, f, indent=2)
print(f" Regions saved β {regions_path.relative_to(ROOT)}")
if uncertain_pages:
print(f" β οΈ Uncertain reading order on pages: {uncertain_pages}")
if empty_pages:
print(f" β οΈ Empty story pages: {empty_pages}")
record["status"] = "ocred" # keep at ocred β reviewed/exported set later
return record, book_regions, {}
# ββ Main βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def main():
parser = argparse.ArgumentParser(description="Smoke Signal β Stage 5: Region Detector")
parser.add_argument("--book-id", help="Process a single book by ID")
parser.add_argument("--batch-id", help="Tag this run with a batch ID")
parser.add_argument("--dry-run", action="store_true")
args = parser.parse_args()
run_id = args.batch_id or f"SS-RUN-{datetime.utcnow().strftime('%Y%m%d-%H%M%S')}"
dry_run = args.dry_run
print(f"\n{'='*60}")
print(f" Smoke Signal β Stage 5: Region Detector")
print(f" Run ID : {run_id}")
print(f" Config : {CONFIG['config_version']}")
if dry_run:
print(f" Mode : DRY RUN")
print(f"{'='*60}")
manifest = load_manifest()
if not manifest:
print("\n Manifest empty. Run earlier stages first.")
sys.exit(1)
books = (
[manifest[args.book_id]] if args.book_id and args.book_id in manifest
else [r for r in manifest.values() if r.get("status") in CONFIG["eligible_statuses"]]
)
if not books:
print(f"\n No books with status in {CONFIG['eligible_statuses']}.")
print(" Run 03_ocr_bakeoff.py first.")
sys.exit(0)
print(f"\n Books to process: {len(books)}")
results = []
t_start = time.time()
for record in books:
updated, book_regions, error = detect_regions_for_book(record, dry_run=dry_run)
result = {
"book_id": record["book_id"],
"filename": record["filename"],
"error": error,
}
if book_regions:
result["uncertain_pages"] = book_regions.get("uncertain_pages", [])
result["empty_story_pages"] = book_regions.get("empty_story_pages", [])
manifest[record["book_id"]] = updated
results.append(result)
if not dry_run:
save_manifest(manifest)
log_path = LOGS_DIR / f"{run_id}_regions_run.json"
with open(log_path, "w") as f:
json.dump({"run_id": run_id, "config": CONFIG, "results": results}, f, indent=2)
print(f"\n Run log β {log_path.relative_to(ROOT)}")
elapsed = round(time.time() - t_start, 1)
succeeded = sum(1 for r in results if not r.get("error"))
print(f"\n{'β'*60}")
print(f" Books processed : {len(results)}")
print(f" Succeeded : {succeeded}")
print(f" Time : {elapsed}s")
print(f"{'β'*60}")
print(f"\n Next: Run 05_llm_normalise.py (Stage 7)\n")
if __name__ == "__main__":
main()
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