gbanyan
6ba128ded4
Codex round 25 returned Minor Revision: round-24's empirical and
cross-reference issues mostly CLOSED. Remaining items were all
partner-facing cosmetic / internal-notes hygiene.
§III v6 polish:
1. §III:11 v5 changelog reprint of real firm names removed
("real firm names 'EY' and 'KPMG'" -> "real firm names/aliases")
-- this was a self-regression I introduced in v5 while
documenting the v5 anonymisation fix.
2. §III:14 empirical anchor range updated:
"Scripts 32-40" -> "Scripts 32-42" (includes Scripts 41 + 42).
3. New v6 changelog entry added under the draft note documenting
the round-25 fixes.
4. Draft note version stamp refreshed: v5 -> v6.
§IV v3.2 polish:
1. §IV draft note rewritten and version label corrected:
"Draft v3" -> "Draft v3.2"; "post codex rounds 21-23" ->
"post codex rounds 21-25". The v3 -> v3.1 -> v3.2 lineage is
now recorded.
2. §IV close-out checklist item 2 rewritten to remove residual
"Tables IV-XVIII" wording. v3.2 explicitly states: v4 table
sequence is Tables V-XVIII plus Table XV-B; no v4 Table IV
is printed; the inherited v3.20.0 Table IV (per-firm
detection counts) remains a v3.x reference only.
Verification:
- Strict-case grep for KPMG / Deloitte / PwC / EY (with word
boundaries) + Chinese firm names: ZERO matches in either
file. Anonymisation is now complete throughout the
manuscript body AND internal notes.
Round 25 closure post-polish:
Major: all CLOSED (round 24 Major 1 table numbering: now
fully explicit V-XVIII + XV-B with v4 Table IV
absent; Major 4 anonymisation: §III:11 leak removed)
Minor: all CLOSED (weight drift 0.023 confirmed across 4
sites; cos <= 0.837 confirmed across 2 sites; n=686
provenance row confirmed)
Editorial: 1 still PARTIAL (internal draft notes + Phase 3
close-out checklist remain in the files but
explicitly marked "internal -- remove before
submission"; these are author working artefacts
intentionally retained until submission packaging)
Phase 4 readiness: technically Yes; the §III/§IV technical
content is converged across 5 codex review rounds. Internal
notes will be stripped at submission packaging time. Ready to
proceed to Phase 4 (Abstract/Intro/Discussion/Conclusion prose).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
PDF Signature Extraction System
Automated extraction of handwritten Chinese signatures from PDF documents using hybrid VLM + Computer Vision approach.
Quick Start
Step 1: Extract Pages from CSV
cd /Volumes/NV2/pdf_recognize
source venv/bin/activate
python extract_pages_from_csv.py
Step 2: Extract Signatures
python extract_signatures_hybrid.py
Documentation
- PROJECT_DOCUMENTATION.md - Complete project history, all approaches tested, detailed results
- README_page_extraction.md - Page extraction documentation
- README_hybrid_extraction.md - Hybrid signature extraction documentation
Current Performance
Test Dataset: 5 PDF pages
- Signatures expected: 10
- Signatures found: 7
- Precision: 100% (no false positives)
- Recall: 70%
Key Features
✅ Hybrid Approach: VLM name extraction + CV detection + VLM verification
✅ Name-Based: Signatures saved as signature_周寶蓮.png
✅ No False Positives: Name-specific verification filters out dates, text, stamps
✅ Duplicate Prevention: Only one signature per person
✅ Handles Both: PDFs with/without text layer
File Structure
extract_pages_from_csv.py # Step 1: Extract pages
extract_signatures_hybrid.py # Step 2: Extract signatures (CURRENT)
README.md # This file
PROJECT_DOCUMENTATION.md # Complete documentation
README_page_extraction.md # Page extraction guide
README_hybrid_extraction.md # Signature extraction guide
Requirements
- Python 3.9+
- PyMuPDF, OpenCV, NumPy, Requests
- Ollama with qwen2.5vl:32b model
- Ollama instance: http://192.168.30.36:11434
Data
- Input:
/Volumes/NV2/PDF-Processing/master_signatures.csv(86,073 rows) - PDFs:
/Volumes/NV2/PDF-Processing/total-pdf/batch_*/ - Output:
/Volumes/NV2/PDF-Processing/signature-image-output/
Status
✅ Page extraction: Tested with 100 files, working ✅ Signature extraction: Tested with 5 files, 70% recall, 100% precision ⏳ Large-scale testing: Pending ⏳ Full dataset (86K files): Pending
See PROJECT_DOCUMENTATION.md for complete details.