pdf_signature_extraction/COMMIT_SUMMARY.md

Git Commit Summary

Files Ready to Commit

Core Scripts (3 files)

✅ extract_pages_from_csv.py (5.3 KB)

• Extracts PDF pages listed in master_signatures.csv
• Tested with 100 files
• Status: Working

✅ extract_signatures_hybrid.py (18 KB)

• Hybrid signature extraction (VLM + CV + verification)
• Current working solution
• Status: 70% recall, 100% precision on test dataset

✅ extract_handwriting.py (9.7 KB)

• Computer vision only approach
• Used as component in hybrid approach
• Status: Archive (insufficient alone but useful reference)

Documentation (4 files)

✅ README.md (2.3 KB)

• Main project README with quick start guide

✅ PROJECT_DOCUMENTATION.md (24 KB)

• Comprehensive documentation of entire project
• All approaches tested and results
• Complete history and technical details

✅ README_page_extraction.md (3.6 KB)

• Documentation for page extraction step

✅ README_hybrid_extraction.md (6.7 KB)

• Documentation for hybrid signature extraction

Configuration (1 file)

✅ .gitignore (newly created)

• Excludes diagnostic scripts, test outputs, venv

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Files NOT to Commit (Diagnostic Scripts)

These are temporary diagnostic/testing scripts created during debugging:

❌ analyze_full_page.py ❌ ask_vlm_describe.py ❌ check_detection.py ❌ check_image_content.py ❌ check_successful_file.py ❌ diagnose_rejected.py ❌ extract_actual_signatures.py ❌ extract_both_regions.py ❌ save_full_page.py ❌ test_coordinate_offset.py ❌ verify_actual_region.py

❌ extract_signatures_vlm.py (failed VLM coordinate approach - keep for reference but mark as deprecated)

Reason: These are one-off diagnostic scripts created to investigate the VLM coordinate issue. They're not part of the production workflow.

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Optional: Archive extract_signatures_vlm.py

You may want to keep extract_signatures_vlm.py as it documents an important failed approach:

• Either commit it with clear "DEPRECATED" marker in filename or comments
• Or move to archive/ subdirectory
• Or exclude from git entirely (already in .gitignore)

Recommendation: Commit it for historical reference with deprecation note in docstring.

---

Suggested Commit Commands

cd /Volumes/NV2/pdf_recognize

# Check current status
git status

# Add the files we want to commit
git add extract_pages_from_csv.py
git add extract_signatures_hybrid.py
git add extract_handwriting.py
git add README.md
git add PROJECT_DOCUMENTATION.md
git add README_page_extraction.md
git add README_hybrid_extraction.md
git add .gitignore

# Optional: Add deprecated VLM coordinate script for reference
git add extract_signatures_vlm.py  # Optional

# Review what will be committed
git status

# Commit with descriptive message
git commit -m "Add hybrid signature extraction with name-based verification

Implement VLM name extraction + CV detection hybrid approach to
replace unreliable VLM coordinate system with name-based verification.

Key Features:
- VLM extracts signature names (周寶蓮, 魏興海, etc.)
- CV or PDF text layer detects regions
- VLM verifies each region against expected names
- Signatures saved with person names: signature_周寶蓮.png
- Duplicate prevention and rejection handling

Test Results:
- 5 PDF pages tested
- 7/10 signatures extracted (70% recall)
- 100% precision (no false positives)
- No blank regions extracted (previous issue resolved)

Files:
- extract_pages_from_csv.py: Extract pages from CSV (tested: 100 files)
- extract_signatures_hybrid.py: Hybrid extraction (current working solution)
- extract_handwriting.py: CV-only approach (component)
- extract_signatures_vlm.py: Deprecated VLM coordinate approach
- PROJECT_DOCUMENTATION.md: Complete project history and results
- README.md: Quick start guide
- README_page_extraction.md: Page extraction docs
- README_hybrid_extraction.md: Hybrid approach docs
- .gitignore: Exclude diagnostic scripts and outputs

Known Limitations:
- 30% of signatures missed due to conservative CV parameters
- Text layer method untested (all test PDFs are scanned images)
- Performance: ~24 seconds per PDF

Next Steps:
- Tune CV parameters for higher recall
- Test with larger dataset (100+ files)
- Process full dataset (86,073 files)
"

---

Verification Before Commit

Run these checks before committing:

1. Check git status

git status

Expected output:

• 8 files to be committed (or 9 if including extract_signatures_vlm.py)
• Diagnostic scripts should NOT appear (covered by .gitignore)

2. Verify .gitignore works

git status --ignored

Expected: Diagnostic scripts shown as ignored

3. Test the scripts still work

# Test page extraction (quick)
python extract_pages_from_csv.py  # Should process first 100 files

# Test signature extraction (slower, uses VLM)
python extract_signatures_hybrid.py  # Should process first 5 PDFs

4. Review documentation

# Open and review
less PROJECT_DOCUMENTATION.md
less README.md

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Post-Commit Actions

After committing, optionally:

1. Tag the release

   git tag -a v1.0-hybrid-70percent -m "Hybrid approach: 70% recall, 100% precision"
   git push origin v1.0-hybrid-70percent
   

2. Clean up diagnostic scripts (optional)

   # Move to archive folder
   mkdir archive
   mv analyze_full_page.py archive/
   mv ask_vlm_describe.py archive/
   # ... etc
   

3. Test on larger dataset

   • Edit extract_signatures_hybrid.py line 425: [:5] → [:100]
   • Run and verify results
   • Document findings

4. Plan improvements

   • Review "Known Issues" in PROJECT_DOCUMENTATION.md
   • Prioritize recall improvement or full-scale processing

---

Summary Statistics

Repository State:

Category	Count	Total Size
Production Scripts	3	33 KB
Documentation	4	37 KB
Configuration	1	<1 KB
Total to Commit	8	~70 KB
Diagnostic Scripts (excluded)	11	31 KB

Test Coverage:

Component	Files Tested	Status
Page extraction	100 PDFs	✅ Working
Signature extraction	5 PDFs	✅ 70% recall
VLM name extraction	5 PDFs	✅ 100% accuracy
CV detection	5 PDFs	⚠️ Conservative
Name verification	7 signatures	✅ 100% accuracy
Text layer search	0 PDFs	⏳ Untested

Code Quality:

✅ All scripts have docstrings and comments ✅ Error handling implemented ✅ Configuration clearly documented ✅ Logging to CSV files ✅ User-friendly console output ✅ Comprehensive documentation

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Ready to Commit?

If all verification checks pass and documentation looks good:

👍 YES - Proceed with commit

If you find issues or want changes:

👎 WAIT - Request modifications

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Document Created: October 26, 2025 Status: Ready for Review Next Action: User review → Git commit