gbanyan/pdf_signature_extraction
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add hybrid signature extraction with name-based verification

Browse Source 
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
- SESSION_INIT.md: Session handoff documentation
- SESSION_CHECKLIST.md: Status checklist
- NEW_SESSION_PROMPT.txt: Template for next session
- HOW_TO_CONTINUE.txt: Visual handoff guide
- COMMIT_SUMMARY.md: Commit preparation guide
- 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)

🤖 Generated with Claude Code
This commit is contained in:
gbanyan
2025-10-26 23:39:52 +08:00
commit 52612e14ba
14 changed files with 3583 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

259
COMMIT_SUMMARY.md Normal file
View File

@@ -0,0 +1,259 @@
# 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
---
## 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.
---
## 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
```bash
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
```bash
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
```bash
git status --ignored
```
**Expected:** Diagnostic scripts shown as ignored
### 3. Test the scripts still work
```bash
# 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
```bash
# Open and review
less PROJECT_DOCUMENTATION.md
less README.md
```
---
## Post-Commit Actions
After committing, optionally:
1. **Tag the release**
```bash
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)
```bash
# 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
---
## 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**
---
**Document Created:** October 26, 2025
**Status:** Ready for Review
**Next Action:** User review → Git commit