How devansh80/aadhaar-uid-masking-tool works
Aadhaar UID masking desktop tool: users select an image or document, the application searches for UID candidates, masks detected numbers, and saves a masked result. The source excerpt supports the OCR, checksum, image-masking, and PDF/TIFF helper behaviors, but omits parts of the main processing functions, so several workflow links are intentionally left unspecified. README capabilities such as batch processing and multilingual recognition are documented but not verifiable in the sampled implementation.
Main entry points: Masking.py File workflow
Components 15
Desktop interface
- File selection UI
Masking.py - File workflow
Masking.py
UID recognition
- OCR and orientation search
Masking.py - UID candidate search
Masking.py - Super-resolution model
Masking.py
Validation and masking
- Verhoeff checksum
Masking.py - UID image masking
Masking.py
Document processing
- Image conversion
Masking.py - PDF page replacement
Masking.py - PDF to TIFF merge
Masking.py
Other components
- User
- Selected document
- Tesseract OCR
- Poppler renderer
- Masked output
Connections 15
- User → File selection UI: selects file
- Selected document → File selection UI: provides input
- File selection UI → File workflow: starts processing
- OCR and orientation search → Tesseract OCR: runs OCR
- OCR and orientation search → UID candidate search: searches text
- UID candidate search → Verhoeff checksum: validates candidates
- UID image masking → Masked output: writes masked image
- File workflow → Image conversion: converts files
- File workflow → PDF page replacement: replaces PDF page
- File workflow → PDF to TIFF merge: exports TIFF
- Image conversion → Poppler renderer: renders PDF pages
- PDF to TIFF merge → Poppler renderer: renders PDF pages
- PDF page replacement → Masked output: writes merged PDF
- PDF to TIFF merge → Masked output: writes merged TIFF
- Super-resolution model → OCR and orientation search: enhances image