GITNUXSOFTWARE ADVICE
Technology Digital MediaTop 10 Best Card Scanner Software of 2026
Discover top 10 card scanner software for efficient digital organization. Scan, store, manage cards effortlessly.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Microsoft Lens
Automatic perspective correction with image enhancement before export
Built for individual users capturing card images into searchable documents.
Adobe Scan
Searchable OCR PDFs that convert card text into copyable, indexed content
Built for users needing searchable PDFs from card photos for storage and sharing.
CamScanner
Auto edge detection with perspective correction for straightened card scans
Built for individuals and small teams capturing occasional IDs and cards on mobile.
Related reading
Comparison Table
This comparison table evaluates card and document scanning software such as Microsoft Lens, Adobe Scan, CamScanner, Scanbot, and ABBYY FineScanner across key use cases like capture quality, OCR accuracy, and export or storage workflows. Readers can compare features that affect day-to-day scanning, including multi-page handling, file formats, and device compatibility.
| # | Tool | Category | Overall | Features | Ease of Use | Value |
|---|---|---|---|---|---|---|
| 1 | Microsoft Lens Mobile document capture tool that scans cards as images, enhances readability, and exports to PDF and common destinations. | document scanning | 8.4/10 | 8.7/10 | 8.9/10 | 7.6/10 |
| 2 | Adobe Scan Mobile scanning app that captures cards, applies OCR for text extraction, and saves results to searchable PDFs. | OCR scanning | 8.3/10 | 8.3/10 | 8.6/10 | 7.9/10 |
| 3 | CamScanner Mobile scanning app that captures card images, improves contrast, and enables OCR export for card details. | mobile scanning | 7.2/10 | 7.2/10 | 7.8/10 | 6.6/10 |
| 4 | Scanbot Mobile scanning SDK and app that captures cards with OCR and exports to cloud workflows and storage targets. | OCR capture | 8.0/10 | 8.4/10 | 7.6/10 | 7.9/10 |
| 5 | ABBYY FineScanner Document scanning app that performs OCR on scanned card text and outputs searchable files for storage. | OCR scanning | 7.7/10 | 7.8/10 | 8.2/10 | 7.2/10 |
| 6 | Evernote Notes app that supports image capture and OCR so scanned cards can be stored and searched in note libraries. | notes with OCR | 7.2/10 | 7.0/10 | 8.0/10 | 6.8/10 |
| 7 | OneNote Digital notebook that accepts scanned images and uses OCR to search card text stored in notebooks. | notes with OCR | 7.3/10 | 7.0/10 | 8.1/10 | 6.8/10 |
| 8 | Notion Workspace database and pages where card images can be stored and OCR text can be used for searching in supported workflows. | database organization | 7.1/10 | 7.0/10 | 7.6/10 | 6.8/10 |
| 9 | Dropbox Cloud storage that accepts scanned card images and enables searchable document handling through built-in OCR features. | cloud storage | 7.5/10 | 7.0/10 | 8.0/10 | 7.5/10 |
| 10 | Google Drive Cloud drive that stores scanned card documents and provides OCR-based search over uploaded files. | cloud storage | 7.2/10 | 7.0/10 | 8.0/10 | 6.8/10 |
Mobile document capture tool that scans cards as images, enhances readability, and exports to PDF and common destinations.
Mobile scanning app that captures cards, applies OCR for text extraction, and saves results to searchable PDFs.
Mobile scanning app that captures card images, improves contrast, and enables OCR export for card details.
Mobile scanning SDK and app that captures cards with OCR and exports to cloud workflows and storage targets.
Document scanning app that performs OCR on scanned card text and outputs searchable files for storage.
Notes app that supports image capture and OCR so scanned cards can be stored and searched in note libraries.
Digital notebook that accepts scanned images and uses OCR to search card text stored in notebooks.
Workspace database and pages where card images can be stored and OCR text can be used for searching in supported workflows.
Cloud storage that accepts scanned card images and enables searchable document handling through built-in OCR features.
Cloud drive that stores scanned card documents and provides OCR-based search over uploaded files.
Microsoft Lens
document scanningMobile document capture tool that scans cards as images, enhances readability, and exports to PDF and common destinations.
Automatic perspective correction with image enhancement before export
Microsoft Lens turns phone images into usable documents with a scan-first workflow and strong capture-to-output options. It can crop and enhance images, then export scans to common formats like PDF and Office files for card-related capture and record keeping. The app also supports saving to cloud locations and reusing scans in other Microsoft experiences. While it handles card text capture well, layout correction and field extraction are best-effort rather than a dedicated card database solution.
Pros
- Fast scan flow with automatic edge detection and perspective correction
- Clear image enhancement and sharpening for readable card details
- Exports to PDF and Office formats for easy sharing and archiving
- Works well offline for capture and later export to cloud
- Integrates with Microsoft storage workflows for document reuse
Cons
- Not a dedicated card scanner with structured card fields
- OCR accuracy depends heavily on lighting and card texture
- Batch card processing and bulk naming are limited
- Fine-grained image correction takes extra steps
Best For
Individual users capturing card images into searchable documents
More related reading
Adobe Scan
OCR scanningMobile scanning app that captures cards, applies OCR for text extraction, and saves results to searchable PDFs.
Searchable OCR PDFs that convert card text into copyable, indexed content
Adobe Scan stands out by producing direct, searchable PDFs and integrating document capture with Adobe Document Cloud workflows. It uses OCR to extract text from card photos, then saves results as PDFs that work well for archiving and sharing. Scanned card images can also support downstream organization via Adobe account storage and PDF viewing in Acrobat. It is best at turning images into readable, shareable documents rather than providing highly specialized card-only fields.
Pros
- Strong OCR turns card images into searchable text PDFs
- Auto-cropping and edge detection speeds up capture
- Acrobat-ready PDF output supports easy sharing and archiving
Cons
- Card-specific field extraction and normalization are limited
- OCR accuracy drops with glare, blur, or low contrast
- Designed for general scanning more than card database creation
Best For
Users needing searchable PDFs from card photos for storage and sharing
CamScanner
mobile scanningMobile scanning app that captures card images, improves contrast, and enables OCR export for card details.
Auto edge detection with perspective correction for straightened card scans
CamScanner stands out with fast phone-based document capture plus AI-assisted enhancement for readable scans. It offers common card scanning workflows like cropping, perspective correction, and edge detection for sharper ID and card images. Users can export scans to common formats and share them for quick verification or record keeping. Mobile-centric tooling also makes it convenient for occasional card capture rather than heavy batch processing.
Pros
- AI-like enhancement improves clarity on uneven lighting for card scans
- Perspective correction and auto-crop reduce manual alignment work
- Quick export and sharing options support hands-on card verification workflows
Cons
- Scanning quality varies across card types and background complexity
- Advanced organization and batch controls feel limited for high-volume capture
- Some processing steps increase friction compared with simpler capture apps
Best For
Individuals and small teams capturing occasional IDs and cards on mobile
Scanbot
OCR captureMobile scanning SDK and app that captures cards with OCR and exports to cloud workflows and storage targets.
Guided capture with real-time quality checks for document readability
Scanbot focuses on production-ready document capture for card-style IDs and printed cards. It provides mobile scanning with edge detection, perspective correction, and guided capture so scans stay readable. The workflow supports exporting and sending captured results for downstream use, including OCR-friendly output from supported documents. Automation features are strongest when integrated into an app or internal process rather than used as a standalone spreadsheet replacement.
Pros
- Strong image preprocessing with edge detection and perspective correction
- Reliable capture guidance that improves scan quality on the first attempt
- Useful export paths for turning captured data into downstream workflows
Cons
- Setup and configuration feel heavier than basic card-scanner apps
- Best results depend on document type support and lighting conditions
- Standalone usage lacks deeper built-in workflow management
Best For
Teams embedding high-quality card and ID scanning into mobile workflows
ABBYY FineScanner
OCR scanningDocument scanning app that performs OCR on scanned card text and outputs searchable files for storage.
ABBYY OCR with automatic image cleanup including de-skewing and contrast enhancement
ABBYY FineScanner stands out with mobile-first document capture that emphasizes fast, guided scanning and automatic image cleanup. It supports OCR to extract text and creates shareable scan files from captured pages. For card-style documents like IDs and business cards, it can improve legibility through de-skewing, cropping, and contrast adjustment before text recognition. Accuracy depends on the quality of the original image and the language of the extracted text.
Pros
- Guided scanning and auto-enhancement improves readability of card-like documents
- OCR converts captured images into editable text for quick downstream use
- De-skewing, cropping, and contrast adjustments reduce common capture defects
- Fast capture flow works well for repeated small-document scans
Cons
- Business-card extraction is not a focused CRM-grade capture workflow
- OCR quality drops on glare, heavy blur, and low-resolution images
- Limited batch-oriented card categorization and field structuring
Best For
Individuals and small teams capturing clean ID or card images with OCR
Evernote
notes with OCRNotes app that supports image capture and OCR so scanned cards can be stored and searched in note libraries.
Full-text search with OCR-enabled notes
Evernote stands out as a note-first system that can store and manage scanned card images alongside searchable notes. It supports mobile capture and scanning tools that convert receipts and documents into text for later retrieval. For card scanning, users can save captured images or extracted text into notebooks and use search to locate items quickly. It is strongest when card details become part of broader personal or team knowledge captured in notes.
Pros
- Reliable notebook organization for captured card images and extracted text
- Fast full-text search across notes for locating card details
- Mobile capture flow keeps scanning and saving in one place
Cons
- Card-specific contact fields and enrichment are limited
- Document OCR quality can vary across lighting and card design
- Exporting structured card data is less direct than CRM tools
Best For
People storing card scans as searchable reference notes
More related reading
OneNote
notes with OCRDigital notebook that accepts scanned images and uses OCR to search card text stored in notebooks.
Notebook-based OCR text search over captured images with desktop and mobile access
OneNote stands out by turning scanned card images into searchable notes tied to Microsoft 365 workflows. It supports capturing images from mobile devices and organizing them into notebooks, sections, and pages for quick retrieval. OCR enables text search across handwritten and printed content inside your notes. It lacks dedicated card capture, card-specific extraction, and automated merchant or card database features found in purpose-built card scanner tools.
Pros
- Strong OCR and text search across scanned card images
- Mobile capture and desktop editing in a single notes workflow
- Flexible notebook structure for sorting cards by account or project
- Easy sharing of notes with colleagues using Microsoft collaboration tools
- Rich annotation options like highlights and handwritten notes
Cons
- No card-specific extraction into fields like number, expiry, and issuer
- Limited automation for categorizing or deduplicating captured cards
- OCR accuracy depends on image quality and card layout
- Search and organization rely on manual labeling and notebook design
- No built-in export format tailored to card records
Best For
Teams capturing card details as notes and searching text with OCR
Notion
database organizationWorkspace database and pages where card images can be stored and OCR text can be used for searching in supported workflows.
Databases with custom properties, relations, and views for card record management
Notion stands out for turning captured information into structured databases, task views, and searchable knowledge with flexible layouts. For card scanning workflows, it supports manual card data entry and storage of fields like contact names, company details, and notes inside customizable databases. Collaboration tools like comments and shared pages help teams review and standardize card records across projects. The system does not provide a dedicated, first-class card OCR scan-to-database pipeline, so results depend on how data gets from the scan into Notion.
Pros
- Custom databases organize card fields into consistent records
- Fast search and tagging across large card collections
- Comments and views support team-based card verification workflows
Cons
- No dedicated card scanner OCR-to-database capture flow
- Extra steps are needed to transform scanned text into database fields
- Limited native support for bulk card import and deduplication
Best For
Teams managing card-derived contacts and notes inside structured workflows
Dropbox
cloud storageCloud storage that accepts scanned card images and enables searchable document handling through built-in OCR features.
Version history for restoring previous scan images in shared folders
Dropbox differentiates itself by centering scanned-card outputs inside a reliable cloud file system. In Card Scanner workflows, it supports saving photos or scans to cloud folders, then syncing them across devices for shared access. File organization, sharing controls, and version history help teams manage frequently updated card images and related documents. The main limitation is that Dropbox itself does not provide dedicated card parsing, OCR-to-fields, or identity-grade card extraction workflows.
Pros
- Automatic sync keeps scanned card images consistent across devices
- Folder-level sharing supports collaborative review of card scans
- Version history helps recover older scan versions after edits
Cons
- No built-in card-specific OCR or field extraction for card data
- Scan management depends on external capture tools and image quality
- Searching extracted card fields is not supported as a native workflow
Best For
Teams storing and sharing card scan images with lightweight workflow needs
Google Drive
cloud storageCloud drive that stores scanned card documents and provides OCR-based search over uploaded files.
Drive search with OCR-backed text retrieval
Google Drive stands out by combining cloud storage with strong document sharing and collaboration for captured card scans. Card images can be stored in Drive, indexed for search, and organized with folders and tags. Scanned files can be shared through permissions and opened in Google Docs, Sheets, or third-party editors for downstream review workflows. Drive does not provide dedicated card-scanning capture tools, so capture quality and OCR depend on external scanners or built-in device apps.
Pros
- Cloud storage centralizes card scan files with stable access across devices
- Permission-based sharing supports quick reviews and controlled distribution
- Drive search helps locate scans using filenames and OCR-extracted text
Cons
- No built-in card capture or edge-detection for ID-style scanning
- OCR and document cleanup rely on upstream capture quality
- Workflow automation needs third-party integrations for scan triage
Best For
Teams storing and sharing card scan images with minimal capture requirements
Conclusion
After evaluating 10 technology digital media, Microsoft Lens stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Card Scanner Software
This buyer's guide helps teams and individuals choose card scanner software for capturing card-like IDs and business cards into searchable files, notes, databases, or shared cloud folders. Coverage includes Microsoft Lens, Adobe Scan, CamScanner, Scanbot, ABBYY FineScanner, Evernote, OneNote, Notion, Dropbox, and Google Drive. The guide maps concrete capabilities like OCR-to-searchable PDF, guided capture quality checks, notebook-based OCR search, and cloud version history to specific real-world outcomes.
What Is Card Scanner Software?
Card scanner software is a mobile or document-capture workflow that turns card photos into readable outputs such as searchable PDFs, OCR text, or stored images with OCR search. It solves the problem of turning small, angled, and glare-prone card content into usable records that can be found later by search or organized into a workflow. In practice, tools like Microsoft Lens and Adobe Scan focus on scan-to-document exports like PDF and Office formats or searchable OCR PDFs. Other tools like Evernote, OneNote, Notion, Dropbox, and Google Drive focus on storing scanned card content inside a broader knowledge or file system and searching with OCR where supported.
Key Features to Look For
The right combination of capture quality controls and downstream organization features determines whether scanned card content becomes searchable and reusable, or stays as hard-to-find images.
Automatic perspective correction and image enhancement before export
Tools like Microsoft Lens and CamScanner use automatic perspective correction with auto-crop and image enhancement so card text stays readable when the photo is taken at an angle. Scanbot also improves capture reliability using strong edge detection and perspective correction with guided capture quality checks.
Searchable OCR output that turns card text into copyable search results
Adobe Scan produces searchable OCR PDFs that convert captured card text into copyable, indexed content for fast retrieval. ABBYY FineScanner also emphasizes OCR with automatic cleanup such as de-skewing and contrast enhancement to support accurate text extraction.
OCR-to-notes search for card details stored as knowledge
Evernote and OneNote treat captured card details as notes and enable full-text search over OCR-enabled content. OneNote supports desktop and mobile access with notebook-based OCR search over captured card images.
Databases and structured fields for card-derived records
Notion supports custom databases with properties, relations, and views so card details can be standardized into structured records for collaboration. This is a fit when card scanning feeds a workflow that also includes manual data entry or structured capture steps beyond OCR-only document output.
Guided capture with real-time quality checks for readable first attempts
Scanbot stands out for guided capture that uses real-time quality checks so scans remain readable for OCR and downstream use. This helps teams embedding card and ID scanning into mobile workflows reduce rescans when lighting or focus is imperfect.
Cloud storage collaboration with version history for shared scan sets
Dropbox focuses on cloud-centered management with version history that restores older scan images after edits. Google Drive also supports OCR-backed text retrieval and permission-based sharing so card scans are searchable and reviewable across collaborators.
How to Choose the Right Card Scanner Software
The selection process should match the capture output to the way card details will be searched, shared, and structured after scanning.
Pick the output format that matches the way records will be retrieved
Choose Adobe Scan when the requirement is searchable OCR PDFs so card text becomes copyable and indexed for retrieval. Choose Microsoft Lens when the requirement is fast scan-to-document export to PDF and Office formats with strong perspective correction and enhancement for readable card details.
Evaluate capture quality controls for angled, glare-prone card photos
Select Microsoft Lens or CamScanner when automatic edge detection and perspective correction are needed to straighten angled scans with readable details. Select Scanbot when guided capture and real-time quality checks are required to improve OCR readability on the first attempt in team mobile workflows.
Align OCR depth with the next workflow step
Choose ABBYY FineScanner when OCR accuracy depends on preprocessing like de-skewing, cropping, and contrast adjustment before text extraction. Avoid assuming structured card field extraction when using general scanning apps because OCR quality drops with glare, blur, and low contrast in tools like Adobe Scan and ABBYY FineScanner.
Choose an organization system that reflects how card data will be stored
Choose Evernote or OneNote when the goal is storing scanned card images alongside searchable notes for reference lookup. Choose Notion when the goal is turning card information into structured records using custom properties and team views, even if scanned text must be transformed into database fields with extra steps.
Use cloud collaboration features only when they are the primary workflow
Choose Dropbox when shared folders and version history are central to collaborative review of scanned card images. Choose Google Drive when the workflow depends on OCR-backed search inside Drive plus permission-based sharing and opening in Google Docs or Sheets for downstream review.
Who Needs Card Scanner Software?
Card scanner software fits distinct card-capture goals that range from personal searchable documents to shared, structured records inside collaboration systems.
Individuals capturing cards into searchable documents
Microsoft Lens is a fit when fast capture with automatic perspective correction and PDF or Office export is the priority. Adobe Scan is a strong fit when searchable OCR PDFs are the priority so card text becomes copyable and indexed for search.
Occasional mobile ID and card capture for individuals and small teams
CamScanner is a fit when quick auto-crop and perspective correction support hands-on verification workflows. This segment often tolerates limited batch controls and depends on capture clarity because scanning quality can vary across card types and backgrounds.
Teams embedding higher-quality card and ID scanning into mobile workflows
Scanbot is the best match when guided capture and real-time quality checks are needed to keep OCR-readable scans consistent across users. Scanbot also offers export paths that support downstream workflows rather than only storing images.
People storing scanned card details as searchable knowledge notes
Evernote is a fit when card scans and extracted text must live inside notebooks where full-text search finds card details later. OneNote is a fit when notebook-based OCR search is needed with flexible sections and pages for sorting card content by account or project.
Common Mistakes to Avoid
Most failed card-scanning rollouts come from choosing a tool for the wrong output type or expecting card-database automation from software that only creates documents or searchable text.
Expecting card database field extraction from general scan-to-document apps
Microsoft Lens and Adobe Scan focus on scan-to-document export and searchable OCR text rather than structured card fields like number and expiry. Notion can store card fields in custom properties, but it requires extra steps to transform scanned text into database fields because it does not provide a dedicated OCR scan-to-database pipeline.
Ignoring capture lighting and image clarity that directly impacts OCR
Adobe Scan and ABBYY FineScanner both show OCR accuracy drop with glare, blur, or low contrast. CamScanner and other phone-first capture workflows can also produce varying scan quality when backgrounds and card types make edge detection harder.
Using cloud storage without selecting an OCR-aware search workflow
Dropbox supports version history for scan images but does not provide native card parsing or OCR-to-fields as a built-in identity-grade workflow. Google Drive supports OCR-backed text retrieval, but it depends on scan quality created by upstream capture tools or device capture apps.
Overbuilding structure before card capture quality is consistent
Teams that move straight to structured workflows often hit rework because OCR preprocessing and capture guidance are the bottleneck. Scanbot reduces this risk with guided capture and real-time quality checks, and ABBYY FineScanner improves legibility using de-skewing and contrast enhancement before OCR.
How We Selected and Ranked These Tools
we evaluated every tool using three sub-dimensions. Features weighed 0.4, ease of use weighed 0.3, and value weighed 0.3. The overall rating is the weighted average of those three values using overall = 0.40 × features + 0.30 × ease of use + 0.30 × value. Microsoft Lens separated itself with concrete capture-to-output performance by combining automatic perspective correction and image enhancement with export to PDF and Office formats, which directly lifted the features and usability sub-dimensions over tools that mainly offer storage or note-based search without a dedicated card capture workflow.
Frequently Asked Questions About Card Scanner Software
What makes a card scanner app different from a generic document scanner for capturing business cards and IDs?
Microsoft Lens and Adobe Scan handle card images as documents by cropping, enhancing, and exporting to formats like PDF and Office files. That workflow supports record keeping but does not create a dedicated card database with fields. CamScanner and Scanbot focus more on straightening and sharpening card-style content using edge detection and perspective correction, which improves readability for later lookup.
Which tool produces the most usable searchable output from card photos?
Adobe Scan converts card photos into searchable PDFs by running OCR and embedding copyable, indexable text. Microsoft Lens and ABBYY FineScanner also perform OCR-style text capture, but their primary strength is scan-to-file output rather than card-first indexing. Google Drive can surface OCR-backed search results once card files land in Drive, but Drive itself does not provide card OCR capture.
How should teams choose between Scanbot and Scanbot-like mobile workflows versus note-first storage?
Scanbot is built for guided capture with real-time quality checks that keep card and ID scans readable before export. Evernote and OneNote store scanned card images alongside searchable notes, which fits workflows where card details are reviewed as knowledge rather than managed as structured records. Notion and Dropbox become stronger when the goal is organization and sharing through databases or synchronized file folders.
Which apps are best for straightening skewed or angled card photos?
CamScanner and Scanbot use perspective correction and edge detection to straighten card edges during capture. ABBYY FineScanner adds de-skewing and contrast adjustment before OCR, which helps card text remain legible. Microsoft Lens also supports automatic perspective correction and image enhancement, but dedicated card cleanup is not as specialized as ABBYY FineScanner and Scanbot.
Can scanned card text be searched effectively after capture?
Adobe Scan supports searchable PDFs that preserve OCR text for quick copy and search. Evernote and OneNote provide full-text search over OCR-enabled notes so card details can be found across notebooks and pages. Google Drive and Dropbox improve retrieval by searching stored files, but the quality of OCR text still depends on how the scan was produced.
Which tool fits a structured contact-management workflow with custom fields and views?
Notion can model card-derived records using databases with custom properties, views, and relations, which suits teams that standardize fields like company and contact notes. Microsoft Lens and Adobe Scan excel at converting images into documents, which supports storage and sharing but does not automatically populate a card schema. Dropbox and Google Drive focus on file organization and access control, not on building structured card fields from OCR.
What integration workflow is most practical for collaboration on scanned cards?
Google Drive and Dropbox enable shared access to scan files through folder permissions and collaboration-friendly storage. Adobe Scan integrates with Adobe Document Cloud so searchable PDFs are accessible in the Adobe ecosystem and openable in Acrobat. OneNote and Evernote support collaborative knowledge capture where scanned card details become searchable content across devices.
Why do some card scans fail to extract usable text, and what tools help most?
Low lighting, glare, and blurry card focus reduce OCR accuracy, which affects Adobe Scan, ABBYY FineScanner, and Evernote text extraction. ABBYY FineScanner mitigates legibility issues using automatic image cleanup like contrast adjustment and de-skewing before OCR. Scanbot and CamScanner help by improving capture quality with guided checks and edge detection so the OCR input is clearer.
What is the safest way to get started with card scanning using these tools?
Start with a capture-first app like Microsoft Lens or Scanbot to crop and correct perspective before exporting scans. Then store outputs in a shared system like Google Drive or Dropbox for controlled access and retrieval. If the workflow depends on text search and document reuse, Adobe Scan and OneNote create OCR-backed content that supports immediate searching across files or notebooks.
Tools reviewed
Referenced in the comparison table and product reviews above.
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