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business-card-scanner

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npx machina-cli add skill dkyazzentwatwa/chatgpt-skills/business-card-scanner --openclaw
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SKILL.md
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Business Card Scanner

Extract contact information from business card images using OCR.

Features

  • OCR Extraction: Extract text from card images
  • Contact Parsing: Name, company, email, phone, address
  • Pattern Recognition: Smart regex for contact fields
  • Multi-Format: JPG, PNG support
  • Batch Processing: Multiple cards
  • Export: vCard, JSON, CSV output

CLI Usage

python business_card_scanner.py --input card.jpg --output contact.json

Dependencies

  • pytesseract>=0.3.10
  • pillow>=10.0.0
  • opencv-python>=4.8.0
  • pandas>=2.0.0

Source

git clone https://github.com/dkyazzentwatwa/chatgpt-skills/blob/main/business-card-scanner/SKILL.mdView on GitHub

Overview

Business Card Scanner uses OCR to extract contact details from card images, including name, company, email, phone, and address. It supports JPG and PNG formats, batch processing, and can export results as vCard, JSON, or CSV for seamless CRM imports.

How This Skill Works

The tool performs OCR on card images to capture text, then applies smart regex-based parsing to identify and separate fields like name, company, email, phone, and address. It supports multi-format input and batch processing, finally exporting structured data to vCard, JSON, or CSV formats for easy integration.

When to Use It

  • Digitize contact information from networking event handouts or business cards collected in the field.
  • Import new leads into a CRM by converting card data into structured JSON or CSV.
  • Batch process large sets of business cards without manual data entry.
  • Prepare contact data for mobile devices by exporting to vCard.
  • Extract contact details from cards with varying layouts using smart regex parsing.

Quick Start

  1. Step 1: Install dependencies (pytesseract>=0.3.10, pillow>=10.0.0, opencv-python>=4.8.0, pandas>=2.0.0).
  2. Step 2: Run the CLI example: python business_card_scanner.py --input card.jpg --output contact.json
  3. Step 3: Import the resulting JSON/CSV/vCard into your CRM or contact app.

Best Practices

  • Capture high-quality card images with even lighting to improve OCR accuracy.
  • Preprocess images if needed (deskew, crop, and enhance contrast) to boost text recognition.
  • Rely on the smart regex patterns for field detection but verify critical fields like email and phone.
  • Process cards in batches to maximize throughput and maintain output consistency.
  • Choose the appropriate output format (vCard for phones, CSV/JSON for CRM imports).

Example Use Cases

  • Convert a stack of 100 conference cards into JSON for a marketing database.
  • Generate vCards from business cards to sync contacts with a mobile phone.
  • Export scanned data as CSV for bulk import into a CRM system.
  • Extract and store Name, Company, and Email for a sales outreach list.
  • Process mixed-format cards (JPG/PNG) and maintain consistent output across formats.

Frequently Asked Questions

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