Installation

From crates.io (recommended)

cargo install qrai-scanner-cli

From GitHub

cargo install --git https://github.com/SuperNovae-ai/qrai-scanner qrai-scanner-cli

Build from source

git clone https://github.com/SuperNovae-ai/qrai-scanner.git
cd qrai-scanner
cargo build --release -p qrai-scanner-cli
# Binary at: target/release/qraisc

Add to PATH (after building)

# macOS/Linux
sudo cp target/release/qraisc /usr/local/bin/

# Or add to your shell profile
echo 'export PATH="$PATH:/path/to/qrai-scanner/target/release"' >> ~/.zshrc

Usage

Basic Validation

# Full validation with visual output
qraisc image.png

# JSON output
qraisc -j image.png

# Score only (for scripts)
qraisc -s image.png
# Output: 85

Fast Mode

# Reduced stress tests (~2x faster)
qraisc -f image.png

Decode Only

# Skip stress tests, just decode
qraisc -d image.png

Timing Information

# Show processing time
qraisc -t image.png

Quiet Mode

# Minimal output
qraisc -q image.png

Options

Examples

Scripting

# Check if QR is production-ready (score >= 70)
if [ $(qraisc -s image.png) -ge 70 ]; then
    echo "Production ready!"
fi

# Batch process directory
for f in *.png; do
    score=$(qraisc -s "$f")
    echo "$f: $score"
done

CI/CD Integration

# GitHub Actions / GitLab CI
- name: Validate QR codes
  run: |
    for qr in assets/qr/*.png; do
      score=$(qraisc -s "$qr")
      if [ $score -lt 70 ]; then
        echo "❌ $qr failed with score $score"
        exit 1
      fi
      echo "✅ $qr passed with score $score"
    done

JSON Processing

# Extract content with jq
qraisc -j image.png | jq -r '.content'

# Get all stress test results
qraisc -j image.png | jq '.stress_results'

Output Format

Visual (default)

  ╔══════════════════════════════════════════════════════════════════╗
  ║  🌟  SCANNABILITY SCORE: 100                                   ║
  ╚══════════════════════════════════════════════════════════════════╝

  📄 File:    image.png
  ⏱  Time:    54ms

  📝 DECODED CONTENT
  https://example.com

  🧪 STRESS TEST RESULTS
   ✓ Original             [PASS]
   ✓ Downscale 50%        [PASS]
   ✓ Downscale 25%        [PASS]
   ✓ Blur (light)         [PASS]
   ✓ Blur (medium)        [PASS]
   ✓ Low Contrast         [PASS]

  📊 QR METADATA
   Version:          v2   (size complexity)
   Error Correction: M    (~15% recovery)
   Modules:          25x25  (grid size)
   Decoders:         rxing, rqrr

JSON (-j)

{
  "score": 100,
  "decodable": true,
  "content": "https://example.com",
  "metadata": {
    "version": 2,
    "error_correction": "M",
    "modules": 25,
    "decoders_success": ["rxing", "rqrr"]
  },
  "stress_results": {
    "original": true,
    "downscale_50": true,
    "downscale_25": true,
    "blur_light": true,
    "blur_medium": true,
    "low_contrast": true
  }
}

Exit Codes

License

MIT

Part of QR Code AI by Thibaut MÉLEN & SuperNovae Studio