🎉 Initial Release - Production Ready! #

Zero Setup Required! The package is now completely self-contained.

Added #

Core Features

• Multi-platform QR code scanning (Android, iOS, macOS, Linux, Windows)
• FFI-based native integration with OpenCV and ZXing
• Multiple QR code detection in single image (up to 50 codes)
• 6 advanced detection strategies for high accuracy:
  1. Original image with aggressive options
  2. Multi-scale processing (0.5x, 1.5x, 2.0x, 2.5x, 3.0x)
  3. Histogram equalization for contrast improvement
  4. Adaptive thresholding (Otsu and adaptive)
  5. Inverted grayscale scanning
  6. Sharpened image with kernel filter
• Duplicate detection to avoid counting same QR code multiple times

Architecture

• Robust modular architecture with clear separation of concerns
• Custom exception hierarchy (QRScannerException, LibraryLoadException, ImageProcessingException, InvalidParameterException)
• Comprehensive input validation for image paths and raw bytes
• Type-safe models (QRCode, QRCodePosition)
• Memory-safe native bindings with automatic cleanup
• Configurable scanning parameters (QRScannerConfig)
• Built-in debug logging system (QRScannerLogger)

API

• scanImageFile() - Scan QR codes from file path
• scanImageBytes() - Scan QR codes from raw pixel data
• updateConfig() - Configure scanning behavior at runtime
• Predefined configs: defaultConfig, fastConfig, accurateConfig

Validation

• Automatic file path validation (existence, format, size)
• Image format support: jpg, jpeg, png, bmp, webp, tiff, tif
• File size limit: 50MB maximum
• Raw image data validation (dimensions, channels, data size)
• Supported dimensions: up to 10000x10000 pixels
• Supported channels: 1 (grayscale), 3 (RGB), 4 (RGBA)

Self-Contained Package

• ZXing-C++ v2.2.1 source code bundled (no external installation)
• OpenCV automatically fetched:
  • Android: From Maven Central (org.opencv:opencv:4.5.3)
  • iOS: Via CocoaPods dependency
• All paths relative to package (no external dependencies)
• Native C++ compilation handled automatically

Documentation

• Complete README with installation and usage
• API reference with examples
• Exception handling guide
• Performance optimization tips
• Troubleshooting section
• Example app with image picker integration

Testing

• Unit tests for models and utilities
• Example app demonstrating all features

Platform Support #

• Android: Min SDK 21 (Android 5.0), supports arm64-v8a, armeabi-v7a, x86, x86_64
• iOS: Min iOS 12.0, supports device and simulator
• Desktop: macOS, Linux, Windows (experimental)

Performance #

• Efficient singleton pattern for resource reuse
• Early validation to fail fast
• Configurable behavior for speed vs accuracy trade-off
• Typical scan times: 50-500ms depending on image size and config

Dependencies #

• Flutter SDK: >=3.0.0
• Dart SDK: >=3.0.0
• ffi: ^2.1.0

License #

• MIT License
• Includes Apache 2.0 licensed ZXing-C++ and OpenCV