✨ Added #

• Intelligent product name normalization via ReceiptNormalizer.normalizeFromGroup
• Graph-based item ordering using PositionGraph with fuzzy matching and topological sort
• CachedReceipt consolidation with improved trust-based merging logic
• Parallelized parsing and graph resolution using Dart's compute() isolates
• Outlier filtering for OCR noise and trailing receipt lines
• Unit tests for name cleaning and group resolution

🛠️ Changed #

• Restructured core/ folder for better modularity
• Improved ReceiptParser._shrinkEntities() to robustly remove lines below sum/total
• Enhanced debug output when scanning receipts in ReceiptRecognizer

📚 Documentation #

• Added concise DartDoc to all public APIs, data models, and helpers

✅ Tests #

• Added group-based name cleaning tests
• Validated space vs. no-space consensus logic (e.g. "Co ke Zero" vs. "Coke Zero")

📚 Documentation #

• Added comprehensive dartdoc comments for all model classes in lib/src/receipt_models.dart

✨ Added #

• Optimizer Module: Introduced a new optimizer module to enhance the performance and efficiency of the receipt recognition pipeline.
• Product Name Detection Enhancements: Implemented advanced techniques for more accurate extraction and recognition of product names from receipts.

🛠️ Changed #

• Company Regex Enhancements: Updated regular expressions related to company name detection to enhance parsing accuracy.

🐛 Fixed #

• Product Name Extraction: Resolved issues where certain product names were not being accurately extracted due to inconsistent formatting.
• Company Name Detection: Fixed bugs in the regular expressions that led to incorrect company name identification in specific receipt formats.
• Parser Stability: Addressed edge cases in the parser that previously caused errors when processing receipts with uncommon layouts.

✅ Added #

• Unit Tests: Introduced unit tests to enhance code reliability and ensure consistent behavior across updates.

🛠️ Changed #

• Parser Refactoring:
  • Moved parsing methods to a dedicated parser module, improving code organization and maintainability.
  • Converted parser methods to static, facilitating easier access without instantiating classes.

🐛 Fixed #

• Company Name Recognition: Refined regular expressions related to company name detection, enhancing accuracy in identifying company names from receipts.

✨ Added #

• ReceiptWidget: A customizable Flutter widget that displays parsed receipt data in a layout resembling a real supermarket receipt.
• Advanced example demonstrating integration with a live video feed using the camera package.

🛠️ Changed #

• Updated README.md to include usage examples and details about models etc.

🐛 Fixed #

• Minor bug fixes and performance improvements.

✨ Added #

• Initial release of receipt_recognition.
• Core functionality to process images of receipts and extract structured data such as store name, items, and total amount using Google's ML Kit.
• Support for both Android and iOS platforms.