image_background_remover 2.0.0

A Flutter package that removes the background from images using an ONNX model.

2.0.0

🎉 Major Update: Migration to flutter_onnxruntime

Breaking Changes

• Migrated from onnxruntime to flutter_onnxruntime package for better maintenance and support
• dispose() method is now asynchronous internally (no user code changes required)

New Features

• Modular Architecture: Refactored codebase into organized modules for better maintainability
  • services/onnx_session_manager.dart - ONNX Runtime session management
  • utils/image_processor.dart - Image processing utilities
  • utils/mask_processor.dart - Mask processing utilities
  • utils/background_composer.dart - Background composition utilities
• Better Resource Management: Improved memory management with proper tensor disposal
• Enhanced Error Handling: More informative error messages and validation

Improvements

• 16KB Android Page Size Support: Compatible with Google Play's 16KB requirement for Android 15+ devices
• Simplified ONNX session initialization (no manual buffer loading required)
• Better documentation with inline migration comments
• Improved code organization and separation of concerns
• Added comprehensive architecture documentation in lib/src/README.md

Important Notes

• Isolate Support: This package cannot be used with Dart isolates because ONNX model loading requires Flutter asset access. See WHY_NO_ISOLATES.md for detailed explanation.
• Async/Await: Use async processing on the main isolate - it provides non-blocking behavior without isolate complexity
• Migration Guide: All changes are marked with // Migration: comments in the code

API Changes

• Session management simplified (internal changes, no user-facing API changes)
• Tensor creation and disposal updated to new API (handled internally)

Files Added

• lib/src/services/onnx_session_manager.dart - Session lifecycle management
• lib/src/utils/image_processor.dart - Image processing utilities
• lib/src/utils/mask_processor.dart - Mask manipulation utilities
• lib/src/utils/background_composer.dart - Background composition
• lib/src/README.md - Architecture documentation
• WHY_NO_ISOLATES.md - Isolate limitations explanation

Migration from v1.x

If upgrading from v1.x:

1. No code changes required! The dispose call remains the same:

   @override
   void dispose() {
     BackgroundRemover.instance.dispose();
     super.dispose();
   }
   

   Note: Even though dispose() is async internally, you should not await it in your widget's dispose method because Flutter's dispose must be synchronous.

2. The public API remains completely backward compatible!

---

1.0.0

Fix

• Minor Bug fix
• Readme file updated

0.0.7

Added

• Implemented threshold-based segmentation to refine background removal.
• Integrated a smooth edge method using bilinear interpolation and average neighboring to improve output quality and reduce harsh edges.
• Implemented edge enhancement for mask refinement using a Sobel-like gradient detection method.

0.0.6

Feat

• Added addBackground function to change background of color

0.0.5

Fix

• Minor bug fixes

0.0.4

Fix

• Solved ONNX session creation error

0.0.3

Added

• Added assets file.

0.0.2

Fix

• Removed incompatible platform support.

0.0.1

Added

• Initial release of the Background Remover Service Flutter package.
• ONNX Runtime integration for background removal using the onnx model.
• Functions to initialize ONNX session:
  • initializeOrt(): Initialize the ONNX environment and session.
• Image processing capabilities:
  • removeBg(Uint8List imageBytes): Removes the background from an input image and returns the image with a transparent background.
  • _resizeImage(): Resizes an image to 320x320 for ONNXy model compatibility.
  • _imageToFloatTensor(): Converts RGBA image data into a normalized float tensor for model input.
  • _applyMaskToOriginalSizeImage(): Applies the generated mask back to the original image size.
• Utility methods:
  • resizeMask(): Resizes the ONNX output mask to match the original image dimensions.
• Designed for cross-platform support (iOS, Android, Web, and Desktop).