0.11.30

[fcakyon]

SAHI v0.11.30 Release Notes

We're excited to announce SAHI v0.11.30 with improved performance tracking, enhanced testing
infrastructure, and better developer experience!

📈 Milestones

• Academic papers citing SAHI reached 400! (#1168)

🚀 Key Updates

Performance & Monitoring

• Fixed postprocess duration tracking in get_sliced_prediction - now properly separates slice,
  prediction, and postprocess timings for accurate performance monitoring
  (#1201) - Thanks @Toprak2!

Framework Updates

• Refactored Ultralytics support with ONNX model support and better compatibility
  (#1184)
• Updated TorchVision support to latest API (#1182)
• Improved Detectron2 support with better config handling to prevent KeyError issues
  (#1116) - Thanks @Arnesh1411!
• Added Roboflow framework support for RF-DETR models from the Roboflow Universe
  (#1161) - Thanks @nok!
• Removed deepsparse integration as the framework is no longer maintained
  (#1164)

Testing Infrastructure

• Migrated test suite to pytest (#1187)
  • Tests now run faster with better parallel execution
  • Extended Python version coverage (3.8, 3.9, 3.10, 3.11, 3.12)
  • Updated to more recent PyTorch versions for better compatibility testing
  • Improved test organization and maintainability
• Refactored MMDetection tests for better reliability (#1185)

Developer Experience

• Added Context7 MCP integration for AI-assisted development
  (#1198)
  • SAHI's documentation is now indexed in Context7 MCP
  • Provides AI coding assistants with up-to-date, version-specific code examples
  • Includes llms.txt file for AI-readable documentation
  • Check out the Context7 MCP installation
    guide to integrate SAHI docs with your AI
    workflow

🛠️ Improvements

Code Quality & Safety

• Immutable bounding boxes for thread-safe operations (#1194,
  #1191) - Thanks @gboeer!
• Enhanced type hints and docstrings throughout the codebase
  (#1195) - Thanks @gboeer!
• Overloaded operators for prediction scores enabling intuitive score comparisons
  (#1190) - Thanks @gboeer!
• PyTorch is now a soft dependency improving flexibility
  (#1162) - Thanks @ducviet00!

Infrastructure & Stability

• Improved dependency management and documentation (#1183)
• Enhanced pyproject.toml configuration for better package management
  (#1181)
• Optimized CI/CD workflows for MMDetection tests (#1186)

🐛 Bug Fixes

• Fixed CUDA device selection to support devices other than cuda:0
  (#1158) - Thanks @0xf21!
• Corrected parameter naming from 'confidence' to 'threshold' for consistency
  (#1180) - Thanks @nok!
• Fixed regex string formatting in device selection function
  (#1165)
• Resolved torch import errors when PyTorch is not installed
  (#1172) - Thanks @ducviet00!
• Fixed model instantiation issues with AutoDetectionModel.from_pretrained
  (#1158)

📦 Dependencies

• Updated OpenCV packages from 4.10.0.84 to 4.11.0.86 (#1171) -
  Thanks @ducviet00-h2!
• Removed unmaintained matplotlib-stubs dependency (#1169)
• Cleaned up unused configuration files (#1199)

📚 Documentation

• Added context7.json for better AI tool integration (#1200)
• Updated README with new contributors (#1175,
  #1179)
• Added Roboflow+SAHI Colab tutorial link (#1177)

Acknowledgments

Special thanks to all contributors who made this release possible: @nok, @gboeer, @Toprak2, @Arnesh1411,
@0xf21, @ducviet00, @ducviet00-h2, @p-constant, and @fcakyon!

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Full Changelog: 0.11.24...0.11.30

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This discussion was created from the release 0.11.30.