Ultralytics

🌟 Summary (v8.2.39 Release)
The latest release `v8.2.39` from Ultralytics includes optimizations and updates across various files to enhance the overall functionality and performance.

📊 Key Changes
- **Documentation Updates:**
- Updated links across the documentation to use consistent URLs, replacing shortened links with full URLs for better readability and maintenance.
- Added embedded YouTube video to the SAHI documentation for enhanced user guidance.

- **Code Optimization and Fixes:**
- Adjusted layer configurations in `yolov8-p6.yaml` for more detailed memory and parameter utilization.
- Refined data augmentation and normalization operations for classification tasks in `augment.py`.
- Simplified code structure by replacing multiple `+=` operations with `append()` for clarity and performance.
- Updated `exporter.py` dependencies for ONNX, ensuring compatibility with the latest versions and enhancements in export capabilities.
- Improved segmentation handling and label generation in `converter.py`.
- Enhanced model configuration handling for ROS integration and temporary module management.

🎯 Purpose & Impact
- **Improved Documentation:**
- Ensures that users have direct and clear access to resources and guidance, enhancing overall user experience.
- Video content helps users better understand complex processes visually.

- **Enhanced Model Configuration and Exports:**
- Updated dependencies and configuration adjustments ensure that models utilize resources efficiently, improving performance metrics like GFLOPs and parameter counts.
- Optimized augmentation routines and classification tasks lead to faster and more accurate model training and predictions.

- **Code Maintenance and Clarity:**
- Codebase improvements, such as using `append()` over `+=`, make the code easier to read and maintain.
- Better structure and handling of transformations and temporary modules prevent potential runtime errors and streamline development.

These updates collectively ensure that the Ultralytics framework remains robust, user-friendly, and optimal for various AI and machine learning applications. 🚀

What's Changed
* Code refactor https://ultralytics.com/actions by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13844
* ROS Quickstart, fixed code formatting by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/13855
* Replace `+=` with faster list `.append()` by Kayzwer in https://github.com/ultralytics/ultralytics/pull/13849
* Fix ambiguous variable names by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13864
* Add https://youtu.be/tq3FU_QczxE to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/13867
* Update yolov8-p6.yaml with model parameters and GFLOPs by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13862
* Fix HUB link https://ultralytics.com/hub by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13884
* `ultralytics 8.2.39` update `onnxslim>=0.1.31` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13883


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.38...v8.2.39

🌟 Summary
Release `v8.2.38` introduces YOLOv10 models to the Ultralytics package, alongside enhancements and bug fixes.

📊 Key Changes
- **Benchmarking YOLOv10 Models:** Added benchmarks for YOLOv10 models.
- **YOLOv10 Documentation:** Detailed addition of YOLOv10 architecture and usage examples.
- **YOLOv10 Support:** Added YOLOv10 configurations (`.yaml` files) for different model sizes including YOLOv10n, YOLOv10s, YOLOv10m, YOLOv10l, and YOLOv10x.
- **New Modules:** Introduced new neural network modules (e.g., `RepVGGDW`, `CIB`, `C2fCIB`, `Attention`, `PSA`, `SCDown`).
- **End-to-End Detect (E2EDetect) Loss:** Added a new loss function for end-to-end detection.
- **Extended Model Exports:** Updated exporter configurations and limitations for new YOLOv10 operations.
- **Bug Fixes & Optimizations:** Addressed various bugs and performance enhancements (e.g., support for different export formats).

🎯 Purpose & Impact
- **Improved Object Detection:** The introduction of YOLOv10 models ensures optimized real-time object detection with high accuracy and low computational cost, beneficial for both current and future applications.
- **Enhanced Flexibility:** The addition of new modules and configurations allows users to tailor their models and training pipelines more precisely according to their needs.
- **Better Performance:** Benchmarking enhancements and end-to-end loss integration ensure more efficient and effective training and inference.
- **Comprehensive Documentation:** Detailed YOLOv10 documentation facilitates easier adoption and understanding for both new and existing users.
- **Expanded Export Options:** While not all formats are currently supported, the expanded export options provide more opportunities to deploy models across different platforms efficiently.

🚀 Next Steps
- Users are encouraged to explore the new YOLOv10 models and configurations for enhanced detection capabilities.
- Refer to the updated documentation for detailed guidance on utilizing the new features and modules effectively.

What's Changed
* `ultralytics 8.2.38` official YOLOv10 support by Burhan-Q in https://github.com/ultralytics/ultralytics/pull/13113


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.37...v8.2.38

🌟 Summary
The `v8.2.37` release focuses on enhancing developer experience and documentation consistency, with improvements in the Contributor License Agreement (CLA) workflow, better documentation formatting, and a refined ROS guide.

📊 Key Changes
- **CLA Workflow Permissions:** Enhancement in the `.github/workflows/cla.yml` with additional permissions and branch handling.
- **Documentation Formatting:**
- Improved indentation and structure in `CONTRIBUTING.md` and `README.md`.
- Updated information and formatting in the Chinese `README` file (`README.zh-CN.md`).
- **ROS Quickstart Guide:** Expanded step-by-step examples and usage scenarios for integrating YOLO with the Robot Operating System (ROS).
- **Removed Unused Code:**
- Elimination of the unused `Silence` class from `nn/modules/block.py`.

🎯 Purpose & Impact
- **Simplified Contribution Process:**
- The updated CLA workflow permissions ensure smoother handling of pull requests and contributions, benefiting both maintainers and contributors.
- **Enhanced Documentation Readability:**
- Improved indentation and formatting ensure that the documentation is easier to read and navigate, which is particularly helpful for new users and contributors.
- **Comprehensive ROS Guide:**
- More detailed examples and explanations in the ROS guide help users better understand the steps needed to integrate YOLO with robotics applications, making it easier for developers to implement and debug their systems.
- **Codebase Cleanliness:**
- The removal of the unused `Silence` class simplifies the codebase, making it more maintainable and reducing potential confusion for developers.

In summary, this release focuses on improving the user and contributor experience through better documentation and workflow enhancements, making it easier for both new and experienced developers to work with the Ultralytics codebase. 🚀

What's Changed
* Update CLA Action by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13831
* Update OpenCV image read error message by blackhu in https://github.com/ultralytics/ultralytics/pull/13822
* ROS quickstart Docs page cleanup by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/13835
* Annotator `txt_color` updates by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13842
* `ultralytics 8.2.37` update `temporary_modules` and Remove YOLOv9e `Silence` module by Laughing-q in https://github.com/ultralytics/ultralytics/pull/13819

New Contributors
* blackhu made their first contribution in https://github.com/ultralytics/ultralytics/pull/13822

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.36...v8.2.37

🌟 Summary
Release v8.2.36 includes improvements to documentation, code formatting, and new guides for integrating YOLO models with various platforms.

📊 Key Changes
- Updated documentation strings and examples for better readability.
- Minor corrections and additions in the README badges and links.
- Integration guides for ROS and enhancements in existing guides.
- Cleaned up unused imports in several files.

🎯 Purpose & Impact
- **Improved Documentation**: Enhances clarity and understanding for both new and experienced users by fixing line breaks and providing more detailed examples.
- **Enhanced Project Guides**: Introduces a new ROS Quickstart guide, helping users integrate YOLO models with the Robot Operating System (ROS) for real-time applications.
- **Streamlined Code**: Removal of redundant imports and cleaner code formatting to maintain a high standard of code quality and maintainability.
- **User-Friendly Experience**: Better Badge descriptions in README make it easier to understand the status and integration options available, improving the onboarding experience.

🌟 Summary
The v8.2.35 release of Ultralytics introduces new YOLOv9 models and various enhancements to the codebase and documentation.

📊 Key Changes
- **New Model Configurations**: Added configurations for YOLOv9 models (`yolov9t`, `yolov9s`, `yolov9m`).
- **Documentation Updates**: Enhanced model documentation with links to model weights and expanded on YOLOv9 details.
- **Code Refactoring**: Replaced `Silence` layers with `nn.Identity` in model configurations.
- **New Modules**: Introduced `ELAN1` and `AConv` modules.
- **Disabled CUDA Tests**: Temporarily disabled CUDA export tests due to limited GPU availability.
- **MLflow Sanitization**: Added a `sanitize_dict` function for cleaning MLflow metrics logging.

🎯 Purpose & Impact
- **Improved Model Availability**: The new YOLOv9 configurations make it easier for users to access and utilize various model sizes tailored to different computational needs, enhancing flexibility and performance tuning.
- **Enhanced Documentation**: Links to model weights and better documentation provide users with more resources and clearer information, aiding in model selection and deployment.
- **Code Quality**: Refactoring and new modules ensure the codebase is more maintainable, robust, and clear, benefiting long-term development and user comprehension.
- **Testing Adjustments**: Disabling CUDA tests prevents potential issues due to resource constraints, ensuring smoother development and testing phases.
- **Better Metrics Logging**: The `sanitize_dict` function improves the accuracy and readability of logged metrics in MLflow, leading to better monitoring and analysis of model training.

What's Changed
* Code Refactor `ruff check --fix --extend-select I` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13672
* Clean up unused `Silence` module by Laughing-q in https://github.com/ultralytics/ultralytics/pull/13674
* `ultralytics 8.2.35` add YOLOv9t/s/m models by Laughing-q in https://github.com/ultralytics/ultralytics/pull/13504


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.34...v8.2.35

🌟 Summary
Ultralytics v8.2.34 introduces several enhancements and dependency updates, aimed at improving the overall functionality and maintainability of the codebase.

📊 Key Changes
- 🔄 **Workflow Update**: Modified the GitHub Actions CI workflow configuration, including:
- Changed the 'pull_request_target' to 'pull_request'.
- Added a `TODO` comment for future improvements.
- Made error handling changes during the documentation build process.
- 📈 **Dependencies Update**:
- Updated `ultralytics-thop` to version 2.0.0 for FLOPs computation.
- Updated `mkdocs-ultralytics-plugin` to version 0.0.48 which is used for documentation meta descriptions and images.
- 🚀 **Code Additions**:
- Added a reference to the `Silence` function in the import statements, ensuring compatibility with YOLOv9 models.

🎯 Purpose & Impact
- 📂 **Workflow Improvements**:
- The workflow update makes the CI process more robust by ensuring that it triggers correctly on pull requests and continues even if there are errors during the documentation steps. This makes it easier for contributors to see their PR statuses without being obstructed by documentation errors.

- 📊 **Enhanced Computation & Documentation**:
- Updating dependencies ensures that users benefit from the latest features and fixes. For instance, the updated FLOPs computation library (`ultralytics-thop`) brings potentially more accurate and efficient model performance metrics.
- The `mkdocs-ultralytics-plugin` update helps keep the documentation generation current and more informative, improving the overall user experience when browsing project docs.

- 🤖 **Model Compatibility**:
- Including the `Silence` function ensures that the code remains compatible with YOLOv9 models, preventing potential loading issues for users employing the latest models.

This release focuses on maintaining a smooth development workflow, improving performance computation tools, and ensuring model compatibility.

What's Changed
* `ultralytics 8.2.34` bump `ultralytics-thop>=2.0.0` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/13662


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.33...v8.2.34