Ultralytics

🌟 Summary
Ultralytics v8.2.49 introduces new documentation and guides for deploying YOLO models on NVIDIA Jetson devices using DeepStream SDK and TensorRT, along with enhancements to existing documentation.

📊 Key Changes
- **New Guide**: Added a detailed guide for deploying YOLOv8 on NVIDIA Jetson devices using DeepStream SDK and TensorRT.
- **Documentation Update**: Included additional guides on model deployment practices and model testing.
- **Improved Index**: Enhanced the 'Guides' index to include the latest documentation updates.

🎯 Purpose & Impact
- **Enhanced Capabilities**: The new guide empowers users to deploy YOLOv8 models on Jetson devices, maximizing inference performance using NVIDIA's DeepStream SDK and TensorRT. 📈
- **Broadened Knowledge Base**: Additional guides on best practices for model deployment and testing provide comprehensive insights to improve model performance and reliability. 📚
- **User-Friendly**: Improved documentation structure makes it easier for users, both new and experienced, to find and utilize resources effectively. 🗂️

What's Changed
* Default strip_optimizer() to `use_dill=False` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14107
* Ultralytics Code Refactor https://ultralytics.com/actions by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14109
* Update NVIDIA Jetson DeepStream Guide with YOLOv8 and Jetson Orin Support by lakshanthad in https://github.com/ultralytics/ultralytics/pull/14059
* Update FAQ.md by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14134
* Update Results and CFG docstrings by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14139
* Add Docs models pages FAQs by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14167
* Add Model Testing Guide and Best Practices for Model Deployment Guide by abirami-vina in https://github.com/ultralytics/ultralytics/pull/14105
* Add https://youtu.be/mUybgOlSxxA to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/14195
* Add FAQ sections to Modes, Tasks, Usage by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14181
* `ultralytics 8.2.49` fix classification `setup_model` by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14199


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.48...v8.2.49

🌟 Summary
A minor update with key improvements and refinements to model loading and processing.

📊 Key Changes
- **Improved Error Messaging**: Updated error and warning messages to generalize references from "YOLOv8" models to "Ultralytics" models.
- **Model Verification**: Enhanced checks to ensure files are valid Ultralytics models before processing.
- **Stripping Optimizer Function**: Added and refined steps within the `strip_optimizer` function:
- Replaced model with Exponential Moving Average (EMA) if available.
- Stripped unnecessary components (optimizer, loss criterion, etc.) to reduce file size.
- Converted specific attributes to ensure compatibility and effective usage.

🎯 Purpose & Impact
- **Improved Clarity**: The changes in messaging make it clearer for users regardless of which version of the model they are using, reducing potential confusion.
- **Efficient Model Handling**: By verifying model validity and stripping non-essential parts, the update ensures smoother operations and smaller file sizes, potentially leading to faster loading times and less storage usage.
- **Enhanced Flexibility**: The refined error and warning messages allow for a more robust handling of various model scenarios, increasing the flexibility and robustness of the software for users.

What's Changed
* `ultralytics 8.2.48` strip model `criterion` on save by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14106


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.47...v8.2.48

🌟 Summary
Ultralytics v8.2.47 introduces new features and enhancements, mainly focusing on documentation updates, action recognition examples, and minor code improvements.

📊 Key Changes
- **Documentation Enhancements**:
- Added detailed sections on Fashion-MNIST dataset, highlighting its usage with a video tutorial embed.
- Introduced a new guide on Model Evaluation and Fine-Tuning.
- Updated the AI Gym workout monitoring guide.
- Improved loss function documentation.
- **New Examples**:
- Added a comprehensive example for Action Recognition using YOLOv8, including an in-depth guide and scripts for real-time video action recognition.
- **Code Improvements**:
- Renamed internal configurations to follow the 'yolov10' naming convention.
- Simplified loss computation classes and functions.
- General improvements to better handle variable image sizes and detailed internal metric extraction in YOLOv8.

🎯 Purpose & Impact
- **Documentation Enhancements**:
- 📚 Provides users with more comprehensive guides and tutorials for better understanding and implementing various features in Ultralytics.
- 🎦 The Fashion-MNIST video tutorial makes it easier for newcomers to start with image classification tasks.
- 🛠 The new guide on model evaluation and fine-tuning helps users optimize their models more effectively, improving overall model performance.
- **New Examples**:
- 🎥 The action recognition example enables users to leverage zero-shot video classification, expanding the range of applications for YOLOv8, particularly in video surveillance and behavioral analysis.
- **Code Improvements**:
- 🧹 Cleans up and organizes internal configurations, making it easier for developers to navigate and understand the codebase.
- 🚀 Simplifies the loss computation process, which could lead to more efficient and readable loss calculation workflows.
- 🔧 Ensures better handling of varied input image sizes, making YOLOv8 more versatile for different datasets and use cases.

What's Changed
* Add https://youtu.be/eX5ad6udQ9Q to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/14077
* Fix deprecation warning by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14091
* Add Insights on Model Evaluation and Fine-Tuning Docs Page by abirami-vina in https://github.com/ultralytics/ultralytics/pull/14085
* Strip `dfl_loss` from `BboxLoss` by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14041
* Results, DFL and AIGym fixes by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/14074
* `ultralytics 8.2.47` YOLOv8 zero-shot action recognition example by fcakyon in https://github.com/ultralytics/ultralytics/pull/13935


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.46...v8.2.47

🌟 Summary
Ultralytics has released version 8.2.46 with updates aimed at enhancing compatibility and usability.

📊 Key Changes
- **Dependency Adjustment**: Modified the numpy version requirement from ">=1.23.5,<2.0.0" to ">=1.23.0,<2.0.0".
- **Enhanced Logging**: Updated numpy attributes logging in tests to print before and after result methods.
- **Optimized Code**: Refactored the `xyxy` method in results handling for more efficient computations.

🎯 Purpose & Impact
- **Dependency Flexibility**: 🛠️ The adjustment in numpy dependency broadens compatibility by allowing a wider range of numpy versions. This could help users avoid conflicts with other projects dependent on different versions of numpy.
- **Improved Debugging**: 🐞 Enhanced logging in tests helps developers by providing clearer insights into the numpy attributes, simplifying debugging and validation processes.
- **Performance & Readability**: ⚡ The optimized `xyxy` method improves performance and maintainability by utilizing more efficient computations for bounding box transformations, benefiting both expert developers and applications that require fast, accurate results.

These updates contribute to a more robust and user-friendly experience for developers working with the Ultralytics YOLO framework. 🚀

What's Changed
* `ultralytics 8.2.46` fix OBB Results `xyxy` attribute by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14020


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.45...v8.2.46

🌟 Summary
Ultralytics v8.2.45 enhances model training guidance and prediction functionalities.

📊 Key Changes
- **Documentation Enhancements:**
- Improved explanations in model training tips including batch size adjustment, early stopping, and training environments.
- Consistent use of contractions for a more conversational tone.

- **Code Updates:**
- Updated model prediction test to include an augmentation parameter.
- Small enhancement to internal model prediction function to check for 'end2end' attribute.

- **Contributor Update:**
- Added a new contributor to the repository (`zhixuwei`).

🎯 Purpose & Impact
- **Documentation Clarity 💡:**
- **Purpose:** Simplifies complex training concepts for better user understanding.
- **Impact:** Users can more easily optimize their model training, leading to better model performance and resource utilization.

- **Enhanced Testing ✅:**
- **Purpose:** Ensures robustness in handling batch predictions with image augmentations.
- **Impact:** Enhances the reliability of prediction outputs, providing users with more dependable results.

- **Inclusivity & Acknowledgment 🌐:**
- **Purpose:** Update contributor list, recognizing ongoing community support.
- **Impact:** Encourages more community contributions by fostering a welcoming environment.

What's Changed
* `ultralytics 8.2.45` Fix YOLOv8 `augment` inference by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14017


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.44...v8.2.45

🌟 Summary
The v8.2.44 release focuses on enhancing model training documentation, improving data loader error handling, and adding new model training tips.

📊 Key Changes
- **GitHub Actions:** Simplified workflow triggers by removing unnecessary push events.
- **Documentation Updates:**
- Added a new guide titled "Tips for Model Training" with extensive best practices and optimization strategies.
- Enhanced various sections by including more detailed instructions and formatting adjustments.
- **Source Code Improvements:**
- Improved image read error handling in data loaders by changing from raising errors to logging warnings.
- Added detailed docstrings and typing annotations in the plotting methods for better code readability and maintenance.

🎯 Purpose & Impact
- **Improved Documentation:**
- 🎓 The new model training tips guide provides comprehensive strategies for efficient training, benefiting both beginners and experienced users.
- 📚 Detailed and structured documentation enhances learning and application of YOLO models, helping users achieve better results.
- **Better Error Handling:**
- 🚀 Improved error handling in data loaders ensures smooth execution, making the system more robust against corrupt or missing image files.
- 🔍 Logging warnings instead of raising errors allows the training process to continue, minimizing interruptions and saving users’ time.
- **Enhanced Code Quality:**
- 🛠️ Improved documentations and added typing in the source code, leading to easier maintenance and better developer experience.

These updates collectively aim to streamline the user experience, boost model performance, and ensure more robust and reliable training workflows.

What's Changed
* Added a `max_size` parameter to the `plot_images` function by bobyard-com in https://github.com/ultralytics/ultralytics/pull/14002
* Add Tips for Model Training Docs Page by abirami-vina in https://github.com/ultralytics/ultralytics/pull/14011
* `ultralytics 8.2.44` Increase Predict dataloader robustness by zhixuwei in https://github.com/ultralytics/ultralytics/pull/14005

New Contributors
* zhixuwei made their first contribution in https://github.com/ultralytics/ultralytics/pull/14005

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.43...v8.2.44