Ultralytics

🌟 Summary
The `v8.3.100` release introduces enhanced support for PaddlePaddle, ensuring compatibility with the latest versions and improving model export functionality. Additionally, it includes updates to documentation, pre-trained model links, and usability improvements for YOLO11 and YOLOE models.

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📊 Key Changes
- **PaddlePaddle Integration**:
- Updated support for PaddlePaddle `>=3.0.0` in both GPU and CPU environments.
- Improved model export handling for `.json` and `.pdiparams` files.
- Disabled OBB model inference for Paddle due to a silent error causing mAP drops (issue raised with PaddlePaddle).
- **Documentation Enhancements**:
- Added a new video tutorial for YOLO11 with NVIDIA DeepStream.
- Updated guides for YOLO11 deployment on Jetson devices.
- Introduced detailed references for YOLOE's visual prompt capabilities and text encoding models like CLIP and MobileCLIP.
- **Pre-trained Model Updates**:
- All pre-trained model links updated to `v8.3.0` for YOLOv8, YOLOv9, YOLOv10, YOLO-NAS, YOLOE, and others.
- **YOLOE Improvements**:
- Prevented unintended modifications to visual prompts during predictions.
- Enhanced task management to automatically detect segmentation or detection tasks based on the predictor.

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🎯 Purpose & Impact
- **Purpose**:
- Ensure compatibility with the latest PaddlePaddle versions and improve export reliability.
- Provide clearer, updated documentation for easier model deployment and usage.
- Enhance YOLOE's stability and usability for workflows involving visual prompts and mixed tasks.
- **Impact**:
- 🚀 **Improved Compatibility**: Users can now leverage PaddlePaddle `>=3.0.0` for seamless integration.
- 📚 **Better Documentation**: Simplifies deployment and training processes with updated guides and resources.
- 🔧 **Enhanced Usability**: YOLOE's improvements reduce errors and streamline workflows for developers.
- 🎥 **User-Friendly Resources**: New video tutorials make it easier for users to adopt YOLO11 on NVIDIA platforms.

This release ensures smoother workflows, better compatibility, and an overall improved user experience. 🌟

What's Changed
* Add https://youtu.be/hvGqrVT2wPg to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19943
* Update assets links by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19949
* Update DeepStream doc with YOLO11 support by lakshanthad in https://github.com/ultralytics/ultralytics/pull/19958
* YOLOE: Prevent original prompts from being modified by Y-T-G in https://github.com/ultralytics/ultralytics/pull/19963
* YOLOE: Preserve task type with refer_image by Y-T-G in https://github.com/ultralytics/ultralytics/pull/19969
* `ultralytics 8.3.100` New `paddlepaddle>=3.0.0` with `*.pdiparams` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19902


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.99...v8.3.100

🌟 Summary
The `v8.3.99` release introduces YOLOE models, a groundbreaking addition to the YOLO family, enabling advanced open-vocabulary detection, segmentation, and visual/text prompt-based tasks. This update also includes enhancements to Docker compatibility, object tracking examples, repository mirroring workflows, and documentation improvements.

📊 Key Changes
- **YOLOE Model Integration**: Added YOLOE models for open-vocabulary detection and segmentation, supporting text and visual prompts.
- **Prompt-Free Mode**: Enabled training and inference without predefined prompts for broader application scenarios.
- **Visual Prompt Embedding (SAVPE)**: Introduced spatial-aware visual prompt embedding for enhanced feature extraction.
- **Docker Updates**: Added Java Runtime Environment (JRE) and specific numpy version for Sony IMX model export compatibility.
- **Object Tracking Enhancements**: Improved YOLO11 tracking examples to handle edge cases and enhance visualization.
- **Repository Mirroring**: Streamlined GitHub-to-DagsHub mirroring workflow with manual triggering and improved flexibility.
- **Documentation Overhaul**: Updated image links, dataset guidance, and training instructions for better clarity and usability.

🎯 Purpose & Impact
- **Enhanced Model Capabilities**: YOLOE models expand YOLO's functionality to detect and segment objects beyond predefined categories, making it ideal for dynamic, real-world applications.
- **Broader Use Cases**: Prompt-free mode and SAVPE enable YOLOE to adapt to diverse scenarios, from autonomous systems to creative AI tasks.
- **Improved Developer Experience**: Docker updates simplify model export workflows, while tracking and documentation enhancements make implementation more robust and user-friendly.
- **Streamlined Repository Management**: Automated mirroring ensures consistent updates across platforms, saving time and improving accessibility for developers.

This release significantly elevates YOLO's versatility and usability, catering to both cutting-edge research and practical deployment scenarios. 🚀

What's Changed
* Update Dockerfile-python with JRE by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19925
* Update object tracking examples in docs by ankanpy in https://github.com/ultralytics/ultralytics/pull/19861
* New Mirror Repository GitHub Action by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19846
* Fix Mirror Action by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19926
* Documentation refactor and improvements by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19927
* `ultralytics 8.3.99` New YOLOE Open-Vocabulary Models by leonnil in https://github.com/ultralytics/ultralytics/pull/19775

New Contributors
* leonnil made their first contribution in https://github.com/ultralytics/ultralytics/pull/19775

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.98...v8.3.99

🌟 Summary
The `v8.3.98` release focuses on improving Java dependency handling for Sony IMX export, enhancing compatibility, and refining several other features across the Ultralytics ecosystem.

📊 Key Changes
- **Java Dependency Update**:
- Updated Dockerfile to use `default-jre` instead of specific Java versions for Sony IMX export.
- Enforced Java version 17 or higher for compatibility during the export process.
- **Bug Fixes and Improvements**:
- Fixed color consistency in YOLO8 LibTorch C++ inference by ensuring padding uses RGB values.
- Resolved a YOLO-NAS post-processing issue, aligning it with the broader Ultralytics framework.
- Improved handling of keypoints in pose models to mark out-of-bounds keypoints as invisible instead of clipping.
- **Documentation Enhancements**:
- Updated contribution guidelines for clarity and compliance with licensing.
- Enhanced README files across examples and integrations for better usability.

🎯 Purpose & Impact
- 🛠 **Simplified Java Setup**: Using `default-jre` reduces installation complexity and ensures smoother Sony IMX export processes.
- ✅ **Improved Accuracy**: Fixes in padding and keypoint handling enhance model reliability and visual consistency.
- 📄 **Better Documentation**: Clearer guidelines and updated examples make it easier for developers to contribute and use Ultralytics tools effectively.
- 🚀 **Framework Alignment**: YOLO-NAS updates ensure better integration and maintainability within the Ultralytics ecosystem.

This release reflects Ultralytics' commitment to improving user experience, compatibility, and technical robustness across its tools and models.

What's Changed
* Fix C++ Example letterbox by Q-qqq in https://github.com/ultralytics/ultralytics/pull/19900
* Fix NAS post-processing by Y-T-G in https://github.com/ultralytics/ultralytics/pull/19882
* README enhancements by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19906
* Fix keypoints being clipped rather than hidden by HeadTriXz in https://github.com/ultralytics/ultralytics/pull/19921
* `ultralytics 8.3.98` Sony IMX Java Runtime Environment>=17 by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19905

New Contributors
* Q-qqq made their first contribution in https://github.com/ultralytics/ultralytics/pull/19900
* HeadTriXz made their first contribution in https://github.com/ultralytics/ultralytics/pull/19921

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.97...v8.3.98

🌟 Summary
The Ultralytics 8.3.97 release focuses on enhancing Sony IMX export capabilities, improving Docker usability, and ensuring compatibility with key dependencies. Additionally, it includes minor documentation and code quality updates for a better user and developer experience. 🚀

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📊 Key Changes
- **Sony IMX Export Enhancements**:
- Added Java (OpenJDK 17) to Docker for Sony IMX compatibility.
- Updated dependencies for Sony IMX export, including `model-compression-toolkit` (>=2.3.0) and `sony-custom-layers` (>=0.3.0).
- Adjusted Python requirements, specifying `numpy==1.26.4` for Sony IMX workflows.
- Introduced a new export command for Sony IMX models in Docker.

- **Dependency Management**:
- Pinned `paddlepaddle` to versions below 3.0.0 to avoid compatibility issues.

- **Documentation and Code Improvements**:
- Standardized license headers across files for clarity.
- Fixed typos and improved consistency in example notebooks.
- Enhanced type annotations and documentation for better code readability.

- **Minor Adjustments**:
- Removed outdated redirects in documentation.
- Improved HTML title handling for documentation pages.

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🎯 Purpose & Impact
- **Enhanced Sony IMX Support**:
- Streamlines Sony IMX export workflows by integrating necessary tools and dependencies directly into Docker.
- Saves users time and effort in setting up their environment.

- **Improved Stability**:
- Pinned `paddlepaddle` ensures smoother exports and inference workflows, avoiding potential bugs from breaking changes in newer versions.

- **Better User Experience**:
- Simplified and standardized example notebooks make it easier for users to follow and implement workflows.
- Documentation updates improve navigation and usability, helping users find information faster.

- **Developer-Friendly Enhancements**:
- Consistent license headers and improved type annotations make the codebase easier to maintain and contribute to.

This release ensures a more robust and user-friendly experience for both end-users and developers, with a particular focus on expanding export capabilities and maintaining compatibility. 🌟

What's Changed
* Remove /SECURITY redirect in mkdocs.yml by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19865
* Fix Example: -> Examples: by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19866
* Pin `paddlepaddle<=3.0.0` to avoid bug in latest release by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19876
* Adopt H1 headers for Docs page HTML <title> by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19875
* Fix typo in notebooks by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19883
* `ultralytics 8.3.97` Update Dockerfile-cpu Sony IMX export tools by lakshanthad in https://github.com/ultralytics/ultralytics/pull/19765


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.96...v8.3.97

🌟 Summary
The Ultralytics 8.3.96 release focuses on simplifying Docker configurations, enhancing compatibility, and improving user experience for developers working with YOLO11 and related tools. 🚀

📊 Key Changes
- 🛠 **Unified Docker Setup**: Removed the `Dockerfile-nvidia-cuda` and consolidated configurations into the main Dockerfile.
- 📦 **Preinstalled Key Libraries**: Added `tensorrt` and `onnxruntime-gpu` to the Dockerfile for streamlined GPU workflows.
- 🔇 **Cleaner Logs**: Suppressed TensorFlow warnings for a more user-friendly experience.
- 🔄 **Simplified PaddlePaddle Installation**: Removed Python version constraints for easier compatibility.
- 📖 **Documentation Updates**:
- Added overclocking instructions for Raspberry Pi 5 to boost YOLO11 performance.
- Expanded Docker documentation with new Dockerfiles for NVIDIA Jetson devices and JupyterLab.
- ⚠️ **Improved Version Warnings**: Enhanced clarity in version mismatch messages to assist users in resolving issues quickly.

🎯 Purpose & Impact
- **Streamlined Docker Management**: By unifying and optimizing Docker configurations, users benefit from reduced complexity and easier maintenance.
- **Enhanced GPU Workflows**: Preinstalled libraries like `tensorrt` and `onnxruntime-gpu` save setup time and improve performance for GPU-based tasks.
- **Improved Usability**: Suppressing TensorFlow warnings and simplifying PaddlePaddle installation make the tools more accessible and user-friendly.
- **Broader Hardware Support**: New Dockerfiles and Raspberry Pi overclocking guidance enable better performance on diverse devices, from Jetson boards to Raspberry Pi.
- **Clearer Error Handling**: Improved version warnings reduce confusion, helping users troubleshoot faster.

This release ensures a smoother, more efficient experience for developers and users across various platforms and workflows. 🌟

What's Changed
* Fix `latest-nvidia-cuda` Docker tag by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19835
* Docker python3 > python symbolic links by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19836
* Fix check_version() report with multiple constraints by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19840
* Update Raspberry Pi doc with overclock information by lakshanthad in https://github.com/ultralytics/ultralytics/pull/19841
* Update Docker doc with missing Dockerfiles by lakshanthad in https://github.com/ultralytics/ultralytics/pull/19842
* `ultralytics 8.3.96` Preinstall `tensorrt` and `onnxruntime-gpu` in Dockerfile by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19845


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.95...v8.3.96

🌟 Summary
The Ultralytics 8.3.95 release introduces a CUDA-optimized Dockerfile for enhanced GPU support, updates dependencies, and improves documentation and usability across various tools and integrations.

📊 Key Changes
- **New NVIDIA CUDA Dockerfile**: Added `Dockerfile-nvidia-cuda` for optimized YOLO11 training and inference on GPUs.
- **Dependency Updates**: Upgraded PyTorch base image to `2.6.0-cuda12.6-cudnn9-runtime` and CoreML compatibility to version 8.0.
- **Improved Documentation**: Enhanced formatting, added examples, and clarified CLI usage across guides.
- **CLI Syntax Standardization**: Ensured array inputs (e.g., `classes`, `kpts`) are enclosed in quotes for consistency.
- **YOLOE Documentation Update**: Added detailed tips for selecting detection modes.
- **GitHub Banner Update**: Redirects to the latest YOLO11 blog for better user engagement.

🎯 Purpose & Impact
- **Enhanced GPU Performance**: The new CUDA Dockerfile ensures seamless multi-GPU training and inference, benefiting users with high-performance hardware. 🚀
- **Improved Compatibility**: Updates to CoreML and PyTorch ensure support for the latest Python versions and GPU optimizations. 🖥️
- **Better Usability**: Documentation improvements and CLI standardization reduce user errors and enhance the overall experience. 📚
- **Future-Proofing**: Keeps the project aligned with the latest software advancements, ensuring long-term reliability and efficiency. 🌟

This release is a significant step forward for developers and users leveraging YOLO11 for advanced AI tasks.

What's Changed
* Add bash codeblock formatting by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19804
* Add quotes for solutions CLI arguments by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19806
* Fix tip display in `YOLOE.md` by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19813
* FROM pytorch/pytorch:2.6.0-cuda12.6-cudnn9-runtime by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19817
* Require `coremltools>=8.0` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19819
* Add https://youtu.be/EXIpyYVEjoI to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19820
* Update GitHub banner redirect by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/19828
* `ultralytics 8.3.95` New `dockerfile-nvidia-cuda` FROM nvidia/cuda:12.8.1-cudnn-runtime-ubuntu22.04 by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/19833


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.3.94...v8.3.95