Ultralytics

🌟 Summary

The v8.2.73 release of Ultralytics introduces significant updates to the Segment Anything Model (SAM) architecture, including new support for SAM 2, which enhances real-time image segmentation capabilities and documentation improvements.

📊 Key Changes

- **Addition of SAM 2 Models**: Introduced new methods for building various SAM 2 models, including `build_sam2_t`, `build_sam2_s`, `build_sam2_b`, and `build_sam2_l`.
- **Enhanced Documentation**: Added comprehensive documentation for SAM and SAM 2 modules, including blocks, decoders, encoders, and memory attention modules.
- **Updated Predictors**: Integrated SAM2Predictor for advanced segmentation prediction, enhancing the overall prediction framework.
- **Expanded API References**: Updated the API references to include new SAM2 modules and their functionalities, ensuring better clarity and usability for developers.

🎯 Purpose & Impact

- **Improved Segmentation Capabilities**: The addition of SAM 2 models significantly enhances the real-time image segmentation capabilities, allowing users to leverage advanced features for more accurate and efficient segmentation tasks.
- **Comprehensive Documentation**: The improved and expanded documentation provides detailed references and examples for both SAM and SAM 2 models, making it easier for users to understand and implement the models in their projects.
- **Upgraded Prediction Framework**: The integration of SAM2Predictor ensures that the prediction framework is robust and capable of handling advanced segmentation tasks, benefiting users with more reliable and efficient predictions.

🔧 Technical Details

- **Model Initialization**: Enhanced the initialization and building process for SAM and SAM 2 models, ensuring that the models are correctly configured with the specified architecture parameters.
- **Attention Mechanisms**: Improved attention mechanisms with the introduction of SAM2TwoWayAttentionBlock and SAM2TwoWayTransformer, providing more efficient attention computations in the models.

What's Changed
* `ultralytics 8.2.73` Meta SAM2 Refactor by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14867


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.72...v8.2.73

🌟 Summary
Ultralytics 'v8.2.72' release focuses on enhancing disk space management, updating documentation, refining model code, and improving testing.

📊 Key Changes
- **Disk Space Management**: Added a step in CI workflows to clean up tool cache, potentially freeing up to 10GB of disk space.
- **Documentation**:
- Improved `CONTRIBUTING.md` with better references and added an FAQ section.
- Updated ROS Quickstart guide for better clarity and specific use cases.
- **Model Enhancements**:
- Adjustments in SAM prediction models for better handling of bounding boxes and points.
- Refined Transformer model's `forward` method.
- **Testing Improvements**: Added extra checks for Torch compatibility in tests.

🎯 Purpose & Impact
- **Disk Space Management**:
- **Purpose**: Ensure workflows run smoothly without disk space issues.
- **Impact**: Enhanced reliability in CI pipelines, preventing build failures due to insufficient disk space. 🧹💾
- **Documentation**:
- **Purpose**: Provide clearer guidance and support to contributors.
- **Impact**: Makes contributing easier and more accessible, fostering community contributions. 📖👥
- **Model Enhancements**:
- **Purpose**: Optimize model predictions and enhance functionality.
- **Impact**: Improves performance and accuracy of object detection and other tasks. 📈🤖
- **Testing Improvements**:
- **Purpose**: Ensure better compatibility and comprehensive testing.
- **Impact**: Increases robustness and reliability of the software across different environments. ✅🧪

These updates collectively aim to improve the project's maintainability, user experience, and performance.

What's Changed
* Delete Docker Cache before building Image by lakshanthad in https://github.com/ultralytics/ultralytics/pull/14894
* ROS quickstart meta description by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/14932
* Fix the docstring of xywhr2xyxyxyxy by patel-zeel in https://github.com/ultralytics/ultralytics/pull/14934
* Fixed `circle_label` and `text_label` docstrings by jk4e in https://github.com/ultralytics/ultralytics/pull/14909
* Fix `is_url()` and `check_disk_space()` docstrings in downloads.py by jk4e in https://github.com/ultralytics/ultralytics/pull/14923
* Update MLP module for RTDETR backward compatibility by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14901
* Corrects CONTRIBUTING.md relative link to CLA.md by Burhan-Q in https://github.com/ultralytics/ultralytics/pull/14857
* `ultralytics 8.2.72` SAM 2 multiple-`bboxes` support by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14928

New Contributors
* patel-zeel made their first contribution in https://github.com/ultralytics/ultralytics/pull/14934

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.71...v8.2.72

🌟 Summary
The Ultralytics `v8.2.71` release focuses on refining model training commands, enhancing the CLI, and fixing some documentation inconsistencies.

📊 Key Changes
- **Matrix Parallelism**: Increased max-parallel jobs from 6 to 10.
- **Retry Logic Modification**: Adjusted retry wait time from 30 to 60 seconds.
- **Documentation Fixes**: Corrected CLI commands for training (`yolo classify train`, `yolo segment train`, `yolo obb train`, `yolo pose train`) and removed some outdated notes on SAM 2.
- **Gitignore Update**: Added `requirements.txt`, `setup.py`, and other files to the `.gitignore` list.
- **CLI Enhancements**: Updated CLI task options to include `obb` and added a new mode `benchmark`.

🎯 Purpose & Impact
- **Enhanced Parallelism**: Increasing max parallel jobs accelerates CI workflows, thereby improving overall efficiency and quicker feedback loops. 🚀
- **Improved Job Reliability**: With longer wait times before retrying jobs, the update aims to reduce the number of job failures, making the process more robust. 🛠️
- **Command Accuracy**: The corrected training commands ensure that users are employing the right commands, reducing the chances of errors and improving user experience. ✅
- **Refined CLI Use**: The added `obb` task option and `benchmark` mode provide users with more versatility and capabilities within the CLI, enabling better performance analysis and use-case flexibility. 💡

🌟 Summary
The `v8.2.70` release of Ultralytics brings valuable enhancements, such as integrating `Black` code formatter and adding substantial documentation, especially around SAM2 (Segment Anything Model 2).

📊 Key Changes
- **Workflow Adjustment**: The GitHub Actions workflow now includes the installation of `Black` for consistent code formatting.
- **Documentation Expansion**: Significant additions to the documentation, including detailed guides and FAQ sections for various integrations and models.
- **New Model Support**: Introduction of support for SAM2, an enhanced model for comprehensive object segmentation in images and videos.

🎯 Purpose & Impact
- **Consistency in Code Formatting**: Adding `Black` to the GitHub Actions workflow ensures that the code base maintains consistent formatting standards, reducing errors and improving readability.
- **Enhanced Documentation**: New and updated documentation provides users with better guidance and understanding of using various models and integrations. Non-expert users can benefit from the clear explanations and examples, while expert developers can delve into the detailed technical aspects.
- **Advanced Model Capabilities**: Supporting SAM2 broadens the capability of the Ultralyics framework, especially for complex image and video segmentation tasks. The improvements and new features in SAM2, such as real-time performance and zero-shot generalization, can significantly impact applications in fields requiring precise and efficient object segmentation.

This release improves the user experience with better documentation and more powerful tools for both developers and end-users. 🚀

What's Changed
* Update comet from init() to login() by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14793
* New Meta Segment Anything Model 2 (SAM2) Docs page by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14794
* SAM2 mkdocs.yml fix by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14796
* `py-cpuinfo` Exception context manager fix by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14814
* Add https://youtu.be/_gRqR-miFPE & https://youtu.be/CfbHwPG01cE to docs by RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/14817
* `ultralytics 8.2.70` Segment Anything Model 2 (SAM 2) by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14813


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.69...v8.2.70

🌟 Summary
Release `v8.2.69` brings improvements to issue templates, documentation, FastSAM’s prompt handling, and the introduction of IBM Watsonx and JupyterLab integrations.

📊 Key Changes
- **Issue Templates Updates**:
- Standardized language in bug report and question templates to consistently reference "Ultralytics YOLO".
- **Documentation Enhancements**:
- Detailed guides on integrating IBM Watsonx and JupyterLab for model training.
- Minor formatting and structural enhancements in various dataset and integration documentation.
- **FastSAM Enhancements**:
- Merged all prompting functionalities directly into `FastSAM` class, removing the need for `FastSAMPrompt`.
- Simplified and optimized the handling of multiple prompt types (bounding boxes, points, texts).
- **Bug Fixes**:
- Fixed class imbalance augmentation issue in data augmentation script.
- Formatting corrections in Google Cloud region latency output.

🎯 Purpose & Impact
- **Improved Usability**:
- Standardized templates help users provide more consistent and comprehensive bug reports and questions, facilitating faster and more accurate triaging.
- **Enhanced Documentation**:
- New IBM Watsonx and JupyterLab integration guides enable users to expand their training environments, offering more flexibility and productivity in model training and experimentation.
- **Streamlined FastSAM Prompting**:
- Integrating prompts into the FastSAM class simplifies usage, making it easier for users to apply multiple prompt types in a single call and improving model inference performance.
- **Enhanced Augmentation and Debugging**:
- Fixing the class imbalance augmentation issue ensures more reliable and balanced training data generation.
- Clearer formatting in latency outputs aids in the easier identification of the best Google Cloud regions for deployment.

These updates focus on enhancing user experience, expanding documentation, and improving model functionalities for more efficient and effective workflows. 🚀

What's Changed
* Add JupyterLab Integrations Docs Page by abirami-vina in https://github.com/ultralytics/ultralytics/pull/14755
* Fixed typo and formatting OpenVINO integration by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/14773
* Add IBM Watsonx Integrations Docs Page by abirami-vina in https://github.com/ultralytics/ultralytics/pull/14785
* Update Ultralytics issue templates by ambitious-octopus in https://github.com/ultralytics/ultralytics/pull/14718
* Eliminate `set()` to avoid `set()` + `list()` op by QinghongLin in https://github.com/ultralytics/ultralytics/pull/14745
* `ultralytics 8.2.69` FastSAM prompt inference refactor by Laughing-q in https://github.com/ultralytics/ultralytics/pull/14724

New Contributors
* QinghongLin made their first contribution in https://github.com/ultralytics/ultralytics/pull/14745

**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.68...v8.2.69

🌟 Summary
Release v8.2.68 includes significant updates to Ultralytics' Docker setup and adds a new class for Google Cloud Platform (GCP) region analysis.

📊 Key Changes
- **Dockerfile Updates**:
- Standardized working directory to `/ultralytics` across all Dockerfiles.
- Removed redundant environment variable `APP_HOME`.
- Updated volume mounts to `/datasets` instead of `/usr/src/datasets`.
- **GCP Support**:
- Added a new `GCPRegions` class in `ultralytics/hub/google/__init__.py` to check and analyze latency across GCP regions.
- **Documentation**:
- Added new reference docs for the `GCPRegions` class.

🎯 Purpose & Impact
- **Dockerfile Updates**:
- **Purpose**: Simplify the Docker setup and ensure consistency across different Docker environments.
- **Impact**: Easier management and setup of Docker containers. This can lead to fewer errors and a smoother development experience.
- **GCP Support**:
- **Purpose**: Provide tools for analyzing and selecting the optimal GCP regions based on latency.
- **Impact**: Users deploying Ultralytics services on GCP can now optimize latency, which can enhance performance and user experience.
- **Documentation**:
- **Purpose**: Offer clear guidance and reference for the new `GCPRegions` functionality.
- **Impact**: Improves user understanding and usability of the new features, making it easier for users to implement and benefit from them.

What's Changed
* Simplify Dockerfile `WORKDIR` by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14750
* `ultralytics 8.2.68` new HUB GCP region latency tests by glenn-jocher in https://github.com/ultralytics/ultralytics/pull/14753


**Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.2.67...v8.2.68