ultralytics 8.3.122

v8.3.122 - `ultralytics 8.3.122` Native Xcode preview of YOLO CoreML Classification models (#20437)

on Python PyPI

🌟 Summary

This release enhances CoreML export for YOLO classification models, introduces more accurate and user-friendly speed estimation, improves tracking and ReID documentation, and adds flexible installation options. 🚀🛠️

📊 Key Changes

• CoreML Export Enhancement: YOLO classification models exported to CoreML now include metadata for native Xcode preview support, making it easier to verify exports in Apple environments. 🍏📦
• Speed Estimation Simplified: Speed estimation no longer requires defining a region—just set the camera scale with meter_per_pixel for easier and more accurate results. New parameters (meter_per_pixel, max_speed, max_hist, fps) provide greater flexibility. 🚗💨
• Tracking & ReID Documentation: Expanded and clarified tracker configuration docs, including a detailed parameter table and step-by-step ReID (Re-Identification) setup for improved object tracking. Default appearance threshold for BoTSORT increased for stricter matching. 🏃‍♂️🔍
• Custom Installation Methods: Quickstart documentation now covers advanced installation scenarios, such as installing without dependencies, using custom forks, or swapping packages for server environments. 🛠️📚
• Dependency Updates: Removed version ceilings for streamlit and shapely, allowing compatibility with the latest releases. 🔄

🎯 Purpose & Impact

• Better Apple Ecosystem Support: Developers can now preview YOLO classification models directly in Xcode, streamlining iOS/macOS app development and debugging.
• Easier & More Accurate Speed Estimation: Users can calibrate speed estimation with a single parameter, reducing setup complexity and improving reliability—especially useful for traffic and surveillance applications.
• Improved Tracking Results: Clearer documentation and stricter defaults help users fine-tune tracking and ReID, leading to more robust multi-object tracking in challenging scenarios.
• Flexible Installations: Power users and system administrators can tailor Ultralytics installations for unique environments, such as headless servers or custom forks, improving integration and deployment workflows.
• Future-Proofing: By loosening dependency restrictions, Ultralytics stays compatible with the latest Python ecosystem updates.

This update is recommended for all users, especially those working with CoreML, speed estimation, advanced tracking, or custom installations! 🚀

What's Changed

• Improve speed estimation using track history and region-free calculation by @RizwanMunawar in #20344
• Add Custom Installation Section to Quickstart Docs by @glenn-jocher in #20430
• Remove streamlit>=1.29.0 and shapely>=2.0.0 version ceilings by @dependabot[bot] in #20045
• Add tracker and re-identification parameters to docs by @Y-T-G in #20435
• ultralytics 8.3.122 Native Xcode preview of YOLO CoreML Classification models by @rromanchuk in #20437

Full Changelog: v8.3.121...v8.3.122