ultralytics 8.3.164

v8.3.164 - `ultralytics 8.3.164` Fix swapped mAP50 and mAP50-95 in COCOEval stats (#21350)

on Python PyPI

🌟 Summary

This release delivers a critical fix to YOLO detection validation metrics, improves dataset flexibility, enhances export reliability, and polishes documentation and developer experience. 🚀

📊 Key Changes

• Metrics Fix in YOLO Detection Validation: Corrected the assignment of mAP50 and mAP50-95 metrics, ensuring accurate reporting in validation results.
• Flexible Text Sample Handling in Datasets: Added a max_samples parameter for controlling the number of text samples in GroundingDataset and improved logic for negative text selection.
• Export Improvements & Warnings: Enhanced TensorRT export logic with better device handling and warnings for dynamic batch sizes, helping users avoid common pitfalls.
• Classification Dataset Compatibility: Now supports valid/ as a fallback validation folder, improving compatibility with Roboflow and similar dataset exports.
• Type Annotation Consistency: Standardized all references from numpy.ndarray to np.ndarray across code and documentation for clarity.
• HEIC Image Support Update: Switched from pillow_heif to pi-heif for HEIC image decoding, simplifying license compliance.
• Documentation & UI Enhancements:
  • Embedded a new YouTube video in the data annotation guide for easier learning.
  • Improved object counting example and clarified usage of the sweep_annotator method.
  • Removed unnecessary CSS animations from the Similarity Search web page for a faster, cleaner interface.
• Minor Fixes:
  • Corrected an error message in classification augmentations for better developer clarity.

🎯 Purpose & Impact

• Accurate Model Evaluation: Ensures that users and researchers see the correct mAP metrics, preventing confusion and supporting trustworthy model comparisons.
• Greater Dataset Flexibility: Developers can fine-tune text augmentation, leading to more efficient training and better use of resources.
• Smoother Model Export: Clearer export warnings and device handling reduce errors and improve deployment reliability, especially for advanced users exporting to TensorRT.
• Broader Dataset Compatibility: Makes it easier to use datasets from popular tools like Roboflow without manual folder renaming.
• Improved Developer Experience: Consistent type hints and clearer error messages make the codebase more approachable and maintainable.
• Better Documentation & Usability: New video resources and UI tweaks help both new and experienced users get started and work more efficiently.
• License Compliance: The change in HEIC image support ensures continued open-source compliance and easier integration in commercial projects.

This update is recommended for all users, especially those validating detection models, working with custom datasets, or exporting models for deployment. 🚀🛠️

What's Changed

• Fix inconsistent max_samples value between GroundingDataset and YOLOMultiModalDataset by @Y-T-G in #21286
• Add max batch warning for dynamic model with NMS by @Y-T-G in #21320
• Support valid/ as fallback validation folder for classification datasets by @JamesBond6873 in #21321
• Fix wrong error message in classify_augmentations by @Toprak2 in #21322
• Update Python hints for augmentation functions by @Laughing-q in #21329
• Eliminate extra CSS from similarity-search.html by @RizwanMunawar in #21335
• Update sweep_annotator example by @RizwanMunawar in #21331
• Switch pillow_heif to pi_heif by @picsalex in #21339
• Add https://youtu.be/iBk6S-PHwS0 to docs by @RizwanMunawar in #21346
• ultralytics 8.3.164 Fix swapped mAP50 and mAP50-95 in COCOEval stats by @Y-T-G in #21350

New Contributors

• @JamesBond6873 made their first contribution in #21321
• @Toprak2 made their first contribution in #21322

Full Changelog: v8.3.163...v8.3.164