fix(deps): update dependency ultralytics ( 8.3.163 → 8.3.165 ) - #51

v8.3.165: - ultralytics 8.3.165 Update datasets YAML's (#​21353)

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🌟 Summary

This release standardizes the folder structure for datasets in Ultralytics, making dataset paths more consistent and user-friendly across multiple YAML configuration files. 📁✨

📊 Key Changes

• Updated the version to 8.3.165.
• Unified dataset image paths in all relevant YAML files to follow a consistent structure: images/train, images/val, and images/test.
• Updated comments to reflect minor changes in dataset download sizes.

🎯 Purpose & Impact

• 🧩 Consistency: All datasets now use the same folder structure, reducing confusion and minimizing setup errors for users.
• 🚀 Ease of Use: Switching between datasets or automating workflows is now simpler, as you no longer need to adjust image paths for different datasets.
• 🛠️ Better Maintenance: This change streamlines future updates and documentation, making Ultralytics more approachable for both new and experienced users.

Overall, this update improves the reliability and usability of dataset management, helping users work more efficiently with Ultralytics models and tools.

What's Changed

• ultralytics 8.3.165 Update datasets YAML's by @​RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/21353

Full Changelog: ultralytics/ultralytics@v8.3.164...v8.3.165

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

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

New Contributors

• @​JamesBond6873 made their first contribution in https://github.com/ultralytics/ultralytics/pull/21321
• @​Toprak2 made their first contribution in https://github.com/ultralytics/ultralytics/pull/21322

Full Changelog: ultralytics/ultralytics@v8.3.163...v8.3.164