ultralytics 8.3.28

v8.3.28 - `ultralytics 8.3.28` new Solutions CLI commands (#17233)

on Python PyPI

🌟 Summary

The release of version 8.3.28 introduces new command-line interface (CLI) commands for "Solutions," allowing users to easily execute various video analytics tasks.

📊 Key Changes

• New Solutions CLI Commands: Users can now use CLI commands to apply different video analytics solutions without needing to modify arguments manually.
• Additional CLI Examples: Includes CLI examples for tasks like object counting, heatmaps, queue management, workout monitoring, speed estimation, and more, complete with customizable parameters.
• Enhanced Auto-Annotation: Improved auto-annotation functionality with new parameters like max_det to limit detections and classes for class-specific filtering.
• Updated Documentation and Badges: Enhancements in documentation accuracy with updated contributor details and added visibility via new badges in README files.
• Rust and TFLite Examples: New and improved examples for Rust ONNX runtime and TFLite Python integration for YOLO models.
• New Docker Support: Added a JupyterLab Docker image for improved interactive development support.

🎯 Purpose & Impact

• Ease of Use: Simplifies using video analytics solutions directly from the command line, making it more accessible for users to implement complex video tasks with YOLO models.
• Enhanced Control: Users gain more precise control over dataset annotation outputs, aiding in task-specific preparation.
• Improved Documentation: Allows for better tracking of project metrics and user interactions with enhanced visibility.
• Robust Cross-Platform Support: New examples and JupyterLab Docker integration support diverse environments, improving user experience and accessibility.
• Platform Precision: Export compatibility checks ensure smoother model conversions across different hardware setups.

Overall, this release significantly enhances usability and equips users with flexible tools for effective computer vision tasks.

What's Changed

• Fix Bboxes numpy.reshape by @Laughing-q in #17301
• Fix MNN Raspberry Pi benchmark attempt by @glenn-jocher in #17308
• Fix mkdocs_github_authors.yaml by @glenn-jocher in #17314
• Update mkdocs_github_authors.yaml by @glenn-jocher in #17320
• Refactor TFLite example. Support FP32, Fp16, INT8 models by @Y-T-G in #17317
• [Example] YOLO-Series(v5-11) ONNXRuntime Rust by @jamjamjon in #17311
• Fix Docker badges by @glenn-jocher in #17321
• Add ultralytics models publication notice in citations section by @RizwanMunawar in #17318
• Optimize Auto-Annotation with all args by @RizwanMunawar in #17315
• New JupyterLab Dockerfile by @ambitious-octopus in #17071
• Update overlap_mask description. by @Y-T-G in #17324
• Generalized M1/M2 references to "Apple silicon" in train.md for broader inclusion by @JairajJangle in #17330
• Add Albumentations Integrations Docs Page by @abirami-vina in #17297
• Fix error on TensorRT export with float workspace value by @Y-T-G in #17352
• Added Error for TFLite int8 end2end model export by @ambitious-octopus in #17360
• Update kfold-cross-validation.md by @M-Amrollahi in #17332
• ultralytics 8.3.28 new Solutions CLI commands by @RizwanMunawar in #17233

New Contributors

• @JairajJangle made their first contribution in #17330
• @M-Amrollahi made their first contribution in #17332

Full Changelog: v8.3.27...v8.3.28