pypi ultralytics 8.3.112
v8.3.112 - `ultralytics 8.3.12` New YOLO Multispectral Image Support (#20223)

latest releases: 8.3.122, 8.3.121, 8.3.120...
10 days ago

🌟 Summary

This release introduces full support for multispectral (multi-channel) images in the Ultralytics ecosystem, allowing YOLO models to train, validate, predict, and export with images containing more than 3 channels (e.g., 10-channel multispectral data). 🌈


πŸ“Š Key Changes

  • Multispectral Image Support:

    • Added robust handling for images with any number of channels (not just RGB) across all YOLO tasks (detection, segmentation, pose, classification, etc.).
    • Introduced a channels field in dataset configuration files to specify the number of image channels.
    • Updated data loaders, caching, and image reading utilities to correctly process multi-channel images, including TIFF support.
    • All model initialization, training, validation, and export routines now dynamically adapt to the dataset's channel count.
  • New COCO8-Multispectral Dataset:

    • Added a 10-channel multispectral version of the COCO8 dataset for rapid testing and experimentation.
    • Provided a utility to convert standard RGB images to multispectral format via interpolation.
    • Comprehensive documentation and usage examples for multispectral datasets.
  • Augmentation & Preprocessing Improvements:

    • Data augmentations and transformations now intelligently apply only to compatible channel configurations.
    • Enhanced plotting and visualization to handle multi-channel data gracefully.
  • Other Notable Updates:

    • Improved MobileSAM documentation for clarity and easier comparison with YOLO models.
    • Updated callbacks documentation with a new, more relevant YouTube tutorial.
    • Enhanced dataset splitting utilities and documentation for classification tasks.
    • Standardized logging for warnings and errors, making messages clearer and more consistent.
    • Improved test coverage for ARM64 systems and multispectral workflows.

🎯 Purpose & Impact

  • Unlocks Advanced Use Cases:

    • Enables researchers and practitioners to work with multispectral and hyperspectral imagery (e.g., satellite, medical, or scientific images) directly in Ultralytics and YOLO models.
    • Facilitates new applications in agriculture, remote sensing, and any domain requiring spectral analysis beyond standard RGB.
  • Seamless Integration:

    • Multispectral support is built-in and automaticβ€”no need for custom code or workarounds.
    • All core YOLO workflows (training, validation, prediction, export) now support multi-channel data out of the box.
  • Enhanced Experimentation:

    • The new COCO8-Multispectral dataset provides a quick, lightweight way to test multispectral pipelines and debug models.
    • Utility functions make it easy to convert existing datasets to multispectral format for experimentation.
  • Improved Usability & Documentation:

    • Clearer docs, better logging, and more robust dataset handling make the platform easier to use for both new and advanced users.
    • ARM64 and cross-platform improvements ensure broader compatibility.

In summary:
This update is a major step forward for users needing advanced image analysis, making Ultralytics and YOLO models more versatile and ready for real-world, multi-channel data challenges. πŸš€

What's Changed

Full Changelog: v8.3.111...v8.3.112

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