v8.4.9 - `ultralytics 8.4.9` Hyperspectral CopyPaste augmentation (#23471) - ultralytics Release Notes

## 🌟 Summary (single-line synopsis) Ultralytics **v8.4.9** improves **segmentation CopyPaste augmentation reliability** (especially for **grayscale/hyperspectral-style single-channel inputs**) and strengthens the broader export/training ecosystem with better ExecuTorch + Torch support 🚀🧩 ## 📊 Key Changes - 🧪 **(Priority) Segmentation CopyPaste mask fix** in `ultralytics/data/augment.py`: - Builds the contour mask as a **2D (H×W) array** instead of matching the full image tensor shape. - Draws contours onto a **single-channel mask** using value `1` (instead of `(1,1,1)`), avoiding channel mismatches. - 🧾 **Version bump:** `8.4.8 → 8.4.9` 🔢 - 📦 **NDJSON datasets always re-download** when using `ul://...` URIs (instead of silently reusing a cached `.ndjson`) 🧹⬇️ - ⚙️ **ExecuTorch support improvements**: - Removes the `<2.10` PyTorch upper bound in dependencies (Windows still excludes `torch==2.4.0`) 🔓 - Centralizes ExecuTorch install checks via `check_executorch_requirements()` to reduce platform-specific install failures 🧩 - ⚡ **Training + compile coverage:** CUDA test now trains with `compile=True`, and stride calculation is simplified for more predictable behavior 🧠🔥 - 📚 **Docs refresh:** Export docs video updated to a more relevant **YOLO26 export/deployment** tutorial 🎥 ## 🎯 Purpose & Impact - 🧩 **More robust segmentation augmentation**: prevents mask shape/channel bugs that can break or silently degrade CopyPaste-based training—especially when images are **single-channel** (common in grayscale and some hyperspectral pipelines) 📷✅ - 📈 **More reliable segmentation training**: fewer augmentation edge cases means smoother training runs and more consistent results 🏋️♂️📊 - 🧹 **Less “stale dataset” confusion**: always refreshing `.ndjson` metadata helps ensure you train/evaluate on the **latest Ultralytics-hosted dataset state** when using `ul://...` 🔄🧪 - 🚀 **Better export/inference readiness on modern stacks**: improved ExecuTorch requirement handling + Torch 2.10+ compatibility reduces install friction and improves deployment workflows 📦⚙️ - ⚡ **Safer `compile=True` usage**: better test coverage helps catch regressions for users relying on PyTorch compile for potential speedups 🧠🛠️ ## What's Changed * Always redownload NDJSON datasets by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/23458 * feat(executorch): Add support for Torch 2.10 in ExecuTorch requirements and imports and remove torch<2.10 pin by @onuralpszr in https://github.com/ultralytics/ultralytics/pull/23344 * Add missing type hints to `checks.py` and `dist.py` by @ahmet-f-gumustas in https://github.com/ultralytics/ultralytics/pull/23485 * Add https://youtu.be/KGHYU-MKYeE to docs by @RizwanMunawar in https://github.com/ultralytics/ultralytics/pull/23463 * Fix training with `compile` by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/23479 * refactor: ♻️ Simplify requirement checks for executorch by @onuralpszr in https://github.com/ultralytics/ultralytics/pull/23475 * `ultralytics 8.4.9` Hyperspectral CopyPaste augmentation by @Y-T-G in https://github.com/ultralytics/ultralytics/pull/23471 **Full Changelog**: https://github.com/ultralytics/ultralytics/compare/v8.4.8...v8.4.9

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v8.4.9 - `ultralytics 8.4.9` Hyperspectral CopyPaste augmentation (#23471)

🌟 Summary (single-line synopsis)

📊 Key Changes

🎯 Purpose & Impact

What's Changed