ultralytics 8.3.249

v8.3.249 - `ultralytics 8.3.249` Jetson AGX Thor and DGX Spark Docker (#23111)

on Python PyPI

🌟 Summary (single-line synopsis)

Ultralytics 8.3.249 adds an official NVIDIA ARM64 Docker image for running YOLO11 on JetPack 7 / ARM64 GPUs (plus a few usability + contributor/docs improvements) 🚀🐳

📊 Key Changes

• 🐳 New Docker image for NVIDIA ARM64 (JetPack 7 / ARM64 GPUs)
  • Added docker/Dockerfile-nvidia-arm64 based on NVIDIA’s PyTorch NGC image (nvcr.io/nvidia/pytorch:25.10-py3)
  • CI now builds & publishes ultralytics/ultralytics:latest-nvidia-arm64
  • Container tweaks for smoother out-of-the-box use:
    • Uses opencv-python-headless (avoids GUI dependency issues in containers) 🧩
    • Installs ARM64 onnxruntime_gpu + reinstalls torch/torchvision for CUDA compatibility 🔥
    • Preloads Ultralytics fonts + includes a default YOLO11 model (yolo11n.pt) 📦
  • JetPack 7 docs updated with pull/run commands ✅
• 🔗 Support for ul:// URIs (Ultralytics Platform / HUB-style referencing)
  • New resolve_platform_uri() resolves ul://... into signed download URLs (using ULTRALYTICS_API_KEY)
  • check_file() now accepts ul://... and automatically downloads/caches the file locally 📥🗂️
  • Better error messages for invalid keys, forbidden access, not found, and “still processing” cases 🚦
• 🧮 Fix: ObjectCounter label display logic
  • Corrected operator precedence in ObjectCounter.display_counts so show_in / show_out flags behave correctly (prevents empty/incorrect labels) 🛠️
• 📝 Contributor workflow improvements
  • Updated CONTRIBUTING.md with PR size/scope guidance, feature PR expectations, and automated review notes to streamline contributions 🤝

🎯 Purpose & Impact

• 🚀 Easier deployment on new NVIDIA ARM64 platforms (Jetson AGX Thor, DGX Spark, JetPack 7)
  • Reduces setup friction (drivers/libs/Python deps) and gets users to a working YOLO11 environment faster—especially useful for edge + embedded deployments.
• 🐳 More consistent “it just works” container experience
  • Headless OpenCV and pinned runtime dependencies lower the chance of common container runtime/import issues, improving reliability for production and CI.
• 🔗 Simpler sharing & reproducibility with ul://
  • Users can reference datasets/models by a short URI and let Ultralytics handle secure resolution + download, making scripts and configs cleaner and more portable.
• ✅ Cleaner analytics overlays in ObjectCounter
  • Prevents misleading or empty class labels when only IN/OUT is enabled—better visual outputs with fewer surprises.
• 📘 Faster, clearer open-source contributions
  • Better guidelines help contributors submit reviewable PRs, which can speed up merges and reduce back-and-forth.

If you want to try the new ARM64 image on JetPack 7:

t=ultralytics/ultralytics:latest-nvidia-arm64
sudo docker pull $t && sudo docker run -it --ipc=host --runtime=nvidia $t

What's Changed

• Add scope and PR size guidelines to CONTRIBUTING.md by @Y-T-G in #23133
• Fix typo in CONTRIBUTING.md guidelines by @Y-T-G in #23134
• Fix operator precedence in ObjectCounter.display_counts by @raimbekovm in #23132
• URI resolution by @glenn-jocher in #23136
• ultralytics 8.3.249 Jetson AGX Thor and DGX Spark Docker by @lakshanthad in #23111

Full Changelog: v8.3.248...v8.3.249