ja/integrations/coreml/

[giscus[bot]]

ja/integrations/coreml/

iOS および macOS 上で最適化されたオンデバイス機械学習のためにYOLO11 モデルをCoreML にエクスポートする方法を学びます。ステップバイステップの指示に従ってください。

https://docs.ultralytics.com/ja/integrations/coreml/

[UltralyticsAssistant]

👋 Hello, thank you for bringing this up and for your interest in Ultralytics 🚀! We recommend checking out the detailed documentation on CoreML Integration for step-by-step guidance on how to export YOLO models for optimized on-device machine learning on iOS and macOS. 📱💻

If you're experiencing any specific issues or have further questions, feel free to provide more context. For 🐛 Bug Reports, it’s very helpful if you can include a minimum reproducible example to help us debug effectively. Make sure to also share any relevant details about your environment (e.g., macOS version, Python version, CoreML setup).

For new users exploring Ultralytics, don't forget to visit the Docs where you’ll find a wealth of information, including Python and CLI usage examples.

Join the Ultralytics community where it suits you best for real-time conversations, advice, and support:

• Discord 🎧
• Discourse for in-depth discussions
• Subreddit to connect with others in the community

Upgrade

To ensure you’re using the latest features and fixes, upgrade your ultralytics package in a Python>=3.8 environment with PyTorch>=1.8 as follows:

pip install -U ultralytics

Environments

Ultralytics models like YOLO11 can be run within verified environments. Check these options for streamlined deployment:

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. Refer to the GCP Quickstart Guide
• Amazon Deep Learning AMI. See the AWS Quickstart Guide
• Docker Image. Refer to the Docker Quickstart Guide

Status

If this badge is green, all Ultralytics CI tests for YOLO modes and tasks are passing successfully across macOS, Windows, and Ubuntu.

This is an automated response 🤖, but rest assured, an Ultralytics engineer will review your discussion and assist you shortly!