indirme

[Muhammedokbi]

bunu yerel mi indiriyoruz

[oznurkarahasan]

evet

[UltralyticsAssistant]

👋 Hello @Muhammedokbi, thank you for your interest in Ultralytics 🚀! This is an automated response, and an Ultralytics engineer will also assist you soon 😊 In the meantime, we recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.

If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.

Join the Ultralytics community where it suits you best. For real-time chat, head to Discord 🎧. Prefer in-depth discussions? Check out Discourse. Or dive into threads on our Subreddit to share knowledge with the community.

Upgrade

Upgrade to the latest ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8 to verify your issue is not already resolved in the latest version:

pip install -U ultralytics

Environments

YOLO may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

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

Status

If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLO Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

[glenn-jocher]

Evet—yerel bilgisayarınızda kullanmak için ultralytics’i kurarsınız; yolo26n.pt gibi ağırlıklar ise siz predict/train çalıştırdığınızda otomatik indirilip Ultralytics önbelleğine kaydedilir (isterseniz kurulum seçenekleri için Ultralytics kurulum (Quickstart) sayfasına bakın).

yolo predict model=yolo26n.pt source=path/to/image.jpg