vi/models/sam/

[giscus[bot]]

vi/models/sam/

Khám phá Mô hình Segment Anything mang tính cách mạng ( SAM ) để phân đoạn hình ảnh nhanh chóng với hiệu suất không cần chụp. Khám phá các tính năng chính, tập dữ liệu và mẹo sử dụng.

https://docs.ultralytics.com/vi/models/sam/

[UltralyticsAssistant]

👋 Hello, thank you for your interest in Ultralytics 🚀! We recommend a visit to the Docs where you can explore the revolutionary Segment Anything Model (SAM) for efficient image segmentation without the need for fine-tuning. The page details key features, datasets, and practical usage tips to help you get started!

If this is a 🐛 Bug Report, please provide a minimum reproducible example to facilitate debugging.

If this is a custom usage ❓ Question related to SAM, please provide as much information as possible, including example inputs, expected outcomes, and details about your environment to better assist you.

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Upgrade

Make sure you're using the latest ultralytics package, which includes all requirements, in a supported Python>=3.8 environment with PyTorch>=1.8 installed:

pip install -U ultralytics

Environments

You can experiment with SAM in the following verified environments, preloaded with all dependencies like Python and PyTorch:

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

Status

If this badge is green, all Ultralytics CI tests are currently passing. CI tests ensure proper functioning of all YOLO and SAM Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and whenever updates are committed.

This is an automated response to assist you quickly 😊. An Ultralytics engineer will follow up with more details soon!