sunsmarterjie/yolov12

Health v2 · maintenance only

Adoption not part of the score

2947 stars · 431 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

YOLOv12 is a PyTorch implementation of attention-centric real-time object detectors, published at NeurIPS 2025. It provides detection models plus classification and instance segmentation variants, with a faster YOLOv12-turbo version.

Use cases

• train a custom object detection model
• real-time object detection with attention
• instance segmentation on images
• image classification with yolo models
• deploy a fast object detector
• detect objects in images with python

When to choose

• you need state-of-the-art real-time detection with attention-based architecture
• you want the official efficient YOLOv12 implementation rather than the ultralytics port
• you need detection, segmentation, and classification from one model family

When to avoid

• you need a permissively licensed model for closed-source products (AGPL-3.0)
• you need a battle-tested production framework with broad ecosystem support
• you only need simple pretrained inference without training

Facets

library · maturity active

computer-vision machine-learning deep-learning image-processing computer-vision deep-learning machine-learning image-processing python cross-platform object-detection yolo attention-mechanism real-time-inference instance-segmentation image-classification research-code pytorch gpu

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