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YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite. Contribute to ultralytics/yolov5 development by creating an account on GitHub.
Discover Ultralytics YOLO - the latest in real-time object detection and image segmentation. Learn its features and maximize its potential in your projects.
Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use. They excel at object detection, tracking, instance segmentation, image classification, and pose estimation tasks. Find detailed documentation in the ...
YOLOv8 is a computer vision model architecture developed by Ultralytics, the creators of YOLOv5. Learn how to deploy, train, and find YOLOv8 models and datasets for various tasks, such as object detection, keypoint detection, and image classification.
YOLOV and YOLOV++ are high performance video object detectors based on YOLOX. This repo provides code, weights and results for different models and datasets, such as ImageNet VID and COCO.
Ultralytics YOLOv8 is a series of state-of-the-art object detection models for various tasks and applications. Learn about its key features, pre-trained models, and performance metrics for different modes and datasets.
YOLOv10 is a new model for real-time object detection, eliminating NMS and optimizing various components for efficiency and accuracy. It outperforms previous YOLO versions and other state-of-the-art models on COCO and other benchmarks.
YOLOv10 is a new generation of YOLO series for real-time end-to-end object detection, presented at NeurIPS 2024. It achieves state-of-the-art performance and efficiency with NMS-free training and holistic model design. See the paper, code, and benchmarks on GitHub.
You Only Look Once (YOLO) is a series of real-time object detection systems based on convolutional neural networks. First introduced by Joseph Redmon et al. in 2015, [1] YOLO has undergone several iterations and improvements, becoming one of the most popular object detection frameworks.
YOLOv5 is a fast, accurate, and easy to use model for object detection, instance segmentation and image classification. Learn how to install, load, and use YOLOv5 from PyTorch Hub with examples and tutorials.