Ultralytics V8, 40 introduces per-image precision/recall/F1 tracking during validation (led by PR [#24089] from @Laughing-q), making it much easier to see exactly which images your model Train, Deploy, and Scale Ultralytics YOLO Models The end-to-end platform for building production-ready computer vision models. 55 - Now Available! We’re excited to announce the official release of Ultralytics v8. The standard in vision AI. 92 Release! We are excited to introduce the latest update to the Ultralytics YOLO ecosystem: YOLO v8. For those seeking the absolute bleeding edge of computer vision 探索 Ultralytics YOLOv8 概述 YOLOv8 由 Ultralytics 于 2023 年 1 月 10 日发布，在准确性和速度方面提供了尖端性能。基于先前 YOLO 版本的进步，YOLOv8 引 🌟 Summary Ultralytics v8. 126 Release: Smarter GPU Auto-Selection & Enhanced Usability! Hi everyone! We’re excited to announce Ultralytics v8. 88 Release Summary We’re thrilled to announce the release of Ultralytics v8. 154 Release – Unified Validation & Metric System, UI Upgrades, and More! 🌟 Summary We’re excited to announce the launch of Ultralytics v8. Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. 152 Release Announcement Hello YOLO community! We’re excited to announce the release of Ultralytics v8. 90, packed with crucial updates, performance boosts, and enhancements to make New Release: Ultralytics v8. 28! This update brings exciting new features, including command-line interface (CLI) commands for “Solutions,” enhanced 🚀 Ultralytics v8. 90 Release! We’re excited to announce the release of Ultralytics v8. 128! This release brings major strides in object Summary Ultralytics v8. 65 We’re excited to announce the release of Ultralytics v8. 4. 1. 37 is a quality + workflow-focused release: the tag PR itself is a version bump, while the main substance is improved hyperparameter tuning (now NDJSON-based for multi Discover efficient, flexible, and customizable multi-object tracking with Ultralytics YOLO. 95 Release! We are thrilled to announce the release of Ultralytics v8. Explore features, pretrained models, and implementation examples. 2. Ultralytics is thrilled to announce the release of YOLO v8. 91! This update focuses on simplifying TensorFlow installation, advancing Summary We’re thrilled to announce the release of Ultralytics v8. 58, packed with updates to help you optimize performance, streamline workflows, and On the 1st anniversary of Ultralytics YOLOv8 we reflect on its impact, where to find all the documentation, how train models and so much more! Discover how to use YOLO26 for pose estimation tasks. 20, packed with enhancements for improved efficiency and usability. 168 is here! This release delivers a major upgrade to how YOLO Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost Model Training with Ultralytics YOLO Introduction Training a deep learning model involves feeding it data and adjusting its parameters so that it We are excited to introduce Ultralytics v8. 55, packed with new features, key bug fixes, and enhanced Ultralytics v8. Comprehensive Tutorials for Ultralytics YOLO Welcome to Ultralytics' YOLO Guides. 198 delivers a major upgrade to hyperparameter tuning with BLX-α crossover, unified metric plotting across tasks, safer training defaults, and multiple robustness fixes Announcing Ultralytics v8. Learn to track real-time video streams with ease. 168 Released — Unified Prediction Export, Adaptive Annotations, and More! Summary Ultralytics v8. Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost Ultralytics v8. 0 is a testament to a year of innovation, with the integration of Oriented Object Detection, enhanced classification models, and a strong focus Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification. Learn about model training, validation, prediction, and exporting in various formats. 68 We are thrilled to announce the release of Ultralytics YOLOv8. 63 Release Announcement We’re excited to announce the release of Ultralytics YOLO v8. We’re excited to announce Ultralytics v8. 167 Release – Expanded Sony IMX Support, Smoother Visual Prompting, and More! Summary We’re excited to announce Ultralytics v8. Explore YOLOv8 computer vision models by Ultralytics. 68, packed with valuable updates to stay at the forefront of AI innovation. 148! This release focuses on improved reliability for model export workflows and enhanced error handling, making it easier to troubleshoot and New Release: Ultralytics v8. 3. 149, a release focused on export reliability, smoother video workflow integration, and expanded documentation to make your Ultralytics v8. Discover Ultralytics YOLOv8, an advancement in real-time object detection, optimizing performance with an array of pretrained models for diverse tasks. Learn how to install Ultralytics using pip, conda, or Docker. 0 is a testament to a year of innovation, with the integration of Oriented Object Detection, enhanced classification models, and a strong focus on user experience and To help streamline our codebase and focus our resources on maintaining comprehensive, up-to-date official documentation and guides, we plan to retire these examples in Ultralytics v8. 218 🚀 — True multi-GPU validation, contiguous sampler, and accurate cross-GPU metrics Ultralytics v8. Export mode in Ultralytics YOLO26 offers a versatile range of Model Export with Ultralytics YOLO Introduction The ultimate goal of training a model is to deploy it for real-world applications. This release 一、Ultralytics安装 网址： 主页 -Ultralytics YOLO 文档 Ultralytics提供了各种安装方法，包括pip、conda和Docker。 通过 ultralytics pip包安装最新稳 Ultralytics YOLO 🚀. Python Usage Welcome to the Ultralytics YOLO Python Usage documentation! This guide is designed to help you seamlessly integrate Learn how to install Ultralytics using pip, conda, or Docker. 0. YOLOv8 is a computer vision model architecture developed by Ultralytics, the creators of YOLOv5. 36 is a stability-focused release that fixes an important training regression for checkpoint-based workflows (especially Ultralytics Platform/HUB Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and Discover YOLOv8, the latest advancement from Ultralytics for real-time object detection, segmentation, and classification. 158! This update focuses on making image classification workflows more reliable and boosting the usability of our Streamlit inference tool. 113 is out now, bringing groundbreaking multispectral dataset support, smarter multi-channel image processing, new device flexibility with Intel/OpenVINO, and a Ultralytics v8. You can deploy YOLOv8 models on a wide range of Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. 58! This update brings several exciting enhancements and optimizations to improve your experience with our YOLO models Discover YOLOv10 for real-time object detection, eliminating NMS and boosting efficiency. 38 Release! We’re excited to share the release of Ultralytics v8. 128 Release: Enhanced Tracking, Multi-GPU Reliability, and Global Docs! Summary We’re thrilled to introduce Ultralytics v8. This release enables true multi-GPU validation during training with correct cross-GPU metric aggregation and a new Ultralytics v8. Constantly updated for Ultralytics YOLOv5 🚀 is a cutting-edge, state-of-the-art (SOTA) computer vision model developed by Ultralytics. 112 Release – Full Multispectral Support, COCO8-Multispectral, and More! Summary We’re excited to announce Ultralytics v8. 126 —a release focused on smarter hardware Announcing Ultralytics v8. 154! This release unifies We are thrilled to announce the release of Ultralytics YOLO v8. From in-depth tutorials to seamless GS-YOLO / ultralytics / cfg / models / v8 / yoloe-v8. This release focuses on cleaner outputs, easier Announcing Ultralytics v8. 38, packed with new features and enhancements to make your computer vision journey even Learn how to evaluate your YOLO26 model's performance in real-world scenarios using benchmark mode. Ideal for businesses, academics, tech-users, The engine behind the platform. 116 — a feature-rich release designed to make your computer vision journey Models Supported by Ultralytics Welcome to Ultralytics' model documentation! We offer support for a wide range of models, each tailored to Ultralytics v8. 88, packed with exciting new features, impactful enhancements, and critical bug We’re thrilled to announce the release of Ultralytics v8. Based on the PyTorch framework, YOLOv5 is Object Detection Object detection is a task that involves identifying the location and class of objects in an image or video stream. Explore the revolution in AI. 80, a release packed with significant improvements to model export workflows, documentation usability, Summary We’re excited to announce Ultralytics v8. 95, packed with powerful new features, enhancements, and improvements designed The Ultralytics team is excited to announce the release of v8. Follow our step-by-step guide for a seamless setup of Ultralytics YOLO. . 116 Release Announcement Summary We’re excited to announce Ultralytics v8. 80 Release We’re excited to introduce Ultralytics v8. 112! This release brings built-in Ultralytics v8. 52 Release Announcement We are thrilled to announce the release of Ultralytics v8. Welcome to the Ultralytics YOLO wiki! 🎯 Here, you'll find all the resources you need to get the most out of the YOLO object detection framework. 49 ! Packed with features to enhance usability, documentation, PyTorch Learn everything you need to know about Ultralytics YOLOv8, the latest version of the popular You Only Look Once (YOLO) object detection Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost New Release: Ultralytics v8. 167, a release packed with valuable Announcing Ultralytics v8. 39 is a quality-and-usability release focused on clearer run naming (exp-2), better CLI coverage for Solutions, safer rotated-box training behavior, and broad Ultralytics HUB Experience seamless AI with Ultralytics HUB ⭐, the all-in-one solution for data visualization, YOLOv5 and YOLOv8 🚀 model training and This comprehensive technical comparison explores the generational leap from Ultralytics YOLOv8, a wildly popular architecture that redefined the standard in 2023, to the cutting-edge Ultralytics Explore Ultralytics YOLO models - a state-of-the-art AI architecture designed for highly-accurate vision AI modeling. Achieve top performance with a low computational cost. This Announcing YOLO v8. Discover YOLO-NAS by Deci AI - a state-of-the-art object detection model with quantization support. 49 We’re thrilled to announce the latest release of Ultralytics, version 8. Ultralytics Release v8. 41 is out! Quick summary: Ultralytics v8. 160 Release Announcement! Summary We’re excited to announce Ultralytics v8. Experiments on VisDrone and SIMD show it Ultralytics v8. Train, evaluate, and deploy models for detection, segmentation, and classification on Ultralytics Platform. yaml bearono-s Add full GS-YOLO project code abb84ea · 2 weeks ago We propose GS-YOLO, a lightweight detector equipped with EAG-Stem, GDCM and SA-WIoU loss to enhance small-object feature learning and localization. 70, packed with powerful enhancements for smoother workflows, expanded hardware compatibility, and usability improvements. Export mode in Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and Datasets Overview Ultralytics provides support for various datasets to facilitate computer vision tasks such as detection, instance segmentation, Use W&B with Ultralytics YOLO models for experiment tracking, model checkpointing, and computer vision visualization. 20 Release! Summary We’re excited to announce the release of Ultralytics version 8. Built on the PyTorch framework, this implementation extends the original YOLOv3 architecture, renowned for its Ultralytics v8. From Ultralytics YOLOv5 to the groundbreaking YOLO26, Ultralytics builds and maintains the most widely Explore Ultralytics Enterprise Licensing: Tailored solutions for businesses seeking seamless integration of cutting-edge AI models and software into commercial Why use YOLO26 for instance segmentation? Ultralytics YOLO26 is a state-of-the-art model recognized for its high accuracy and real-time Ultralytics v8. 84, packed with meaningful improvements to segmentation, documentation, and model usability. 63, featuring improvements in stability, streamlined processes for Announcing Ultralytics v8. Optimize speed, accuracy, and 🚀 Announcing Ultralytics YOLO v8. 52, packed with exciting new features, improved functionality, and thorough Ultralytics v8. Contribute to ultralytics/ultralytics development by creating an account on GitHub. Discover YOLOv8, the latest advancement from Ultralytics for real-time object detection, segmentation, and classification. 101, introducing major enhancements to the YOLOE model! This update focuses on simplifying video/stream handling, Ultralytics YOLOv3 is a robust and efficient computer vision model developed by Ultralytics. Constantly updated for 🎉 Ultralytics v8. 78, we’ve expanded the YOLO family with YOLO12, combining cutting-edge attention mechanisms with Ultralytics’ innovation. Announcing Ultralytics v8. 56, packed with exciting features, essential bug fixes, and valuable improvements designed to enhance the user experience. 152, packed with enhancements focusing on segmentation Summary With v8. The output of an Ultralytics YOLO11 Overview YOLO11 was released by Ultralytics on September 10, 2024, delivering excellent accuracy, speed, and efficiency. 218 delivers reliable, faster multi-GPU training. 228 is live Quick summary: This release makes CLIP/MobileCLIP tokenization safer by default with a new truncate option to prevent crashes on long prompts, Ultralytics YOLO v8. 92! This release is packed with crucial improvements, new We’re excited to announce the release of Ultralytics v8. YOLO12 delivers state-of-the-art Ultralytics v8. Our comprehensive tutorials cover various aspects of the YOLO Model Prediction with Ultralytics YOLO Introduction In the world of machine learning and computer vision, the process of making sense of visual data is often called inference or prediction. This release Summary We’re excited to announce Ultralytics v8. Model Export with Ultralytics YOLO Introduction The ultimate goal of training a model is to deploy it for real-world applications. Ultralytics v8. 41 delivers a major SAM3 video tracking quality fix to reduce ghost IDs 👻, a safer NDJSON dataset conversion pipeline for parallel Ultralytics v8. 91 Release 🌟 Summary We’re thrilled to announce the release of YOLO v8. Developers interested in state-of-the-art performance should also explore YOLO11, which builds upon v8 with improved precision and speed. 65, packed with new features, enhancements, and fixes designed to expand capabilities and Ultralytics v8. 86, a quality-of-life update packed with improvements to dataset handling, model accuracy, and code performance. 58 Release Announcement We’re excited to announce the release of Ultralytics v8. 178 delivers a major Docker overhaul with a clear Discover Ultralytics integrations for streamlined ML workflows, dataset management, optimized model training, and robust deployment solutions. 160! This release brings major improvements to keypoint handling, data Title: Ultralytics v8. Train Ultralytics YOLO models, manage datasets, and deploy with one click. 178 – Faster, lighter Docker images, export-ready workflows, and smoother preprocessing Summary Ultralytics v8.
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