Ultralytics version py build; Ultralytics YOLO11 Vue d'ensemble. YOLO11 basiert auf den neuesten Entwicklungen in den Bereichen Deep Learning und Computer Vision und bietet eine unvergleichliche Leistung in Bezug auf Geschwindigkeit und Genauigkeit. 49,<9. We hope that the resources here will help you get the most out of YOLO. For my situation, cloning the repo is not desirable. 7. That's why even though I've run pip install ultralytics==8. 58 Release! Hello Ultralytics Community! We are thrilled to announce the release of Ultralytics YOLO v8. version. I use torch to set the device to cuda but still not working on my GPU. Mar 17, 2025 · Ultralytics is a computer vision AI company specializing in state-of-the-art object detection and image segmentation models, with a focus on the YOLO (You Only Look Dec 5, 2024 · It will also automatically pin the ultralytics version to 8. Mar 19, 2025 · YOLOv5: An improved version of the YOLO architecture by Ultralytics, offering better performance and speed trade-offs compared to previous versions. 0 Using device="cpu" or not having any CUDA devices available for inference using Ultralytics YOLO What’s not impacted As far as our testing Ultralytics YOLOv5 🚀 is a cutting-edge, state-of-the-art (SOTA) computer vision model developed by Ultralytics. YOLO11 is built on cutting-edge advancements in deep learning and computer vision, offering unparalleled performance in terms of speed and accuracy. Ultralytics has 43 repositories available. Jan 13, 2025 · Search before asking I have searched the Ultralytics YOLO issues and found no similar bug report. We are planning on implementing some sandboxing in our desktop app in the future to better protect against these types of attacks. 95 release Sep 3, 2024 · 🌟 Ultralytics Release v8. Mar 4, 2025 · This page offers a detailed technical comparison between Ultralytics YOLO11 and Ultralytics YOLOv8, two state-of-the-art models designed for object detection and other vision tasks. 87 Summary We are excited to announce the release of Ultralytics v8. 3. Please install the official `ultralytics` package via `pip install ultralytics Apr 8, 2025 · Configuring INT8 Export. Nous travaillons actuellement à une intégration directe et étroite entre YOLOv8 et Ultralytics HUB , qui permettra automatiquement aux utilisateurs de visualiser les mesures et les pertes de leur modèle, de prévisualiser les prédictions et de les comparer à d'autres modèles, publics ou privés. 85! This update brings significant enhancements, including new features, improved workflows, and better compatibility across the platform. Sample Datasets: Included a selection of curated datasets for testing, demonstration, and benchmarking purposes, showcasing the capabilities of Ultralytics' models. Mahmoud Atta Mohammed Ali, Tarek Aly, Atef Tayh Raslan, Mervat Gheith, Essam A. The HUB also supports collaboration, making it easy for teams to work together on AI projects. YOLO11 est la dernière itération de la série des détecteurs d'objets en temps réel. Conditions for issue Windows computers Using torch==2. version) ``` 这种方法同样适用于大多数现代 Python 包管理场景下确定软件包的确切 pip を使ってUltralytics をインストールするには？ conda を使ってUltralytics YOLO をインストールできますか？ Ultralytics YOLO を実行するためにDockerを使用する利点は何ですか？ 開発用にUltralytics リポジトリをクローンするには？ なぜUltralytics YOLO CLI を使うべきなの pip を使ってUltralytics をインストールするには？ conda を使ってUltralytics YOLO をインストールできますか？ Ultralytics YOLO を実行するためにDockerを使用する利点は何ですか？ 開発用にUltralytics リポジトリをクローンするには？ なぜUltralytics YOLO CLI を使うべきなの Ultralytics Docsは、Ultralytics 特徴や機能を理解し、活用するために設計された包括的なリソースです。 このハブは、あなたが 機械学習の 経験者であろうと初心者であろうと、あなたのプロジェクトでYOLO可能性を最大限に引き出すことを目的としています。 Aug 19, 2024 · 🚀 Announcing Ultralytics YOLO v8. 134. We unveiled major features like ‘Teams Dec 6, 2023 · 要查看已安装的 `ultralytics` 库的具体版本号，可以按照以下步骤操作： ### 方法一：通过 Python 解释器直接查看 你可以打开一个命令行工具（如 Windows 的 CMD 或 PowerShell，macOS/Linux 的终端），然后运行以下命令进入 Python 交互模式，并导入 `ultralytics` 模块以获取其 Jul 26, 2024 · What going on? :pytorch: PyTorch 2. Mar 28, 2024 · 问题，在使用ultralytics训练yolov8-obb模型时，修改了ultralytics源码的网络结构，发现调用的还是pip install安装的ultralytics库，新版本源码中还没有setup. Vous pouvez installer YOLO via la méthode ultralytics pip pour la dernière version stable, ou en clonant le paquetage Ultralytics Dépôt GitHub pour obtenir la version la plus récente. In self-driving cars, detecting pedestrians, other vehicles, and obstacles quickly and accurately is crucial for safety. Let’s dive into the highlights! 🌟 Summary This 見るんだ： Ultralytics ｜工業用パッケージデータセットを使用したカスタムデータでのYOLOv9トレーニング YOLOv9の紹介. 59 Release! We’re thrilled to unveil v8. " Find the version you want to revert to, click on the "" menu next to it, and select "Revert to Version. settings_version '0. ultralytics. Apr 1, 2025 · Ultralytics YOLOv5u is an advanced version of YOLOv5, integrating the anchor-free, objectness-free split head that enhances the accuracy-speed tradeoff for real-time object detection tasks. We are in the works to provide a direct, tight integration between YOLOv8 and Ultralytics HUB, which will automatically allow users to visualize their model metrics and losses, preview predictions, and compare against other models, public or private. Ultralytics 、YOLOYOLO、SAM、RT-DETRモデルとともに、YOLOv3からYOLO11包括的なYOLO （You Only Look Once）バージョンをサポートしています。 各バージョンは、検出、セグメンテーション、分類など様々なタスクに最適化されている。 Watch: Ultralytics YOLOv8 모델 개요 YOLOv8 주요 기능. 0. 55, packed with new features, key bug fixes, and enhanced documentation. Follow their code on GitHub. To get started with HUB, simply create an account on the Ultralytics HUB platform, and you can begin training and managing your models through an intuitive Ultralytics HUB es una plataforma de IA intuitiva para crear, entrenar y desplegar modelos de aprendizaje automático con una interfaz sin código y compatibilidad con marcos de aprendizaje profundo. Whether you’re training advanced models, deploying with GPUs, or leveraging integrations, this release brings something for everyone! 🌟 Summary The v8. Ultralytics HUB’s Growth in 2023. 61 Release! Hello Ultralytics Community! We are thrilled to announce the release of Ultralytics v8. 🌟 Summary The v8. Unlike the traditional YOLOv5, YOLOv5u adopts an anchor-free detection mechanism, making it more flexible and adaptive in diverse scenarios. They will also need to be selected based on the device resources available, however the default arguments should work for most Ampere (or newer) NVIDIA discrete GPUs. com; Community: https://community. This version introduces the Medical Pills Detection Dataset, improved developer tools, and refined workflows that raise the bar for your AI projects. 79! This update brings significant improvements in documentation workflows, a refined deployment process, and enhanced compatibility for inference tasks. 4. Install. 85 Release Announcement Summary We are excited to announce the release of Ultralytics YOLO v8. Simpler. 0)[computer software] Oct 10, 2024 · Ultralytics YOLO11 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 performance and flexibility. Sep 1, 2024 · 🌟 Ultralytics YOLO v8. 51! 🎉 This update brings significant improvements to training workflows, new features like a built-in security alarm system, and expanded support for platform exports, all while paving the way for a smooth transition to YOLO11. Jul 13, 2023 · :warning: The `yolov8` package is a placeholder, not the official Ultralytics version. And now, YOLO11 is designed to support any YOLO architecture, not just v8. 0 and childenvironment depends on ultralytics (^8. Users interested in using YOLOv7 need to follow the installation and usage instructions provided in the YOLOv7 GitHub repository. 8 environment with PyTorch>=1. YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite. cuda command in Python Checks if a new version of the ultralytics package is available on PyPI. py，该怎么把源码中的ultralytics安装到环境中。效果等同于python setup. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLO 🚀 and Vision AI ⭐ Using YOLO11 through the Ultralytics package. 87! This version brings significant improvements in queue management, model export workflows, and compatibility with the latest PyTorch, alongside enhancements for hyperparameter tuning processes. Amin Mar 3, 2024 · Join the vibrant Ultralytics Discord 🎧 community for real-time conversations and collaborations. Apr 1, 2025 · Framework Support: Providing a comprehensive framework within Ultralytics YOLOv8 to facilitate these assessments and ensure consistent and reliable results. 51 release focuses on Jan 22, 2025 · 对于那些可能不提供 `__version__` 属性的老版库来说，还可以尝试使用 `pkg_resources` 来读取元数据中的版本字段： ```python from pkg_resources import get_distribution print(get_distribution('ultralytics'). For users preferring a no-code approach, Ultralytics HUB provides an easy way to train and deploy YOLO11 models with just a few clicks. Jun 1, 2023 · Pip install the ultralytics package including all One way to check if there is an issue with your installation is to run the torch. For other state-of-the-art models, you can explore and train using Ultralytics tools like Ultralytics HUB. arXiv preprint arXiv:2207. 15. Smarter. Ultralytics YOLO11 Visão geral. 最適なリアルタイムの物体検出を追求する中で、YOLOv9は、ディープニューラルネットワークに特有の情報損失の課題を克服する革新的なアプローチで際立っています。 Installieren Sie Ultralytics. 4' str: Ultralytics 설정 버전( Ultralytics pip 버전과 구분) datasets_dir '/path/to/datasets' str: 데이터 세트가 저장된 디렉터리: weights_dir '/path/to/weights' str: 모델 가중치가 저장되는 디렉토리: runs_dir '/path/to/runs' str: 실험 실행이 저장되는 디렉터리: uuid 'a1b2c3d4' str Apr 1, 2025 · Watch: Ultralytics YOLOv8 Model Overview Key Features of YOLOv8. Ideal para empresas, académicos, usuarios de tecnología y entusiastas de la IA. YOLOv8 、リアルタイムの物体検出、セグメンテーション、分類のためのUltralytics からの最新の進歩をご覧ください。AIの革命をご覧ください。 Adrian demonstrated that once an Ultralytics YOLO model is trained, users can export it using a few simple command-line flags. 59, the latest version of Ultralytics YOLO. Explore les modèlesYOLO d'Ultralytics - une architecture d'IA de pointe conçue pour une modélisation d'IA de vision très précise. 4 Release! 🌟 Summary We’re excited to announce the release of Ultralytics v8. com OpenVINO Compatibility: Updated OpenVINO version requirements to avoid macOS-specific issues and reverted CI runners to macOS 14 for stability. fovjj rtdm dhegh wegl xxury myfhomxl levbnlr hwvsuew jiq tizpr hlmaxbw sni sepi twqbe mhnun
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