YOLO26 is a model available on Hugging Face that supports a range of computer vision tasks, including object detection, instance segmentation, image classification, pose estimation, oriented bounding box (obb) detection, tracking, and semantic segmentation. The model is associated with the Ultralytics implementation and can be used with the ultralytics library in Python. Instructions are provided for running inference with the model using ultralytics, and example code is given for loading a pretrained version and making predictions on images. YOLO26 is accessible for use in various environments such as Google Colab and Kaggle, and can be integrated into local applications. The model card notes that it is licensed under the AGPL-3.0 license. The Hugging Face page mentions support for multiple languages, although specific details on language support are not provided. YOLO26 is positioned as a tool for users interested in advanced computer vision applications, but the evidence does not specify particular user roles or industries. No information is provided regarding pricing beyond the open-source license, and there are no explicit details about performance metrics or dataset compatibility. The model is part of the broader class of YOLO (You Only Look Once) models used for visual recognition tasks.
YOLO26 is an Other AI product. It focuses on providing an open-source YOLO26 model for object detection and vision applications. YOLO26 is an open-source project aimed at computer vision developers and researchers. The project is open source (AGPL-3.0). It runs on the command line, and it can be self-hosted.
hts-ai builds and maintains YOLO26, and the product first shipped in 2022. The project is developed in the open on GitHub with 59.4k stars and 517 commits in the last 90 days. Among its 5 catalogued features are object detection, instance segmentation, and pose estimation.
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