Yolo26 enables users to upload images or videos and apply real-time object detection, segmentation, pose estimation, or classification using YOLO26 models. It provides adjustable confidence and IoU thresholds, making it accessible for users to experiment with computer vision tasks without programming. Ideal for ML enthusiasts and researchers.
Yolo26 sits in PulseGate's Computer vision, OCR & document AI category. It focuses on running advanced computer vision tasks like detection, segmentation, and pose estimation on user-supplied images or videos without coding. It is built as a consumer product for machine learning enthusiasts. Yolo26 is free to use. Yolo26 is available on the web, and it can be self-hosted.
It is developed by atalaydenknalbant, and it first shipped in 2024. Among its 8 catalogued features are real-time detection, segmentation, and pose estimation.
Summary written by a language model from the project’s public pages.
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