Ultralytics YOLOv8 is the latest version of the acclaimed real-time object detection and image segmentation model. YOLOv8 is built on cutting-edge advancements in deep learning and computer vision, offering unparalleled performance in terms of speed and accuracy.
The YOLOv8 image classification model is designed to detect 1000 pre-defined classes in images in real-time.
Image classification is the simplest of the three tasks and involves classifying an entire image into one of a set of predefined classes. Different from YOLO's Segment and Object detection models which are trained on COCO datasets, the image classification models is trained on ImageNet dataset.
The YOLOv8 model has demonstrated state-of-the-art performance on ImageNet classification tasks. Y
- Authors: Glenn Jocher and Ayush Chaurasia and Jing Qiu
- Title: Ultralytics YOLOv8
- Version: 8.0.0
- Year: 2023
- URL: https://github.com/ultralytics/ultralytics
- Orcid: 0000-0001-5950-6979, 0000-0002-7603-6750, 0000-0003-3783-7069
- License: AGPL-3.0
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