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46 lines
2.3 KiB
46 lines
2.3 KiB
2 years ago
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# Ultralytics YOLOv8 Tasks
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YOLOv8 is an AI framework that supports multiple computer vision **tasks**. The framework can be used to
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perform [detection](detect.md), [segmentation](segment.md), [classification](classify.md),
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and [keypoints](keypoints.md) detection. Each of these tasks has a different objective and use case.
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<img width="1024" src="https://user-images.githubusercontent.com/26833433/212094133-6bb8c21c-3d47-41df-a512-81c5931054ae.png">
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## [Detection](detect.md)
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Detection is the primary task supported by YOLOv8. It involves detecting objects in an image or video frame and drawing
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bounding boxes around them. The detected objects are classified into different categories based on their features.
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YOLOv8 can detect multiple objects in a single image or video frame with high accuracy and speed.
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[Detection Examples](detect.md){ .md-button .md-button--primary}
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## [Segmentation](segment.md)
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Segmentation is a task that involves segmenting an image into different regions based on the content of the image. Each
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region is assigned a label based on its content. This task is useful in applications such as image segmentation and
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medical imaging. YOLOv8 uses a variant of the U-Net architecture to perform segmentation.
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[Segmentation Examples](segment.md){ .md-button .md-button--primary}
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## [Classification](classify.md)
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Classification is a task that involves classifying an image into different categories. YOLOv8 can be used to classify
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images based on their content. It uses a variant of the EfficientNet architecture to perform classification.
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[Classification Examples](classify.md){ .md-button .md-button--primary}
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<!--
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## [Keypoints](keypoints.md)
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Keypoints detection is a task that involves detecting specific points in an image or video frame. These points are
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referred to as keypoints and are used to track movement or pose estimation. YOLOv8 can detect keypoints in an image or
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video frame with high accuracy and speed.
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[Keypoints Examples](keypoints.md){ .md-button .md-button--primary}
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-->
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## Conclusion
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YOLOv8 supports multiple tasks, including detection, segmentation, classification, and keypoints detection. Each of
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these tasks has different objectives and use cases. By understanding the differences between these tasks, you can choose
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the appropriate task for your computer vision application.
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