退购1.1定位算法

docs/tasks/index.md

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