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Glenn Jocher
2023-07-17 12:40:04 +02:00
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docs/tasks/classify.md
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---
comments: true
description: Check YOLO class label with only one class for the whole image, using image classification. Get strategies for training and validation models.
keywords: YOLOv8n-cls, image classification, pretrained models
description: Learn about YOLOv8 Classify models for image classification. Get detailed information on List of Pretrained Models & how to Train, Validate, Predict & Export models.
keywords: Ultralytics, YOLOv8, Image Classification, Pretrained Models, YOLOv8n-cls, Training, Validation, Prediction, Model Export
---
Image classification is the simplest of the three tasks and involves classifying an entire image into one of a set of
@ -178,4 +178,4 @@ i.e. `yolo predict model=yolov8n-cls.onnx`. Usage examples are shown for your mo
| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-cls_paddle_model/` | ✅ | `imgsz` |
| [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-cls_ncnn_model/` | ✅ | `imgsz`, `half` |
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.

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docs/tasks/detect.md
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---
comments: true
description: Learn how to use YOLOv8, an object detection model pre-trained with COCO and about the different YOLOv8 models and how to train and export them.
keywords: object detection, YOLOv8 Detect models, COCO dataset, models, train, predict, export
description: Official documentation for YOLOv8 by Ultralytics. Learn how to train, validate, predict and export models in various formats. Including detailed performance stats.
keywords: YOLOv8, Ultralytics, object detection, pretrained models, training, validation, prediction, export models, COCO, ImageNet, PyTorch, ONNX, CoreML
---
Object detection is a task that involves identifying the location and class of objects in an image or video stream.
@ -169,4 +169,4 @@ Available YOLOv8 export formats are in the table below. You can predict or valid
| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n_paddle_model/` | ✅ | `imgsz` |
| [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n_ncnn_model/` | ✅ | `imgsz`, `half` |
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.

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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.
keywords: YOLOv8, computer vision, detection, segmentation, classification, pose, keypoint detection, image segmentation, medical imaging
description: Learn about the cornerstone computer vision tasks YOLOv8 can perform including detection, segmentation, classification, and pose estimation. Understand their uses in your AI projects.
keywords: Ultralytics, YOLOv8, Detection, Segmentation, Classification, Pose Estimation, AI Framework, Computer Vision Tasks
---
# Ultralytics YOLOv8 Tasks

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docs/tasks/pose.md
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---
comments: true
description: Learn how to use YOLOv8 pose estimation models to identify the position of keypoints on objects in an image, and how to train, validate, predict, and export these models for use with various formats such as ONNX or CoreML.
keywords: YOLOv8, Pose Models, Keypoint Detection, COCO dataset, COCO val2017, Amazon EC2 P4d, PyTorch
description: Learn how to use Ultralytics YOLOv8 for pose estimation tasks. Find pretrained models, learn how to train, validate, predict, and export your own.
keywords: Ultralytics, YOLO, YOLOv8, pose estimation, keypoints detection, object detection, pre-trained models, machine learning, artificial intelligence
---
Pose estimation is a task that involves identifying the location of specific points in an image, usually referred
@ -183,4 +183,4 @@ i.e. `yolo predict model=yolov8n-pose.onnx`. Usage examples are shown for your m
| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-pose_paddle_model/` | ✅ | `imgsz` |
| [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-pose_ncnn_model/` | ✅ | `imgsz`, `half` |
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.

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docs/tasks/segment.md
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---
comments: true
description: Learn what Instance segmentation is. Get pretrained YOLOv8 segment models, and how to train and export them to segments masks. Check the preformance metrics!
keywords: instance segmentation, YOLOv8, Ultralytics, pretrained models, train, predict, export, datasets
description: Learn how to use instance segmentation models with Ultralytics YOLO. Instructions on training, validation, image prediction, and model export.
keywords: yolov8, instance segmentation, Ultralytics, COCO dataset, image segmentation, object detection, model training, model validation, image prediction, model export
---
Instance segmentation goes a step further than object detection and involves identifying individual objects in an image
@ -183,4 +183,4 @@ i.e. `yolo predict model=yolov8n-seg.onnx`. Usage examples are shown for your mo
| [PaddlePaddle](https://github.com/PaddlePaddle) | `paddle` | `yolov8n-seg_paddle_model/` | ✅ | `imgsz` |
| [ncnn](https://github.com/Tencent/ncnn) | `ncnn` | `yolov8n-seg_ncnn_model/` | ✅ | `imgsz`, `half` |
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.
See full `export` details in the [Export](https://docs.ultralytics.com/modes/export/) page.