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Title:
Pose Estimation Datasets Overview - Ultralytics YOLO Docs
Description:
Learn about Ultralytics YOLO format for pose estimation datasets, supported formats, COCO-Pose, COCO8-Pose, Tiger-Pose, and how to add your own dataset.
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Keywords {🔍}
dataset, ultralytics, format, yolo, pose, keypoints, images, cocopose, object, estimation, coco, file, training, yaml, train, datasets, model, number, class, human, models, usage, coordinates, configuration, classes, names, label, hand, tool, convert, validation, conversion, normalized, width, height, keypoint, pathtoimgs, path, read, dog, detection, labels, text, image, row, information, index, val, test, optional,
Topics {✒️}
top previous package-seg coco8-pose tiger-pose description coco-pose coco8-pose description yolo train data=coco8-pose bounding box segmentation ultralytics coco8-pose supported datasets dog-pose adding 0/coco8-pose coco8-pose large-scale object detection coco-pose description dog pose dataset coco-pose dataset /ultralytics/assets/releases/download/v0 visit coco-pose coco-pose popular coco dataset pose estimation dataset detection approaches tiger pose estimation task estimate dog poses human pose estimation human hand datasets coco dataset coco format pose estimation hand ultralytics yolo format dog poses dog anatomy visibility flag ultralytics yolo defines //docs pose dataset coco train2017 /coco/annotations/ dataset yaml format multiple keypoints specific yolo dataset files dog dataset yaml file yolo11n-pose animal pose yaml file format dataset label format ultralytics yolo
Questions {❓}
- How can I add my own dataset for pose estimation in Ultralytics YOLO?
- How can I convert COCO dataset labels to Ultralytics YOLO format for pose estimation?
- How do I use the COCO-Pose dataset with Ultralytics YOLO?
- What is the Ultralytics YOLO format for pose estimation?
- What is the purpose of the dataset YAML file in Ultralytics YOLO?
Schema {🗺️}
["Article","FAQPage"]:
context:https://schema.org
headline:Pose Estimation Datasets Overview
image:
https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png
datePublished:2023-11-12 02:49:37 +0100
dateModified:2025-06-30 18:36:07 +0800
author:
type:Organization
name:Ultralytics
url:https://ultralytics.com/
abstract:Learn about Ultralytics YOLO format for pose estimation datasets, supported formats, COCO-Pose, COCO8-Pose, Tiger-Pose, and how to add your own dataset.
mainEntity:
type:Question
name:What is the Ultralytics YOLO format for pose estimation?
acceptedAnswer:
type:Answer
text:The Ultralytics YOLO format for pose estimation datasets involves labeling each image with a corresponding text file. Each row of the text file stores information about an object instance: For 2D poses, keypoints include pixel coordinates. For 3D, each keypoint also has a visibility flag. For more details, see Ultralytics YOLO format.
type:Question
name:How do I use the COCO-Pose dataset with Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:To use the COCO-Pose dataset with Ultralytics YOLO:
type:Question
name:How can I add my own dataset for pose estimation in Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:To add your dataset:
type:Question
name:What is the purpose of the dataset YAML file in Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:The dataset YAML file in Ultralytics YOLO defines the dataset and model configuration for training. It specifies paths to training, validation, and test images, keypoint shapes, class names, and other configuration options. This structured format helps streamline dataset management and model training. Here is an example YAML format: Read more about creating YAML configuration files in Dataset YAML format.
type:Question
name:How can I convert COCO dataset labels to Ultralytics YOLO format for pose estimation?
acceptedAnswer:
type:Answer
text:Ultralytics provides a conversion tool to convert COCO dataset labels to the YOLO format, including keypoint information: This tool helps seamlessly integrate COCO datasets into YOLO projects. For details, refer to the Conversion Tool section and the data preprocessing guide.
Organization:
name:Ultralytics
url:https://ultralytics.com/
Question:
name:What is the Ultralytics YOLO format for pose estimation?
acceptedAnswer:
type:Answer
text:The Ultralytics YOLO format for pose estimation datasets involves labeling each image with a corresponding text file. Each row of the text file stores information about an object instance: For 2D poses, keypoints include pixel coordinates. For 3D, each keypoint also has a visibility flag. For more details, see Ultralytics YOLO format.
name:How do I use the COCO-Pose dataset with Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:To use the COCO-Pose dataset with Ultralytics YOLO:
name:How can I add my own dataset for pose estimation in Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:To add your dataset:
name:What is the purpose of the dataset YAML file in Ultralytics YOLO?
acceptedAnswer:
type:Answer
text:The dataset YAML file in Ultralytics YOLO defines the dataset and model configuration for training. It specifies paths to training, validation, and test images, keypoint shapes, class names, and other configuration options. This structured format helps streamline dataset management and model training. Here is an example YAML format: Read more about creating YAML configuration files in Dataset YAML format.
name:How can I convert COCO dataset labels to Ultralytics YOLO format for pose estimation?
acceptedAnswer:
type:Answer
text:Ultralytics provides a conversion tool to convert COCO dataset labels to the YOLO format, including keypoint information: This tool helps seamlessly integrate COCO datasets into YOLO projects. For details, refer to the Conversion Tool section and the data preprocessing guide.
Answer:
text:The Ultralytics YOLO format for pose estimation datasets involves labeling each image with a corresponding text file. Each row of the text file stores information about an object instance: For 2D poses, keypoints include pixel coordinates. For 3D, each keypoint also has a visibility flag. For more details, see Ultralytics YOLO format.
text:To use the COCO-Pose dataset with Ultralytics YOLO:
text:To add your dataset:
text:The dataset YAML file in Ultralytics YOLO defines the dataset and model configuration for training. It specifies paths to training, validation, and test images, keypoint shapes, class names, and other configuration options. This structured format helps streamline dataset management and model training. Here is an example YAML format: Read more about creating YAML configuration files in Dataset YAML format.
text:Ultralytics provides a conversion tool to convert COCO dataset labels to the YOLO format, including keypoint information: This tool helps seamlessly integrate COCO datasets into YOLO projects. For details, refer to the Conversion Tool section and the data preprocessing guide.
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