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docs/en/datasets/pose/tiger-pose.md
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@ -8,11 +8,11 @@ keywords: Ultralytics, Tiger-Pose, dataset, pose estimation, YOLOv8, training da
## Introduction
[Ultralytics](https://ultralytics.com) introduces the Tiger-Pose dataset, a versatile collection designed for pose estimation tasks. This dataset comprises 263 images sourced from a [YouTube Video](https://www.youtube.com/watch?v=MIBAT6BGE6U&pp=ygUbVGlnZXIgd2Fsa2luZyByZWZlcmVuY2UubXA0), with 210 images allocated for training and 53 for validation. It serves as an excellent resource for testing and troubleshooting pose estimation algorithm.
[Ultralytics](https://www.ultralytics.com/) introduces the Tiger-Pose dataset, a versatile collection designed for pose estimation tasks. This dataset comprises 263 images sourced from a [YouTube Video](https://www.youtube.com/watch?v=MIBAT6BGE6U&pp=ygUbVGlnZXIgd2Fsa2luZyByZWZlcmVuY2UubXA0), with 210 images allocated for training and 53 for validation. It serves as an excellent resource for testing and troubleshooting pose estimation algorithm.
Despite its manageable size of 210 images, tiger-pose dataset offers diversity, making it suitable for assessing training pipelines, identifying potential errors, and serving as a valuable preliminary step before working with larger datasets for pose estimation.
This dataset is intended for use with [Ultralytics HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics).
This dataset is intended for use with [Ultralytics HUB](https://hub.ultralytics.com/) and [YOLOv8](https://github.com/ultralytics/ultralytics).
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@ -101,7 +101,7 @@ The dataset has been released available under the [AGPL-3.0 License](https://git
### What is the Ultralytics Tiger-Pose dataset used for?
The Ultralytics Tiger-Pose dataset is designed for pose estimation tasks, consisting of 263 images sourced from a [YouTube video](https://www.youtube.com/watch?v=MIBAT6BGE6U&pp=ygUbVGlnZXIgd2Fsa2luZyByZWZlcmVuY2UubXA0). The dataset is divided into 210 training images and 53 validation images. It is particularly useful for testing, training, and refining pose estimation algorithms using [Ultralytics HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics).
The Ultralytics Tiger-Pose dataset is designed for pose estimation tasks, consisting of 263 images sourced from a [YouTube video](https://www.youtube.com/watch?v=MIBAT6BGE6U&pp=ygUbVGlnZXIgd2Fsa2luZyByZWZlcmVuY2UubXA0). The dataset is divided into 210 training images and 53 validation images. It is particularly useful for testing, training, and refining pose estimation algorithms using [Ultralytics HUB](https://hub.ultralytics.com/) and [YOLOv8](https://github.com/ultralytics/ultralytics).
### How do I train a YOLOv8 model on the Tiger-Pose dataset?
@ -161,4 +161,4 @@ To perform inference using a YOLOv8 model trained on the Tiger-Pose dataset, you
### What are the benefits of using the Tiger-Pose dataset for pose estimation?
The Tiger-Pose dataset, despite its manageable size of 210 images for training, provides a diverse collection of images that are ideal for testing pose estimation pipelines. The dataset helps identify potential errors and acts as a preliminary step before working with larger datasets. Additionally, the dataset supports the training and refinement of pose estimation algorithms using advanced tools like [Ultralytics HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics), enhancing model performance and accuracy.
The Tiger-Pose dataset, despite its manageable size of 210 images for training, provides a diverse collection of images that are ideal for testing pose estimation pipelines. The dataset helps identify potential errors and acts as a preliminary step before working with larger datasets. Additionally, the dataset supports the training and refinement of pose estimation algorithms using advanced tools like [Ultralytics HUB](https://hub.ultralytics.com/) and [YOLOv8](https://github.com/ultralytics/ultralytics), enhancing model performance and accuracy.