TrainingDataPro/pose_estimation

---
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
language:
- en
tags:
- code
- finance
dataset_info:
features:
- name: image_id
dtype: uint32
- name: image
dtype: image
- name: mask
dtype: image
- name: shapes
dtype: string
splits:
- name: train
num_bytes: 142645152
num_examples: 29
download_size: 137240523
dataset_size: 142645152
---
# Pose Estimation
The dataset is primarly intended to dentify and predict the positions of major joints of a human body in an image. It consists of people's photographs with body part labeled with keypoints.

# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets/pose-estimation-annotation?utm_source=huggingface&utm_medium=cpc&utm_campaign=pose_estimation)** to buy the dataset


# Data Format

Each image from `PE` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the key points. For each point, the x and y coordinates are provided, and there is a `Presumed_Location` attribute, indicating whether the point is presumed or accurately defined.

# Example of XML file structure
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# Labeled body parts
Each keypoint is ordered and corresponds to the concrete part of the body:

0 **Nose**

1 **Neck**

2 **Right shoulder**

3 **Right elbow**

4 **Right wrist**

5 **Left shoulder**

6 **Left elbow**

7 **Left wrist**

8 **Right hip**

9 **Right knee**

10 **Right foot**

11 **Left hip**

12 **Left knee**

13 **Left foot**

14 **Right eye**

15 **Left eye**

16 **Right ear**

17 **Left ear**

# Keypoint annotation is made in accordance with your requirements.

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/pose-estimation-annotation?utm_source=huggingface&utm_medium=cpc&utm_campaign=pose_estimation)** to discuss your requirements, learn about the price and buy the dataset

## **[TrainingData](https://trainingdata.pro/datasets/pose-estimation-annotation?utm_source=huggingface&utm_medium=cpc&utm_campaign=pose_estimation)** provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**

*keywords: keypoints dataset, people with keypoints, keypoints annotation, keypoint detection dataset, biometric dataset, biometric data dataset, pose recognition database, pose detection dataset, pose estimation dataset, annotated body joints, pose annotations dataset, human images dataset, 2d human movements, hpe dataset*

原始信息汇总

数据集概述

数据集基本信息

• 许可证: cc-by-nc-nd-4.0
• 任务类别: image-classification
• 语言: en
• 标签: code, finance

数据集特征

• image_id: 数据类型为 uint32
• image: 数据类型为 image
• mask: 数据类型为 image
• shapes: 数据类型为 string

数据集分割

• 训练集:
  • 大小: 142645152 字节
  • 示例数量: 29
  • 下载大小: 137240523 字节

数据集描述

• 目的: 主要用于识别和预测图像中人体主要关节的位置。
• 内容: 包含人体照片，身体部位标记有关键点。
• 数据格式: 每个图像伴随一个XML文件，指示关键点的坐标。
• 标记的身体部位: 包括鼻子、脖子、肩膀、肘部、手腕、臀部、膝盖和脚等17个关键点。