Datasets:

guillherms
/

human-activity-pose_v4

annotations_creators:
  - human-annotated
language:
  - en
license: cc-by-4.0
pretty_name: Human Activity Pose Dataset (Split Version)
task_categories:
  - keypoint-detection
  - image-classification
task_ids:
  - pose-estimation
  - multi-class-classification
size_categories:
  - 1K<n<10K

🧍 Human Activity Pose Dataset (Split Version)

This dataset contains human pose landmarks extracted with MediaPipe Pose, annotated with activity labels and textual descriptions in English.

Dataset structure

train/ — 80% of samples for training
validation/ — 20% of samples for validation

Each record includes:

33 pose keypoints (fields: x, y, z, visibility)
label: activity name (e.g., reading, dancing, office_work)
description: a short textual description of the action context

Recommended usage

from datasets import load_dataset
dataset = load_dataset("guillherms/human-activity-pose_v4")
train = dataset["train"]
val = dataset["validation"]

Example labels

label	description
reading	A person reading or reviewing a document attentively.
waving	A person waving their hand as a greeting or farewell gesture.
office_work	People working in an office, using laptops, papers, or mobile devices.

Source

Created by Guilherme Santos using MediaPipe and OpenCV.

Notes

The YAML front-matter at the top of this file is used by Hugging Face Cards to populate the repo card. It must start on the first line (---) with no preceding blank lines or spaces.
License: CC-BY-4.0