quanteda provides R tools for textual data, including corpora, tokens, and document-feature matrices.
Openpose
OpenPose detects body, face, hand, and foot keypoints for multiple people in real time.

About Openpose
OpenPose detects body, foot, hand and facial keypoints for multiple people from images, video, webcam and camera sources. It covers 135 keypoints in total, with 2D multi-person detection and single-person 3D triangulation, and can save images and structured keypoint files.
It offers a command-line demo and C++ and Python APIs with support for custom inputs and outputs. Hand and face estimation runtime depends on the number of detected people, and 3D detection is limited to a single person.
Key features
- Detects 15, 18 or 25 body and foot keypoints for multiple people
- Estimates 2x21 hand keypoints and 70 face keypoints
- Performs 3D triangulation from multiple single views
- Accepts image, video, webcam, IP camera and Flir/Point Grey input
- Saves keypoints as JSON, XML or YML and images as PNG, JPG, AVI
- Provides command-line demo plus C++ and Python APIs for custom use
- Body and foot detection runtime is invariant to number of detected people
- Supports CUDA, OpenCL and CPU-only hardware versions
- Includes calibration toolbox for distortion and camera parameters
- Hand and face estimation runtime depends on number of detected people
- 3D keypoint detection is limited to single-person use
- Use without installing or writing code is described only for Windows portable version
Openpose at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Linux, macOS, Windows
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Openpose FAQ
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