Generate detailed pose estimates from images
Detect and visualize poses in videos
Detect objects and poses in images
Track chicken poses in real-time
Detect and visualize human poses in images and videos
Create a video using aligned poses from an image and a dance video
Evaluate and improve your yoga pose accuracy
Estimate and visualize 3D body poses from video
Detect human poses in images
Analyze workout posture in real-time
ITS PRETTY
Analyze your powerlifting form with video input
Detect and annotate poses in images and videos
OpenPose is a cutting-edge library for pose estimation developed by the Carnegie Mellon University (CMU) Perceptual Computing Laboratory. It is designed to detect and estimate human body poses from images, videos, and other media. OpenPose supports both 2D and 3D pose estimation and is widely used in fields like computer vision, robotics, and fitness tracking. It is an open-source tool, making it accessible for research and commercial use.
• Multi-person pose estimation: OpenPose can detect poses of multiple people in a single image. • Real-time processing: Enables fast and efficient pose estimation for real-time applications. • Body, face, and hands tracking: Supports estimation of body keypoints, facial landmarks, and hand keypoints. • 3D pose estimation: Offers 3D pose reconstruction for deeper understanding of human movement. • Cross-platform compatibility: Runs on Windows, Linux, and macOS. • Customizable models: Users can train or use pre-trained models for specific use cases.
What input formats does OpenPose support?
OpenPose supports images (JPG, PNG, etc.), videos (MP4, AVI, etc.), and camera inputs. It can also process frames from video streams.
Can OpenPose work with multiple people in the same image?
Yes, OpenPose is designed to detect and estimate poses of multiple people simultaneously in a single image or video frame.
How do I improve the accuracy of pose estimation?
You can improve accuracy by using higher-resolution images, adjusting model parameters, or re-training the model with a dataset specific to your use case.