MediaPipe-Pose-Estimation
Detect and track human body poses in real-time images and video streams.
The MediaPipe Pose Landmark Detector is a machine learning pipeline that predicts bounding boxes and pose skeletons of poses in an image.
Technical Details
Input resolution:256x256
Number of parameters (MediaPipePoseDetector):815K
Model size (MediaPipePoseDetector):3.14 MB
Number of parameters (MediaPipePoseLandmarkDetector):3.37M
Model size (MediaPipePoseLandmarkDetector):12.9 MB
Applicable Scenarios
- Accessibility
- Augmented Reality
- ARVR
Licenses
Source Model:APACHE-2.0
Deployable Model:AI Model Hub License
Tags
- real-timeA “real-time” model can typically achieve 5-60 predictions per second. This translates to latency ranging up to 200 ms per prediction.
Supported Compute Chipsets
- Snapdragon® X Elite