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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.

Snapdragon® X Elite
1.04ms
Inference Time
3MB
Memory Usage
139NPU
Layers

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-time
    A “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