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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.

0.61ms
Inference Time
0-39MB
Memory Usage
107NPU
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

Supported Form Factors

  • Phone
  • Tablet
  • IoT

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 Devices

  • Google Pixel 3
  • Google Pixel 3a
  • Google Pixel 3a XL
  • Google Pixel 4
  • Google Pixel 4a
  • Google Pixel 5a 5G
  • QCS8550 (Proxy)
  • Samsung Galaxy S21
  • Samsung Galaxy S21 Ultra
  • Samsung Galaxy S21+
  • Samsung Galaxy S22 5G
  • Samsung Galaxy S22 Ultra 5G
  • Samsung Galaxy S22+ 5G
  • Samsung Galaxy S23
  • Samsung Galaxy S23 Ultra
  • Samsung Galaxy S23+
  • Samsung Galaxy S24
  • Samsung Galaxy S24 Ultra
  • Samsung Galaxy S24+
  • Samsung Galaxy Tab S8
  • Xiaomi 12
  • Xiaomi 12 Pro

Supported Chipsets

  • Qualcomm® QCS8550
  • Snapdragon® 8 Gen 1 Mobile
  • Snapdragon® 8 Gen 2 Mobile
  • Snapdragon® 8 Gen 3 Mobile
  • Snapdragon® 888 Mobile
  • Snapdragon® X Elite