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
Supported Form Factors
- Phone
- Tablet
- IoT
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 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