MediaPipe-Hand-Detection
Real-time hand detection optimized for mobile and edge.
The MediaPipe Hand Landmark Detector is a machine learning pipeline that predicts bounding boxes and pose skeletons of hands in an image.
Technical Details
Input resolution:256x256
Number of parameters (MediaPipeHandDetector):1.76M
Model size (MediaPipeHandDetector):6.76 MB
Number of parameters (MediaPipeHandLandmarkDetector):2.01M
Model size (MediaPipeHandLandmarkDetector):7.71 MB
Applicable Scenarios
- Gesture Control
- Virtual Reality
- Gaming
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)
- SA8255 (Proxy)
- SA8650 (Proxy)
- SA8775 (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
- Qualcomm® SA8255P
- Qualcomm® SA8650P
- Qualcomm® SA8775P
- Snapdragon® 8 Gen 1 Mobile
- Snapdragon® 8 Gen 2 Mobile
- Snapdragon® 8 Gen 3 Mobile
- Snapdragon® 888 Mobile
- Snapdragon® X Elite