MediaPipe-Hand-Gesture-Recognition
Real‑time hand gesture recognition optimized for mobile and edge.
The MediaPipe Gesture Recognizer is a real‑time machine learning pipeline that detects hands, predicts 21 hand landmarks, determines handedness (left/right), and classifies gestures from a predefined set
Not supported
This model is currently not supported on any Automotive chipset.
To see performance metrics for this model on other chipsets, click the button below.
View for other chipsetsTechnical Details
Input resolution:256x256
Number of parameters (palm_detector):1.76M
Model size (palm_detector) (w8a8):2.05 MB
Number of parameters (hand_landmark_detector):2.72M
Model size (hand_landmark_detector) (w8a8):3.12 MB
Number of parameters (canned_gesture_classifier):143K
Model size (canned_gesture_classifier) (w8a8):180 KB
Model size (palm_detector) (float):6.75 MB
Model size (hand_landmark_detector) (float):10.4 MB
Model size (canned_gesture_classifier) (float):577 KB
Applicable Scenarios
- Gesture Control
- Virtual Reality
- Gaming
License
Model:APACHE-2.0
Tags
- real-time
Supported Automotive Devices
- SA7255P ADP
- SA8255P ADP
- SA8295P ADP
- SA8650P ADP
- SA8775P ADP
Supported Automotive Chipsets
- Qualcomm® SA7255P
- Qualcomm® SA8295P
- Qualcomm® SA8775P
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