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
Technical Details
Input resolution:256x256
Number of parameters (PalmDetector):1.76M
Model size (PalmDetector) (w8a8):2.05 MB
Number of parameters (HandLandmarkDetector):2.72M
Model size (HandLandmarkDetector) (w8a8):3.12 MB
Number of parameters (CannedGestureClassifier):143K
Model size (CannedGestureClassifier) (w8a8):180 KB
Model size (PalmDetector) (float):6.75 MB
Model size (HandLandmarkDetector) (float):10.4 MB
Model size (CannedGestureClassifier) (float):577 KB
Applicable Scenarios
- Gesture Control
- Virtual Reality
- Gaming
License
Model:APACHE-2.0
Tags
- real-time
Supported IoT Devices
- Dragonwing IQ-9075 EVK
- Dragonwing Q-6690 MTP
- Dragonwing RB3 Gen 2 Vision Kit
- QCS8275 (Proxy)
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCM6690
- Qualcomm® QCS6490
- Qualcomm® QCS8275 (Proxy)
- Qualcomm® QCS8550 (Proxy)
- Qualcomm® QCS9075
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