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---
license: other
license_name: aplux-model-farm-license
license_link: https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf
pipeline_tag: keypoint-detection
tags:
- AIoT
- QNN
---
## MediaPipe-Hand: Gesture Recognition
MediaPipe Hands is a real-time hand tracking and gesture recognition framework developed by Google, based on deep learning. This model can detect and track hands using a single RGB camera, identifying 21 key points of the hand and fingers. MediaPipe Hands employs a lightweight convolutional neural network, allowing it to achieve high-precision gesture recognition and hand tracking with low latency. The algorithm first uses a palm detector to locate the hand, followed by refining the position of key hand points. Its efficiency makes MediaPipe Hands widely used in applications such as virtual reality, gesture control, and augmented reality, providing robust support for real-time interaction systems.
### Source model
- Input shape: [1x3x256x256], [1x3x256x256]
- Number of parameters:1.76M, 2.01M
- Model size:7.11MB, 8.09MB
- Output shape: [1x2944x18, 1x2944x1], [1,1,1x21x3]
Source model repository: [MediaPipe-Hand](https://github.com/zmurez/MediaPipePyTorch/)
## Performance Reference
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## Inference & Model Conversion
Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models)
## License
- Source Model: [APACHE-2.0](https://github.com/zmurez/MediaPipePyTorch/blob/master/LICENSE)
- Deployable Model: [APLUX-MODEL-FARM-LICENSE](https://aiot.aidlux.com/api/v1/files/license/model_farm_license_en.pdf) |