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[](https://github.com/sponsors/vladmandic)
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@ -354,18 +355,18 @@ And for even better results, you can run detection in a separate web worker thre
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Default models in Human library are:
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- **Face Detection**: MediaPipe BlazeFace Back variation
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- **Face Mesh**: MediaPipe FaceMesh
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- **Face Iris Analysis**: MediaPipe Iris
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- **Face Description**: HSE FaceRes
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- **Emotion Detection**: Oarriaga Emotion
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- **Body Analysis**: MoveNet Lightning variation
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- **Hand Analysis**: HandTrack & MediaPipe HandLandmarks
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- **Body Segmentation**: Google Selfie
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- **Object Detection**: CenterNet with MobileNet v3
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- **Face Detection**: *MediaPipe BlazeFace Back variation*
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- **Face Mesh**: *MediaPipe FaceMesh*
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- **Face Iris Analysis**: *MediaPipe Iris*
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- **Face Description**: *HSE FaceRes*
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- **Emotion Detection**: *Oarriaga Emotion*
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- **Body Analysis**: *MoveNet Lightning variation*
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- **Hand Analysis**: *HandTrack & MediaPipe HandLandmarks*
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- **Body Segmentation**: *Google Selfie*
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- **Object Detection**: *CenterNet with MobileNet v3*
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Note that alternative models are provided and can be enabled via configuration
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For example, body pose detection by default uses `MoveNet Lightning`, but can be switched to `MultiNet Thunder` for higher precision or `Multinet MultiPose` for multi-person detection or even `PoseNet`, `BlazePose` or `EfficientPose` depending on the use case
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For example, body pose detection by default uses *MoveNet Lightning*, but can be switched to *MultiNet Thunder* for higher precision or *Multinet MultiPose* for multi-person detection or even *PoseNet*, *BlazePose* or *EfficientPose* depending on the use case
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For more info, see [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration) and [**List of Models**](https://github.com/vladmandic/human/wiki/Models)
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@ -388,6 +389,7 @@ and [**API Specification**](https://vladmandic.github.io/human/typedoc/classes/H
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<br>
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[](https://github.com/sponsors/vladmandic)
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Subproject commit 1e147d34e64b3874e07bdf2455ac3344ccf024d0
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Subproject commit cf9ea4929d720dcb4e1b25a6b7c1fb4c5b4d2718
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