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  ## Model Details
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- • SuperAnimal-Quadruped model developed by the [M.W.Mathis Lab](http://www.mackenziemathislab.org/) in 2023, trained to predict quadruped pose from images.
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  Please see [Shaokai Ye et al. 2023](https://arxiv.org/abs/2203.07436) for details.
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- • The model is an HRNet-w32 trained on our Quadruped-80K dataset.
 
 
 
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- It was trained within the DeepLabCut framework. Full training details can be found in Ye et al. 2023.
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- You can use this model simply with our light-weight loading package called [DLCLibrary](https://github.com/DeepLabCut/DLClibrary).
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  Here is an example useage:
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  ```python
 
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  ## Model Details
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+ • SuperAnimal-Quadruped model(s) developed by the [M.W.Mathis Lab](http://www.mackenziemathislab.org/) in 2023, trained to predict quadruped pose from images.
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  Please see [Shaokai Ye et al. 2023](https://arxiv.org/abs/2203.07436) for details.
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+ • The there are three models:
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+ - One is an HRNet-w32 trained within mmpose on our Quadruped-80K dataset.
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+ - pose_model is an HRNet-w32 compatable for DLC3.0+ Pytorch code, trained on our Quadruped-80K dataset.
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+ - Detector is a Faster R-CNN that can be used as a detector for top-down estimation.
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+ • Full training details can be found in Ye et al. 2023.
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+ You can use the pose_model and detector simply with our light-weight loading package called [DLCLibrary](https://github.com/DeepLabCut/DLClibrary).
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  Here is an example useage:
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  ```python