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  tags:
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  - computer_vision
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  - pose_estimation
 
 
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  ---
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  # MODEL CARD:
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  trained to predict mouse topline 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 DLCRNet and/or HRNet-w32 trained on our TopViewMouse-5K 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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  # Creates a folder and downloads the model to it
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  model_dir = Path("./superanimal_topviewmouse_model")
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  model_dir.mkdir()
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- download_huggingface_model("superanimal_topviewmouse", model_dir)
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  ```
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  ## Intended Use
 
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  tags:
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  - computer_vision
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  - pose_estimation
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+ - animal_pose_estimation
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+ - deeplabcut
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  ---
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  # MODEL CARD:
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  trained to predict mouse topline 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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+ - `pose_model.pth` is an HRNet-w32 compatable for DLC3.0+ Pytorch code, trained on our TopViewMouse-5K dataset.
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+ - `detector.pt` is a Faster R-CNN that can be used as a detector for top-down detection.
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+ - `DLC_ma_supertopview5k_resnet_50_iteration-0_shuffle-1.tar.gz` is a DLCRNet trained on our TopViewMouse-5K dataset.
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+
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+ • 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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  # Creates a folder and downloads the model to it
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  model_dir = Path("./superanimal_topviewmouse_model")
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  model_dir.mkdir()
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+ download_huggingface_model("superanimal_topviewmouse_model", model_dir)
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  ```
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  ## Intended Use