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README.md
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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
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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("
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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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• 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
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