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Title: GitHub - DeepLabCut/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans ยท GitHub

Open Graph Title: GitHub - DeepLabCut/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

X Title: GitHub - DeepLabCut/DeepLabCut: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans - DeepLabCut/DeepLabCut

Open Graph Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans - DeepLabCut/DeepLabCut

X Description: Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans - DeepLabCut/DeepLabCut

Opengraph URL: https://github.com/DeepLabCut/DeepLabCut

X: @github

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๐Ÿ“šDocumentationhttps://deeplabcut.github.io/DeepLabCut/README.html
๐Ÿ› ๏ธ Installationhttps://deeplabcut.github.io/DeepLabCut/docs/installation.html
๐ŸŒŽ Home Pagehttps://www.deeplabcut.org
๐Ÿฟ๐Ÿด๐Ÿ๐Ÿ˜๐Ÿ† Model Zoohttp://www.mackenziemathislab.org/deeplabcut/
๐Ÿšจ Newshttps://deeplabcut.github.io/DeepLabCut/README.html#news-and-in-the-news
๐Ÿชฒ Reporting Issueshttps://github.com/DeepLabCut/DeepLabCut/issues
๐Ÿซถ Getting Assistancehttps://deeplabcut.github.io/DeepLabCut/README.html#be-part-of-the-dlc-community
โˆž DeepLabCut Online Coursehttps://github.com/DeepLabCut/DeepLabCut-Workshop-Materials/blob/master/DLCcourse.md
๐Ÿ“ Publicationshttps://deeplabcut.github.io/DeepLabCut/README.html#references
๐Ÿ‘ฉ๐Ÿพโ€๐Ÿ’ป๐Ÿ‘จโ€๐Ÿ’ป DeepLabCut AI Residencyhttps://www.deeplabcutairesidency.org/
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https://pepy.tech/project/deeplabcut
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https://www.gnu.org/licenses/lgpl-3.0
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https://github.com/DeepLabCut/DeepLabCut/tree/master#welcome-
Read a short development and application summary belowhttps://github.com/DeepLabCut/DeepLabCut#why-use-deeplabcut
Installationhttps://deeplabcut.github.io/DeepLabCut/docs/installation.html
https://github.com/DeepLabCut/DeepLabCut/tree/master#installation
https://github.com/DeepLabCut/DeepLabCut/tree/master#quick-start
Install PyTorchhttps://pytorch.org/get-started/locally/
installation instructionshttps://deeplabcut.github.io/DeepLabCut/docs/installation.html
https://github.com/DeepLabCut/DeepLabCut/tree/master#documentation-the-deeplabcut-process
Nature Protocols paperhttps://doi.org/10.1038/s41596-019-0176-0
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Code demohttps://github.com/DeepLabCut/DeepLabCut/blob/main/examples/README.md
https://github.com/DeepLabCut/DeepLabCut/tree/master#code-demo
https://colab.research.google.com/github/DeepLabCut/DeepLabCut/blob/master/examples/COLAB/COLAB_DEMO_mouse_openfield.ipynb
more demos herehttps://github.com/DeepLabCut/DeepLabCut/blob/main/examples/README.md
https://github.com/DeepLabCut/DeepLabCut/tree/master#why-use-deeplabcut
https://github.com/DeepLabCut/DeepLabCut/tree/master#performance-
https://github.com/DeepLabCut/DeepLabCut/tree/master#pretrained-models
SuperAnimal-Quadruped datasethttps://doi.org/10.5281/zenodo.10619172
SuperAnimal-TopViewMouse datasethttps://doi.org/10.5281/zenodo.13757509
Ye et al. 2024https://www.nature.com/articles/s41467-024-48792-2
this Guidehttps://deeplabcut.github.io/DeepLabCut/docs/pytorch/architectures.html
link provides the model weightshttps://huggingface.co/mwmathis/DeepLabCutModelZoo-SuperAnimal-Quadruped
https://github.com/DeepLabCut/DeepLabCut/tree/master#the-history
https://github.com/DeepLabCut/DeepLabCut/tree/master#development-and-applications
trail trackinghttps://vnmurthylab.org/
reaching in micehttp://www.mousemotorlab.org/
Mathis et al.https://www.nature.com/articles/s41593-018-0209-y
ratshttp://www.mousemotorlab.org/deeplabcut
mouse whiskershttp://www.mousemotorlab.org/deeplabcut
race horseshttp://www.mousemotorlab.org/deeplabcut
Pretraining boosts out-of-domain robustness for pose estimationhttps://arxiv.org/abs/1909.11229
Lauer et al 2022https://www.nature.com/articles/s41592-022-01443-0
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Mathis et al. 2018https://www.nature.com/articles/s41593-018-0209-y
Mathis/Warrenhttps://www.biorxiv.org/content/early/2018/10/30/457242
Mathis/Warrenhttps://www.biorxiv.org/content/early/2018/10/30/457242
Nath* and Mathis* et al. 2019https://doi.org/10.1038/s41596-019-0176-0
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Alexander Mathishttps://github.com/AlexEMG
Mackenzie Mathishttps://github.com/MMathisLab
Tanmay Nathhttps://github.com/meet10may
Jessy Lauerhttps://github.com/jeylau
Niels Poulsenhttps://github.com/n-poulsen
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herehttps://www.biorxiv.org/content/10.1101/476531v1
DeepLabCuthttps://www.nature.com/articles/s41593-018-0209-y
https://github.com/DeepLabCut/DeepLabCut/releases/tag/1.11https://github.com/DeepLabCut/DeepLabCut/releases/tag/1.11
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herehttps://deeplabcut.github.io/DeepLabCut/docs/ModelZoo.html
new 2.2+ releaseshttps://github.com/DeepLabCut/DeepLabCut/releases
paper, Lauer et al 2022https://www.nature.com/articles/s41592-022-01443-0
new docshttps://deeplabcut.github.io/DeepLabCut
Lauer et al 2022https://www.nature.com/articles/s41592-022-01443-0
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DLC-live-GUIhttps://github.com/DeepLabCut/DeepLabCut-live-GUI
https://github.com/DeepLabCut/DeepLabCut/tree/master#in-the-news
'Using DeepLabCut for 3D markerless pose estimation across species and behaviors'https://www.nature.com/articles/s41596-019-0176-0
'DeepLabCut: the motion-tracking tool that went viral'https://www.nature.com/articles/d41586-024-01474-x
'DeepLabCut: markerless pose estimation of user-defined body parts with deep learning'https://www.nature.com/articles/s41593-018-0209-y
https://forum.image.sc/tag/deeplabcut
SuperAnimal pretrained pose estimation models for behavioral analysis by Ye et al.https://arxiv.org/abs/2203.07436
https://deeplabcut.github.io/DeepLabCuthttps://deeplabcut.github.io/DeepLabCut
Pretraining boosts out-of-domain robustness for pose estimationhttps://openaccess.thecvf.com/content/WACV2021/html/Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper.html
DLClive.deeplabcut.orghttp://DLClive.deeplabcut.org
docshttps://github.com/DeepLabCut/DeepLabCut/blob/main/docs/UseOverviewGuide.md
review on animal pose estimation is published!https://www.sciencedirect.com/science/article/pii/S0959438819301151
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Behavior tracking cuts deephttps://www.nature.com/articles/s41684-018-0164-y
Behavioral Tracking Gets Realhttps://www.nature.com/articles/s41593-018-0215-0
preprinthttps://arxiv.org/abs/1804.03142
Nature Neurosciencehttps://www.nature.com/articles/s41593-018-0209-y
AI Enables Markerless Animal Trackinghttps://news.developer.nvidia.com/ai-enables-markerless-animal-tracking/
Atlantichttps://www.theatlantic.com/science/archive/2018/07/deeplabcut-tracking-animal-movements/564338
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DeepLabCut - 3.0 Latest May 22, 2026 https://github.com/DeepLabCut/DeepLabCut/releases/tag/v3.0.0
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Please reload this pagehttps://github.com/DeepLabCut/DeepLabCut/tree/master
Learn more about GitHub Sponsorshttps://github.com/sponsors
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