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Title: GitHub - stanlp86/DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals, including humans · GitHub

Open Graph Title: GitHub - stanlp86/DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals, including humans

X Title: GitHub - stanlp86/DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals, including humans

Description: Markerless pose estimation of user-defined features with deep learning for all animals, including humans - stanlp86/DeepLabCut

Open Graph Description: Markerless pose estimation of user-defined features with deep learning for all animals, including humans - stanlp86/DeepLabCut

X Description: Markerless pose estimation of user-defined features with deep learning for all animals, including humans - stanlp86/DeepLabCut

Opengraph URL: https://github.com/stanlp86/DeepLabCut

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dlc.pyhttps://github.com/stanlp86/DeepLabCut/blob/master/dlc.py
dlc.pyhttps://github.com/stanlp86/DeepLabCut/blob/master/dlc.py
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Code of conducthttps://github.com/stanlp86/DeepLabCut
LGPL-3.0 licensehttps://github.com/stanlp86/DeepLabCut
https://badge.fury.io/py/deeplabcut
https://pypistats.org/packages/deeplabcut
http://krihelinator.xyz/repositories/AlexEMG/DeepLabCut
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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
www.deeplabcut.orghttps://www.mousemotorlab.org/deeplabcut/
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DeepLabCuthttps://www.nature.com/articles/s41593-018-0209-y
Nature Protocolshttps://doi.org/10.1038/s41596-019-0176-0
herehttps://www.biorxiv.org/content/10.1101/476531v1
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DeepLabCuthttps://www.nature.com/articles/s41593-018-0209-y
https://github.com/AlexEMG/DeepLabCut/releases/tag/1.11https://github.com/AlexEMG/DeepLabCut/releases/tag/1.11
Installationhttps://github.com/stanlp86/DeepLabCut/blob/master/docs/installation.md
https://github.com/stanlp86/DeepLabCut#installation
install DeeplabCuthttps://github.com/stanlp86/DeepLabCut/blob/master/docs/installation.md
Documentation: The DeepLabCut Processhttps://github.com/stanlp86/DeepLabCut/blob/master/docs/UseOverviewGuide.md
https://github.com/stanlp86/DeepLabCut#documentation-the-deeplabcut-process
Nature Protocols paperhttps://doi.org/10.1038/s41596-019-0176-0
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DEMO the codehttps://github.com/stanlp86/DeepLabCut/blob/master/examples
https://github.com/stanlp86/DeepLabCut#demo-the-code
https://github.com/stanlp86/DeepLabCut#why-use-deeplabcut
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Mathis et al. 2019https://www.nature.com/articles/s41593-018-0209-y
Mathis et al. 2019https://arxiv.org/abs/1909.11229
Mathis/Warrenhttps://www.biorxiv.org/content/early/2018/10/30/457242
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.https://doi.org/10.1038/s41596-019-0176-0
https://github.com/stanlp86/DeepLabCut#code-contributors
Alexander Mathishttps://github.com/AlexEMG
Mackenzie Mathishttps://github.com/MMathisLab
Tanmay Nathhttp://www.mousemotorlab.org/team
DeeperCuthttps://github.com/eldar/pose-tensorflow
contributorshttps://github.com/AlexEMG/DeepLabCut/graphs/contributors
AUTHORShttps://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
https://github.com/stanlp86/DeepLabCut#community-support-developers--help
https://forum.image.sc/tags/deeplabcut
Scientific Community Image Forum: A discussion forum for scientific image softwarehttps://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000340
https://github.com/AlexEMG/DeepLabCut/issueshttps://github.com/AlexEMG/DeepLabCut/issues
https://gitter.im/DeepLabCut/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
testscript.pyhttps://github.com/stanlp86/DeepLabCut/blob/master/examples/testscript.py
herehttps://github.com/stanlp86/DeepLabCut/blob/master/docs/contribute.md
https://github.com/stanlp86/DeepLabCut#references
cite Mathis et al, 2018https://www.nature.com/articles/s41593-018-0209-y
Nath, Mathis et al, 2019https://doi.org/10.1038/s41596-019-0176-0
Mathis et al. 2019https://arxiv.org/abs/1909.11229
https://github.com/stanlp86/DeepLabCut#license
cite us!https://www.nature.com/articles/s41593-018-0209-y
https://github.com/stanlp86/DeepLabCut#news-and-in-the-news
releaseshttps://github.com/AlexEMG/DeepLabCut/releases
ImageNet pretraining contributes to robustnesshttps://arxiv.org/abs/1909.11229
review on animal pose estimationhttps://arxiv.org/abs/1909.13868
releaseshttps://github.com/AlexEMG/DeepLabCut/releases
twitterhttps://twitter.com/deeplabcut
https://twitter.com/DeepLabCut
herehttps://github.com/AlexEMG/DeepLabCut-Workshop-Materials
https://forum.image.sc/tags/deeplabcut
BioRxivhttps://www.biorxiv.org/content/early/2018/11/24/476531
DLCutilshttps://github.com/AlexEMG/DLCutils
BioRxivhttps://www.biorxiv.org/content/early/2018/10/30/457242
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
arXiv.orghttps://arxiv.org/abs/1804.03142
deeplabcut.orghttp://deeplabcut.org
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