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# [Installation: how to install DeepLabCut](https://deeplabcut.github.io/DeepLabCut/docs/installation.html)
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Very quick start: `pip install "deeplabcut[gui,tf]"` that includes all functions plus GUIs, or `pip install deeplabcut[tf]` (headless version with PyTorch and TensorFlow).
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* We recommend using our conda file, see [here](https://github.com/DeepLabCut/DeepLabCut/blob/main/conda-environments/README.md) or the new [`deeplabcut-docker` package](https://github.com/DeepLabCut/DeepLabCut/tree/main/docker). Please note that currently we support Python 3.9 (see conda files for guidance).
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Please click the link above for all the information you need to get started! Please note that currently we support only Python 3.10+ (see conda files for guidance).
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Developers Stable Release:
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- Very quick start: You need to have TensorFlow installed (up to v2.10 supported across platforms) `pip install "deeplabcut[gui,tf]"` that includes all functions plus GUIs, or `pip install deeplabcut[tf]` (headless version with PyTorch and TensorFlow).
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Developers Alpha Release:
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- We also have an alpha release of PyTorch DeepLabCut available! [Please see here for instructions and information](https://github.com/DeepLabCut/DeepLabCut/blob/pytorch_docs/docs/pytorch/user_guide.md).
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We recommend using our conda file, see [here](https://github.com/DeepLabCut/DeepLabCut/blob/main/conda-environments/README.md) or the new [`deeplabcut-docker` package](https://github.com/DeepLabCut/DeepLabCut/tree/main/docker).
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# [Documentation: The DeepLabCut Process](https://deeplabcut.github.io/DeepLabCut)
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@@ -209,6 +217,8 @@ SuperAnimal models are provided for research use only (non-commercial use).
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- For all versions, please see [here](https://github.com/DeepLabCut/DeepLabCut/releases).
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VERSION 3.0: A whole new experience with PyTorch🔥. While the high-level API remains the same, the backend and developer friendliness have greatly improved, along with performance gains!
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VERSION 2.3: Model Zoo SuperAnimals, and a whole new GUI experience.
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VERSION 2.2: Multi-animal pose estimation, identification, and tracking with DeepLabCut is supported (as well as single-animal projects).
@@ -220,6 +230,8 @@ VERSION 1.0: The initial, Nature Neuroscience version of [DeepLabCut](https://ww
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# News (and in the news):
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:purple_heart: We released a major update, moving from 2.x --> 3.x with the backend change to PyTorch
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:purple_heart: The DeepLabCut Model Zoo launches SuperAnimals, see more [here](http://www.mackenziemathislab.org/dlc-modelzoo/).
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:purple_heart:**DeepLabCut supports multi-animal pose estimation!** maDLC is out of beta/rc mode and beta is deprecated, thanks to the testers out there for feedback! Your labeled data will be backwards compatible, but not all other steps. Please see the [new `2.2+` releases](https://github.com/DeepLabCut/DeepLabCut/releases) for what's new & how to install it, please see our new [paper, Lauer et al 2022](https://www.nature.com/articles/s41592-022-01443-0), and the [new docs](https://deeplabcut.github.io/DeepLabCut) on how to use it!
@@ -228,6 +240,9 @@ VERSION 1.0: The initial, Nature Neuroscience version of [DeepLabCut](https://ww
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:purple_heart: We have a **real-time** package available! http://DLClive.deeplabcut.org
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- June 2024: Our second DLC paper ['Using DeepLabCut for 3D markerless pose estimation across species and behaviors'](https://www.nature.com/articles/s41596-019-0176-0) in Nature Protocols has surpassed 1,000 Google Scholar citations!
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- May 2024: DeepLabCut was featured in Nature: ['DeepLabCut: the motion-tracking tool that went viral'](https://www.nature.com/articles/d41586-024-01474-x)
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- January 2024: Our original paper ['DeepLabCut: markerless pose estimation of user-defined body parts with deep learning'](https://www.nature.com/articles/s41593-018-0209-y) in Nature Neuroscience has surpassed 3,000 Google Scholar citations!
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- December 2023: DeepLabCut hit 600,000 downloads!
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- October 2023: DeepLabCut celebrates a milestone with 4,000 🌟 in Github!
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