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Merge pull request #155 from DeepLabCut/jaap/update_installation_docs
Update installation docs for windows users with GPU
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README.md

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@@ -77,14 +77,18 @@ DeepLabCut-live can be installed from PyPI with PyTorch or Tensorflow directly:
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uv pip install deeplabcut-live[pytorch] # or [tf]
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```
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Note: On **Windows**, the `deeplabcut-live[pytorch]` extra will not install the required CUDA-enabled wheels for PyTorch by default. For GPU support, install CUDA-enabled PyTorch first, then install `deeplabcut-live[pytorch]`.
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Please see our instruction manual for more elaborate information on how to install on a [Windows or Linux machine](
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docs/install_desktop.md) or on a [NVIDIA Jetson Development Board](
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docs/install_jetson.md). Note, this code works with PyTorch, TensorFlow 1 or TensorFlow
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docs/install_jetson.md).
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This code works with PyTorch, TensorFlow 1 or TensorFlow
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2 models, but whatever engine you exported your model with, you must import with the
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same version (i.e., export a PyTorch model, then install PyTorch, export with TF1.13,
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then use TF1.13 with DlC-Live; export with TF2.3, then use TF2.3 with DLC-live).
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Note, you can test your installation by running:
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You can test your installation by running:
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```bash
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dlc-live-test

docs/install_desktop.md

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# Or using uv
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uv pip install deeplabcut-live[pytorch] # or [tf]
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```
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### Windows-users with GPU:
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On **Windows**, the `deeplabcut-live[pytorch]` extra will not install the required CUDA-enabled wheels for PyTorch by default. Windows users with a CUDA GPU should install CUDA-enabled PyTorch first:
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```bash
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# First install PyTorch with CUDA support
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pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124
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# Then install DeepLabCut-live (it will use the existing GPU-enabled PyTorch)
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pip install deeplabcut-live[pytorch]
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```
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## 2. Install from Git Repository
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If you want to install from a local clone of the repository, follow these steps:

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