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Option (B). If you install mmpose with pip, open you python interpreter and copy & paste the following codes.
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Option (B). If you install mmpose with pip, open your Python interpreter and copy & paste the following codes.
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```python
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from mmpose.apis import inference_topdown, init_model
@@ -170,25 +170,25 @@ When installing PyTorch, you need to specify the version of CUDA. If you are not
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Please make sure the GPU driver satisfies the minimum version requirements. See [this table](https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#cuda-major-component-versions__table-cuda-toolkit-driver-versions) for more information.
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Installing CUDA runtime libraries is enough if you follow our best practices, because no CUDA code will be compiled locally. However if you hope to compile MMCV from source or develop other CUDA operators, you need to install the complete CUDA toolkit from NVIDIA's [website](https://developer.nvidia.com/cuda-downloads), and its version should match the CUDA version of PyTorch. i.e., the specified version of cudatoolkit in `conda install` command.
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Installing CUDA runtime libraries is enough if you follow our best practices, because no CUDA code will be compiled locally. However, if you hope to compile MMCV from source or develop other CUDA operators, you need to install the complete CUDA toolkit from NVIDIA's [website](https://developer.nvidia.com/cuda-downloads), and its version should match the CUDA version of PyTorch. i.e., the specified version of cudatoolkit in `conda install` command.
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### Install MMEngine without MIM
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To install MMEngine with pip instead of MIM, please follow [MMEngine installation guides](https://mmengine.readthedocs.io/zh_CN/latest/get_started/installation.html).
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For example, you can install MMEngine by the following command.
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For example, you can install MMEngine using the following command.
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```shell
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pip install mmengine
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```
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### Install MMCV without MIM
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MMCV contains C++ and CUDA extensions, thus depending on PyTorch in a complex way. MIM solves such dependencies automatically and makes the installation easier. However, it is not a must.
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MMCV contains C++ and CUDA extensions, thus, it depends on PyTorch in a complex way. MIM solves such dependencies automatically and makes the installation easier. However, it is not a must.
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To install MMCV with pip instead of MIM, please follow [MMCV installation guides](https://mmcv.readthedocs.io/en/2.x/get_started/installation.html). This requires manually specifying a find-url based on PyTorch version and its CUDA version.
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For example, the following command install mmcv built for PyTorch 1.10.x and CUDA 11.3.
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For example, the following command installs mmcv built for PyTorch 1.10.x and CUDA 11.3.
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