| # Installation | |
| ## 📙 We support two independent environments. You just need to install corresponding environment. | |
| ## For MMPose | |
| 🌵🌵🌵 This environment helps you to train and test our DWPose. You can ignore the following installation for ControlNet. | |
| 🌵 You can refer [MMPose Installation](https://mmpose.readthedocs.io/en/latest/installation.html) or | |
| ``` | |
| # Set MMPose environment | |
| pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html | |
| pip install -r requirements.txt | |
| ``` | |
| ## For ControlNet | |
| 🌵🌵🌵 This environment helps you to apply DWPose to ControlNet. You can ignore the above installation for mmpose. | |
| 🌵 First, make sure to run ControlNet successfully. | |
| ``` | |
| # Set ControlNet environment | |
| conda env create -f environment.yaml | |
| conda activate control-v11 | |
| ``` | |
| 🌵 Second, install tools to apply DWPose to ControlNet. If it's hard to install onnxruntime, you can refer branch [opencv_onnx](https://github.com/IDEA-Research/DWPose/tree/opencv_onnx), which runs the onnx model with opencv. | |
| ``` | |
| # Set ControlNet environment | |
| pip install onnxruntime | |
| # if gpu is available | |
| pip install onnxruntime-gpu | |
| ``` |