Summary

This guide outlines the setup process for ViTPose, a state-of-the-art 2D/3D pose estimation model, on a Windows 11 system with an RTX 4080 GPU. While the official documentation primarily supports Linux, this setup demonstrates a successful installation on Windows.

Device Configuration

Operating System: Windows 11 (Official support: Linux)
GPU: NVIDIA RTX 4080
NVIDIA Driver: 566.07
CUDA Version: 11.1 (Download CUDA 11.1.1)
cuDNN Version: 8.0.5 (Download cuDNN 8.0.5)
Development Tools:
- MSYS2 + MinGW-w64
- Python: 3.7.16
- Visual Studio: 2019
- GCC: 14.2.0 (Rev2, Built by MSYS2 project).
- System PATH: MinGW-w64 is added to Windows' system PATH

Library	Version
PyTorch	1.9.0 + cu111
TorchVision	0.10.0 + cu111
MMCV (mmcv-full)	1.3.9
MMPose	0.24.0
OpenCV	4.11.0
xtcocotools	1.14.3
timm	0.4.9
scipy	1.7.3
openmim	0.3.9
opencv-python	4.11.0.86
opencv-contrib-python	4.11.0.86
numpy	1.21.6
matplotlib	3.5.3
json-tricks	3.17.3

Installation Steps

conda create -n vitpose_official python=3.7.6 -y
conda activate vitpose_test
conda install pytorch==1.9.0 torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia
pip install timm==0.4.9 einops
pip install matplotlib==3.5.3
pip install scipy==1.7.3
pip install json-tricks==3.17.3
pip install numpy==1.21.6

% clone ViTPose 
git clone https://github.com/ViTAE-Transformer/ViTPose.git
cd ViTPose
git clone https://github.com/open-mmlab/mmcv.git
cd mmcv
git checkout v1.3.9
set MMCV_WITH_OPS=1 
pip install -e .
======
(maybe below code also okay)
pip install -U openmim
mim install mmcv-full==1.3.9
=====
cd ..
git clone https://github.com/open-mmlab/mmpose.git
cd mmpose
pip install -r requirements.txt
pip install -v -e .
cd ..
pip install -v -e .