This repo's aim is to get V2VPoseNet working on the DepthAI cameras
Tested on a Windows 11 AMD 5950x Nvidia 3090 machine running:
- Python 3.9.9
- numpy 1.22.0
- open3d 0.14.1.0
- depthai 2.13.3.0
- torch 1.10+cu113 (pytorch)
- Clone the repo
- Open a Python terminal in the root directory of the repo
- Run the following to install the dependencies
python3 install_requirements.py - Install PyTorch (with CUDA) the install link for this on Windows 10/11 with a modern Nvidia GPU is as follows:
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio===0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
For other installs use the config tool at pytorch.org to download it
Run the following:
python3 main.py
This should spawn a window of the depth camera output, where the person is highlighted in blue and the background in red.
To orient this correctly the camera should be placed so it's 90degrees to the right (so the cable comes out the left side).
Using the blue pointcloud a center point is generated which is passed to V2VPoseNet along with a cropped pointcloud, and the output is then displayed.
Moon, Gyeongsik, Ju Yong Chang, and Kyoung Mu Lee. "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map." CVPR 2018. [arXiv]
@InProceedings{Moon_2018_CVPR_V2V-PoseNet,
author = {Moon, Gyeongsik and Chang, Juyong and Lee, Kyoung Mu},
title = {V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018}
}