One View, Many Worlds: Single-Image to 3D Object Meets Generative Domain Randomization for One-Shot 6D Pose Estimation

Zheng Geng, Nan Wang, Shaocong Xu, Bohan Li, Zhaoxi Chen, Chongjie Ye, Sida Peng, Hao Zhao

TODO:

• [ ] Release Polished Paper
• [ ] Release Evaluation Code
• [ ] Release Training Code

⚙️ Installation

Quick Setup Using setup.sh

To streamline the setup process, we provide a setup.sh script that automates all installation steps. Follow these instructions to get started:

Prerequisites

Before running the setup.sh script, ensure you have the following prerequisites installed on your system:

• Python 3.11+
• Conda (recommended)
• Basic build tools (git, make, cmake, etc.)

Usage

1. Clone the repository:

bash git clone https://github.com/GZWSAMA/OnePoseviaGen.git cd OnePoseviaGen

1. Make the setup.sh script executable:

bash chmod +x setup.sh

1. Run the setup.sh script:

It is recommended to run this script within a fresh conda environment. Here's how you can create and activate a new environment before running the script:

bash conda create -n OnePoseviaGen python=3.11 -y conda activate OnePoseviaGen ./setup.sh

The script will handle: - Installing PyTorch with CUDA support. - Installing required dependencies. - Cloning and installing external extensions. - Building FoundationPose. - Installing local packages in editable mode. - Downloading pretrained weights. - Patching the transformers library.

1. Verify the setup:

After running the script, verify that all dependencies are correctly installed and the necessary files are downloaded.

1. Web demo:

bash python app.py

Troubleshooting

Indices should be on the same device

Can't convert cuda:0 device type tensor to numpy

📚 Citation

If you find this work useful, please cite:

TODO