Awesome
DiffusionNOCS
Overview
The repository contains the implementation of DiffusionNOCS inference.
The paper and github pages are available:
- arXiv: https://arxiv.org/abs/2402.12647
- Github Pages: https://woven-planet.github.io/DiffusionNOCS/
Run on Google Colab
You can try the inference of DiffusionNOCS by clicking the link below and following instructions in the colab noteboook.
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Run locally
How to install
git clone https://github.com/woven-planet/DiffusionNOCS.git
cd DiffusionNOCS
./download_weights.sh
python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
pip install -e .
ipython kernel install --user --name=venv
If you'd like to use your specific version, please modify requirements.txt based on your preference.
Try inference on jupyter notebook
Run the following code:
jupyter notebook notebooks/diffusion_nocs.ipynb
Click Kernel tab, then change kernel to venv.
Try inference from python file
Run the following code:
python3 scripts/inference.py --category-name "bottle"
Generalization Benchmark Dataset
How to create the dataset of Generalization Benchmark
About This Project and Us
This work has been done at Woven by Toyota, Inc, and Toyota Research Institute.
Takuya Ikeda, Tianyi Ko, Robert Lee and Koichi Nishiwaki are with the Woven by Toyota, Inc.
Sergey Zakharov, Muhammad Zubair Irshad, Katherine Liu and Rares Ambrus are with the Toyota Research Institute.
Acknowledgement
The implementation was supported by Yuki Igarashi in Woven by Toyota, Inc. We'd like to express our deep gratitude to him.