LanPaint Benchmark

This is the repo for academic benchmark of LanPaint

Prerequisites

• Python 3.9 or higher
• A Linux-based operating system (e.g., Ubuntu)
• make utility for build automation

Setup Instructions

1. Create a Python Virtual Environment
   Create and activate a new Python virtual environment to manage dependencies:

   python3 -m venv venv
   source venv/bin/activate

2. Install System Dependencies
   Ensure make is installed on your Linux system. Run the following commands:

   sudo apt update
   sudo apt install make

3. Install Python Dependencies

   pip install -r requirements.txt

4. Download the Pre-trained Model
   Download the pre-trained model checkpoint from the following link:
   256x256_diffusion_uncond.pt
   Place the downloaded file in the ./checkpoints directory.

5. Run the Benchmark
   Execute the benchmark using the provided make command:

   make run_imagenet

6. Check Results
   Metrics like LPIPS and FID will be output into ./results as a CSV file.

Citation

@misc{zheng2025lanpainttrainingfreediffusioninpainting,
      title={Lanpaint: Training-Free Diffusion Inpainting with Exact and Fast Conditional Inference}, 
      author={Candi Zheng and Yuan Lan and Yang Wang},
      year={2025},
      eprint={2502.03491},
      archivePrefix={arXiv},
      primaryClass={eess.IV},
      url={https://arxiv.org/abs/2502.03491}, 
}