The GitHub repository titled "PerCo" by Nikolai10 presents a PyTorch implementation of a novel image compression technique aimed at achieving perfect realism at ultra-low bitrates. This work is based on the paper "Towards Image Compression with Perfect Realism at Ultra-Low Bitrates," which is set to be presented at ICLR 2024. The repository distinguishes itself by utilizing Stable Diffusion v2.1 as its latent diffusion model, contrasting with the original work that relied on a proprietary pre-trained model. The project is actively under development, with several updates already made. Notable improvements include fine-tuning the entire U-Net architecture, which has led to enhanced results, and the release of pre-trained models. The repository also documents various experiments, including ablation studies that explored different techniques without achieving significant improvements. Visual comparisons of the compression results on the Kodak dataset illustrate the model's performance at the lowest bit-rate, showcasing reconstructions that reflect uncertainty about the original images. The repository provides quantitative performance metrics, indicating that while the PerCo (SD v2.1) model achieves competitive perceptual results, it sacrifices some image fidelity compared to the official model due to fewer training steps. Installation instructions are provided, along with guidance for training, inference, and evaluation. The project uses the OpenImagesV6 dataset for training and offers a simplified Google Colab demo for ease of use. Future plans include enhancing compression functionality, integrating additional datasets, and refining the training pipeline. The file structure of the repository is organized into directories for Docker functionality, Jupyter notebooks, evaluation data, and source code. The project acknowledges various libraries and frameworks that inspired its development, including HuggingFace's Diffusers and Transformers, as well as other tools for data compression and neural network research. Overall, the PerCo repository represents a significant step forward in the field of image compression, aiming to balance the trade-offs between perceptual quality and image fidelity at extremely low bitrates. The project is licensed under the Apache License 2.0, encouraging collaboration and further development within the open-source community.