Make sure you have successfully built python environment and installed pytorch with cuda version. Before running the script, ensure you have all the required packages installed. You can install them using:

pip install diffusers, PIL, numpy, timm, argparse, einops

Usage👀️

To use the CoRe^2 pipeline, you need to run the sample_img.py script with appropriate command-line arguments. Below are the available options:

Command-Line Arguments

--pipeline: Select the model pipeline (sdxl, sd35). Default is sdxl.
--prompt: The textual prompt based on which the image will be generated. Default is "Mickey Mouse painting by Frank Frazetta."
--inference-step: Number of inference steps for the diffusion process. Default is 50.
--cfg: Classifier-free guidance scale. Default is 5.5.
--pretrained-path: Path to the pretrained model weights. Default is a specified path in the script.
--size: The size (height and width) of the generated image. Default is 1024.
--method: Select the inference method (standard, core, zigzag, z-core)

Running the Script

Run the script from the command line by navigating to the directory containing sample_img.py and executing:

python sample_img.py --pipeline sdxl --prompt "A banana on the left of an apple." --size 1024

This command will generate an image based on the prompt using the Stable Diffusion XL model with an image size of 1024x1024 pixels.

Output🎉️

The script will save one image.

sst12345/CoRe2

The Official Implementation of our Arxiv 2025 paper:

New

Overview

Requirements

Installation🚀️

Usage👀️

Command-Line Arguments

Running the Script

Output🎉️

sst12345/
CoRe2