README.md

---
title: CCSR Upscaler
emoji: 👁
colorFrom: gray
colorTo: indigo
sdk: gradio
sdk_version: 4.42.0
app_file: app.py
pinned: true
short_description: Upscale an image using CCSR
---

# CCSR Upscaler

This Gradio space implements the Continuous Contrastive Super-Resolution (CCSR) model for image upscaling. CCSR is a state-of-the-art super-resolution method that can upscale images while preserving details and enhancing quality.

## Features

- Upload any image for upscaling
- Adjust super-resolution scale (1x to 8x)
- Fine-tune parameters like t_max and t_min
- Choose from different color fixing methods

## How to Use

1. Upload an image you want to upscale
2. Adjust the SR Scale slider to set the upscaling factor
3. Fine-tune t_max and t_min values if desired
4. Select a color fixing method from the dropdown
5. Click "Submit" to generate the upscaled image

## Model Details

This space uses the CCSR model trained on real-world images. The model checkpoint and configuration are loaded from:

- Checkpoint: `weights/real-world_ccsr.ckpt`
- Config: `configs/model/ccsr_stage2.yaml`

## Requirements

The main dependencies for this project are listed in the `requirements.txt` file, including:

- torch
- torchvision
- gradio
- einops
- pytorch-lightning
- omegaconf
- open-clip-torch
- xformers
- taming-transformers

## Acknowledgements

This implementation is based on the CCSR model. For more details about the original work, please refer to the [CCSR GitHub repository](https://github.com/camenduru/CCSR).