Spaces:
Running
Running
A newer version of the Gradio SDK is available:
5.9.1
metadata
title: CCSR Upscaler
emoji: π
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
- Upload an image you want to upscale
- Adjust the SR Scale slider to set the upscaling factor
- Fine-tune t_max and t_min values if desired
- Select a color fixing method from the dropdown
- 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.