Spaces:
Running
on
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Running
on
Zero
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README.md
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title:
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned:
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title: CCSR Upscaler
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emoji: 👁
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colorFrom: gray
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sdk: gradio
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sdk_version: 3.23.0
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app_file: app.py
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pinned: true
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short_description: Upscale an image using CCSR
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# CCSR Upscaler
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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.
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## Features
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- Upload any image for upscaling
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- Adjust super-resolution scale (1x to 8x)
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- Fine-tune parameters like t_max and t_min
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- Choose from different color fixing methods
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## How to Use
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1. Upload an image you want to upscale
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2. Adjust the SR Scale slider to set the upscaling factor
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3. Fine-tune t_max and t_min values if desired
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4. Select a color fixing method from the dropdown
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5. Click "Submit" to generate the upscaled image
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## Model Details
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This space uses the CCSR model trained on real-world images. The model checkpoint and configuration are loaded from:
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- Checkpoint: `weights/real-world_ccsr.ckpt`
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- Config: `configs/model/ccsr_stage2.yaml`
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## Requirements
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The main dependencies for this project are listed in the `requirements.txt` file, including:
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- torch
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- torchvision
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- gradio
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- einops
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- pytorch-lightning
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- omegaconf
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- open-clip-torch
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- xformers
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- taming-transformers
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## Acknowledgements
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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).
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