ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting (NeurIPS 2023, Spotlight)
Official Repo : https://github.com/zsyOAOA/ResShift
I have developed a very advanced Gradio APP.
Developed APP Scripts and Installers : https://www.patreon.com/posts/110331752
Features
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It supports following tasks:
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Real-world image super-resolution
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Bicubic (resize by Matlab) image super-resolution
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Blind Face Restoration
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Automatically saving all generated image with same name + numbering if necessary
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Randomize seed feature for each generation
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Batch image processing - give input and output folder paths and it batch process all images and saves
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1-Click to install on Windows, RunPod, Massed Compute and Kaggle (free account)
Windows Requirements
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Python 3.10, FFmpeg, Cuda 11.8, C++ tools and Git
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If it doesn't work make sure to below tutorial and install everything exactly as shown in this below tutorial
How to Install on Windows
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Make sure that you have the above requirements
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Extract files into a folder like c:/reshift_v1
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Double click Windows_Install.bat and it will automatically install everything for you with an isolated virtual environment folder (VENV)
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After that double click Windows_Start_app.bat and start the app
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When you first time use a task it will download necessary models (all under 500 MB) into accurate folders
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If during download it fails, file gets corrupted sadly it doesn't verify that so delete files inside weights and restart
How to Install on RunPod, Massed Compute, Kaggle
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Follow the Massed_Compute_Instructions_READ.txt and Runpod_Instructions_READ.txt
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For Kaggle follow the notebook written steps
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An example video of how to use my RunPod, Massed Compute scripts and Kaggle notebook can be seen below watch it to learn
Some Screenshots
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