CodeFormer by sczhou - AI Face Restoration Model

sczhou / codeformer

Robust face restoration algorithm for old photos / AI-generated faces

Warm

Public
41.3M runs
L40S
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=sczhou/codeformer

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run sczhou/codeformer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "sczhou/codeformer:cc4956dd26fa5a7185d5660cc9100fab1b8070a1d1654a8bb5eb6d443b020bb2",
  {
    input: {
      image: "https://replicate.delivery/mgxm/a11098b0-a18a-4c02-a19a-9a7045d68426/010.jpg",
      upscale: 2,
      face_upsample: true,
      background_enhance: true,
      codeformer_fidelity: 0.1
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run sczhou/codeformer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "sczhou/codeformer:cc4956dd26fa5a7185d5660cc9100fab1b8070a1d1654a8bb5eb6d443b020bb2",
    input={
        "image": "https://replicate.delivery/mgxm/a11098b0-a18a-4c02-a19a-9a7045d68426/010.jpg",
        "upscale": 2,
        "face_upsample": True,
        "background_enhance": True,
        "codeformer_fidelity": 0.1
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run sczhou/codeformer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "cc4956dd26fa5a7185d5660cc9100fab1b8070a1d1654a8bb5eb6d443b020bb2",
    "input": {
      "image": "https://replicate.delivery/mgxm/a11098b0-a18a-4c02-a19a-9a7045d68426/010.jpg",
      "upscale": 2,
      "face_upsample": true,
      "background_enhance": true,
      "codeformer_fidelity": 0.1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Generated in

21.3 seconds

Tweak itReport

This example was created by a different version, sczhou/codeformer:7de2ea26.

Examples

View more examples

Run time and cost

This model costs approximately $0.0066 to run on Replicate, or 151 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 7 seconds.

Readme

Towards Robust Blind Face Restoration with Codebook Lookup Transformer (NeurIPS 2022) Paper | Project Page | Video

visitors

This web demo is for research purposes! If you want to use our CodeFormer for permanent free, you can run the [Github Code] locally or try out [Colab Demo] instead.

☕️ CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces. 🚀 Try CodeFormer for improved stable-diffusion generation!

If CodeFormer is helpful, please help to ⭐ the [Github Repo]. Thanks!

📋 License This project is licensed under S-Lab License 1.0. Redistribution and use for non-commercial purposes should follow this license. Note that Replicate API of CodeFormer cannot be used commercially.

📝 Citation If our work is useful for your research, please consider citing:

@inproceedings{zhou2022codeformer,
    author = {Zhou, Shangchen and Chan, Kelvin C.K. and Li, Chongyi and Loy, Chen Change},
    title = {Towards Robust Blind Face Restoration with Codebook Lookup TransFormer},
    booktitle = {NeurIPS},
    year = {2022}
}