Input

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

npx create-replicate --model=cjwbw/real-esrgan

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 cjwbw/real-esrgan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/real-esrgan:d0ee3d708c9b911f122a4ad90046c5d26a0293b99476d697f6bb7f2e251ce2d4",
  {
    input: {
      image: "https://replicate.delivery/pbxt/ILGG7cg5B6nJe95KzEYuUwn6ANVMNWutvNo0thaFFfkF9Xuu/groot.jpeg",
      upscale: 4
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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 cjwbw/real-esrgan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/real-esrgan:d0ee3d708c9b911f122a4ad90046c5d26a0293b99476d697f6bb7f2e251ce2d4",
    input={
        "image": "https://replicate.delivery/pbxt/ILGG7cg5B6nJe95KzEYuUwn6ANVMNWutvNo0thaFFfkF9Xuu/groot.jpeg",
        "upscale": 4
    }
)
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 cjwbw/real-esrgan 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": "cjwbw/real-esrgan:d0ee3d708c9b911f122a4ad90046c5d26a0293b99476d697f6bb7f2e251ce2d4",
    "input": {
      "image": "https://replicate.delivery/pbxt/ILGG7cg5B6nJe95KzEYuUwn6ANVMNWutvNo0thaFFfkF9Xuu/groot.jpeg",
      "upscale": 4
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

12.0 seconds

Tweak itReport

Examples

View more examples

Run time and cost

This model costs approximately $0.0025 to run on Replicate, or 400 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 T4 GPU hardware. Predictions typically complete within 11 seconds.

Readme

Original implementation: https://github.com/ai-forever/Real-ESRGAN

Real-ESRGAN

PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original version. It is also easier to integrate this model into your projects.

This is not an official implementation. We partially use code from the original repository

Real-ESRGAN is an upgraded ESRGAN trained with pure synthetic data is capable of enhancing details while removing annoying artifacts for common real-world images.