Input

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

npx create-replicate --model=xinntao/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 xinntao/esrgan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "xinntao/esrgan:c263265e04b16fda1046d1828997fc27b46610647a3348df1c72fbffbdbac912",
  {
    input: {
      image: "https://replicate.delivery/mgxm/72cbdfd0-ffbb-406c-8b65-a8b16b84de40/Screen_Shot_2021-08-25_at_18.51.54.png"
    }
  }
);

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

output = replicate.run(
    "xinntao/esrgan:c263265e04b16fda1046d1828997fc27b46610647a3348df1c72fbffbdbac912",
    input={
        "image": "https://replicate.delivery/mgxm/72cbdfd0-ffbb-406c-8b65-a8b16b84de40/Screen_Shot_2021-08-25_at_18.51.54.png"
    }
)
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 xinntao/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": "xinntao/esrgan:c263265e04b16fda1046d1828997fc27b46610647a3348df1c72fbffbdbac912",
    "input": {
      "image": "https://replicate.delivery/mgxm/72cbdfd0-ffbb-406c-8b65-a8b16b84de40/Screen_Shot_2021-08-25_at_18.51.54.png"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Tweak itReport

This output was created using a different version of the model, xinntao/esrgan:3a69fc05.

Examples

View more examples

Run time and cost

This model costs approximately $0.0015 to run on Replicate, or 666 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 7 seconds.

Readme

Enhanced Super-Resolution Generative Adversarial Networks

By Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, Chen Change Loy

We won the first place in PIRM2018-SR competition (region 3) and got the best perceptual index. The paper is accepted to ECCV2018 PIRM Workshop.