jingyunliang/swinir:660d922d – Run with an API on Replicate

Version

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jingyunliang /swinir:660d922d

Playground API

Input

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

npx create-replicate --model=jingyunliang/swinir

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

const output = await replicate.run(
  "jingyunliang/swinir:660d922d33153019e8c263a3bba265de882e7f4f70396546b6c9c8f9d47a021a",
  {
    input: {
      jpeg: 40,
      noise: 15,
      task_type: "Real-World Image Super-Resolution-Large"
    }
  }
);

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

output = replicate.run(
    "jingyunliang/swinir:660d922d33153019e8c263a3bba265de882e7f4f70396546b6c9c8f9d47a021a",
    input={
        "jpeg": 40,
        "noise": 15,
        "task_type": "Real-World Image Super-Resolution-Large"
    }
)
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 jingyunliang/swinir 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": "jingyunliang/swinir:660d922d33153019e8c263a3bba265de882e7f4f70396546b6c9c8f9d47a021a",
    "input": {
      "jpeg": 40,
      "noise": 15,
      "task_type": "Real-World Image Super-Resolution-Large"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

No output yet! Press "Submit" to start a prediction.