Prediction

flores-o/sd-x2-latent-upscaler:afa82d37

Model

flores-o/sd-x2-latent-upscaler:afa82d37

lv2i3gcwpfhgnkto4dqibiqqom

Status

Succeeded

Source

Web

Hardware

–

Total duration

2m 34s

Created

almost 3 years ago

Input

image
scheduler: K_EULER
guidance_scale: 7.5
num_inference_steps: "5"

{
  "image": "https://replicate.delivery/pbxt/ILIDByuZiYqR0In8CFaEXsM1YhiCa8Pm9raS1KiOhvjEper2/input_image.png",
  "scheduler": "K_EULER",
  "guidance_scale": 7.5,
  "num_inference_steps": "5"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

Run flores-o/sd-x2-latent-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "flores-o/sd-x2-latent-upscaler:afa82d37d41bbf365d8a50a14ecc66283c0c004f72ca9ac43196bd8cbd54dc0e",
  {
    input: {
      image: "https://replicate.delivery/pbxt/ILIDByuZiYqR0In8CFaEXsM1YhiCa8Pm9raS1KiOhvjEper2/input_image.png",
      scheduler: "K_EULER",
      guidance_scale: 7.5,
      num_inference_steps: "5"
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run flores-o/sd-x2-latent-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "flores-o/sd-x2-latent-upscaler:afa82d37d41bbf365d8a50a14ecc66283c0c004f72ca9ac43196bd8cbd54dc0e",
    input={
        "image": "https://replicate.delivery/pbxt/ILIDByuZiYqR0In8CFaEXsM1YhiCa8Pm9raS1KiOhvjEper2/input_image.png",
        "scheduler": "K_EULER",
        "guidance_scale": 7.5,
        "num_inference_steps": "5"
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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

Run flores-o/sd-x2-latent-upscaler 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": "flores-o/sd-x2-latent-upscaler:afa82d37d41bbf365d8a50a14ecc66283c0c004f72ca9ac43196bd8cbd54dc0e",
    "input": {
      "image": "https://replicate.delivery/pbxt/ILIDByuZiYqR0In8CFaEXsM1YhiCa8Pm9raS1KiOhvjEper2/input_image.png",
      "scheduler": "K_EULER",
      "guidance_scale": 7.5,
      "num_inference_steps": "5"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

6.2 seconds

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