andreasjansson/stable-diffusion-inpainting:3b65a049

Version

You're looking at a specific version of this model. Jump to the model overview.

andreasjansson /stable-diffusion-inpainting:3b65a049

Playground API

Input

prompt

string

Shift + Return to add a new line

Input prompt

Default: ""

image

*file

Input image to in-paint. Width and height should both be divisible by 8. If they're not, the image will be center cropped to the nearest width and height divisible by 8

mask

*file

Black and white image to use as mask. White pixels are inpainted and black pixels are preserved.

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output. NSFW filter in enabled, so you may get fewer outputs than requested if flagged

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=andreasjansson/stable-diffusion-inpainting

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";
import fs from "node:fs";

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

Run andreasjansson/stable-diffusion-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/stable-diffusion-inpainting:3b65a049057a5ce7d0d4cff143cacbeedf7a0587add8ba96a81f9512e3566ec1",
  {
    input: {
      prompt: "",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 50
    }
  }
);

// 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

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 andreasjansson/stable-diffusion-inpainting using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/stable-diffusion-inpainting:3b65a049057a5ce7d0d4cff143cacbeedf7a0587add8ba96a81f9512e3566ec1",
    input={
        "prompt": "",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 50
    }
)

# 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.

Set the REPLICATE_API_TOKEN environment variable:

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

Find your API token in your account settings.

Run andreasjansson/stable-diffusion-inpainting 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": "andreasjansson/stable-diffusion-inpainting:3b65a049057a5ce7d0d4cff143cacbeedf7a0587add8ba96a81f9512e3566ec1",
    "input": {
      "prompt": "",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 50
    }
  }' \
  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.