qr2ai/img2paint_controlnet:dec8d855 – Run with an API on Replicate

Version

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qr2ai /img2paint_controlnet:dec8d855

Playground API

Input

image

file

Input image for img2img or inpaint mode

qr_data

string

Shift + Return to add a new line

The data to be encoded in a QR code.

prompt

string

Shift + Return to add a new line

aerial view, a futuristic research complex in a bright foggy jungle, hard lightingaerial view, a futuristic research complex in a bright foggy jungle, hard lighting

Input prompt

Default: "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting"

negative_prompt

string

Shift + Return to add a new line

Input Negative Prompt

Default: "low quality, bad quality, sketches"

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

condition_scale

number

(minimum: 0, maximum: 1)

controlnet conditioning scale for generalization

Default: 0.5

seed

integer

Random seed. Set to 0 to randomize the seed

Default: 0

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

npx create-replicate --model=qr2ai/img2paint_controlnet

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 qr2ai/img2paint_controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "qr2ai/img2paint_controlnet:dec8d855d5e1692b737a5edd83a816f704552549b04e23c453d5a7ef4dd107b6",
  {
    input: {
      seed: 0,
      prompt: "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting",
      condition_scale: 0.5,
      negative_prompt: "low quality, bad quality, sketches",
      num_inference_steps: 50
    }
  }
);
console.log(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 qr2ai/img2paint_controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "qr2ai/img2paint_controlnet:dec8d855d5e1692b737a5edd83a816f704552549b04e23c453d5a7ef4dd107b6",
    input={
        "seed": 0,
        "prompt": "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting",
        "condition_scale": 0.5,
        "negative_prompt": "low quality, bad quality, sketches",
        "num_inference_steps": 50
    }
)
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 qr2ai/img2paint_controlnet 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": "dec8d855d5e1692b737a5edd83a816f704552549b04e23c453d5a7ef4dd107b6",
    "input": {
      "seed": 0,
      "prompt": "aerial view, a futuristic research complex in a bright foggy jungle, hard lighting",
      "condition_scale": 0.5,
      "negative_prompt": "low quality, bad quality, sketches",
      "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.