rossjillian/controlnet_1-1:bc5c323e | Run with an API on Replicate

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rossjillian /controlnet_1-1:bc5c323e

Playground API

Input

image

*file

Input image

prompt

*string

Shift + Return to add a new line

Prompt for the model

structure

*string

Structure to condition on

num_samples

string

Number of samples (higher values may OOM)

Default: "1"

image_resolution

string

Resolution of image (square)

Default: "512"

steps

integer

Steps

Default: 20

scale

number

(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 9

seed

integer

Seed

eta

number

Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise

Default: 0

a_prompt

string

Shift + Return to add a new line

Additional text to be appended to prompt

Default: "Best quality, extremely detailed"

n_prompt

string

Shift + Return to add a new line

Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low qualityLongbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality

Negative prompt

Default: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality"

low_threshold

integer

(minimum: 1, maximum: 255)

[canny only] Line detection low threshold

Default: 100

high_threshold

integer

(minimum: 1, maximum: 255)

[canny only] Line detection high threshold

Default: 200

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

npx create-replicate --model=rossjillian/controlnet_1-1

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 rossjillian/controlnet_1-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "rossjillian/controlnet_1-1:bc5c323ec65c090856ad3bc6da609b5b47d7ede9c367b1f17c372d7563bd0218",
  {
    input: {
      eta: 0,
      image: "https://replicate.delivery/pbxt/IfYdW0q5YMRU1djC3KhGk9H59v8Qns8jkP6bN5DDAxZmEMMD/house.png",
      scale: 9,
      steps: 20,
      prompt: "a modernist house in a nice landscape",
      a_prompt: "Best quality, extremely detailed",
      n_prompt: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      structure: "seg",
      num_samples: "1",
      low_threshold: 100,
      high_threshold: 200,
      image_resolution: "512"
    }
  }
);

// 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 rossjillian/controlnet_1-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "rossjillian/controlnet_1-1:bc5c323ec65c090856ad3bc6da609b5b47d7ede9c367b1f17c372d7563bd0218",
    input={
        "eta": 0,
        "image": "https://replicate.delivery/pbxt/IfYdW0q5YMRU1djC3KhGk9H59v8Qns8jkP6bN5DDAxZmEMMD/house.png",
        "scale": 9,
        "steps": 20,
        "prompt": "a modernist house in a nice landscape",
        "a_prompt": "Best quality, extremely detailed",
        "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
        "structure": "seg",
        "num_samples": "1",
        "low_threshold": 100,
        "high_threshold": 200,
        "image_resolution": "512"
    }
)
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 rossjillian/controlnet_1-1 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": "rossjillian/controlnet_1-1:bc5c323ec65c090856ad3bc6da609b5b47d7ede9c367b1f17c372d7563bd0218",
    "input": {
      "eta": 0,
      "image": "https://replicate.delivery/pbxt/IfYdW0q5YMRU1djC3KhGk9H59v8Qns8jkP6bN5DDAxZmEMMD/house.png",
      "scale": 9,
      "steps": 20,
      "prompt": "a modernist house in a nice landscape",
      "a_prompt": "Best quality, extremely detailed",
      "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      "structure": "seg",
      "num_samples": "1",
      "low_threshold": 100,
      "high_threshold": 200,
      "image_resolution": "512"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

4.1 seconds

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