fermatresearch/high-resolution-controlnet-tile:4af11083

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fermatresearch /high-resolution-controlnet-tile:4af11083

Playground API

Input

prompt

string

Shift + Return to add a new line

a very dark image, close up of a girl in a dark room, some neon lights in the background, cyberpunk vibes, it's so dark you can barely see anythinga very dark image, close up of a girl in a dark room, some neon lights in the background, cyberpunk vibes, it's so dark you can barely see anything

Prompt for the model

image

file

Control image for scribble controlnet

resolution

integer

Image resolution

Default: 2048

resemblance

number

(minimum: 0, maximum: 1)

Conditioning scale for controlnet

Default: 0.5

creativity

number

(minimum: 0, maximum: 1)

Denoising strength. 1 means total destruction of the original image

Default: 0.5

hdr

number

(minimum: 0, maximum: 1)

HDR improvement over the original image

Default: 0

scheduler

string

Choose a scheduler.

Default: "DDIM"

steps

integer

Steps

Default: 20

guidance_scale

number

(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 7

seed

integer

Seed

negative_prompt

string

Shift + Return to add a new line

Teeth, tooth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutantTeeth, tooth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant

Negative prompt

Default: "teeth, tooth, open mouth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"

guess_mode

boolean

In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.

Default: false

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

npx create-replicate --model=fermatresearch/high-resolution-controlnet-tile

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 fermatresearch/high-resolution-controlnet-tile using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fermatresearch/high-resolution-controlnet-tile:4af11083a13ebb9bf97a88d7906ef21cf79d1f2e5fa9d87b70739ce6b8113d29",
  {
    input: {
      hdr: 1,
      image: "https://replicate.delivery/pbxt/K5vHl2fdS6hSShLXd1Z9ODQ7RUYCFFLZB1ZZkcX47bqUUWh3/out-0.png",
      steps: 20,
      prompt: "a very dark image, close up of a girl in a dark room, some neon lights in the background, cyberpunk vibes, it's so dark you can barely see anything",
      scheduler: "DDIM",
      creativity: 0.15,
      guess_mode: false,
      resolution: 2048,
      resemblance: 0.99,
      guidance_scale: 5,
      negative_prompt: "Teeth, tooth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"
    }
  }
);

// 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 fermatresearch/high-resolution-controlnet-tile using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fermatresearch/high-resolution-controlnet-tile:4af11083a13ebb9bf97a88d7906ef21cf79d1f2e5fa9d87b70739ce6b8113d29",
    input={
        "hdr": 1,
        "image": "https://replicate.delivery/pbxt/K5vHl2fdS6hSShLXd1Z9ODQ7RUYCFFLZB1ZZkcX47bqUUWh3/out-0.png",
        "steps": 20,
        "prompt": "a very dark image, close up of a girl in a dark room, some neon lights in the background, cyberpunk vibes, it's so dark you can barely see anything",
        "scheduler": "DDIM",
        "creativity": 0.15,
        "guess_mode": False,
        "resolution": 2048,
        "resemblance": 0.99,
        "guidance_scale": 5,
        "negative_prompt": "Teeth, tooth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"
    }
)
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 fermatresearch/high-resolution-controlnet-tile 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": "fermatresearch/high-resolution-controlnet-tile:4af11083a13ebb9bf97a88d7906ef21cf79d1f2e5fa9d87b70739ce6b8113d29",
    "input": {
      "hdr": 1,
      "image": "https://replicate.delivery/pbxt/K5vHl2fdS6hSShLXd1Z9ODQ7RUYCFFLZB1ZZkcX47bqUUWh3/out-0.png",
      "steps": 20,
      "prompt": "a very dark image, close up of a girl in a dark room, some neon lights in the background, cyberpunk vibes, it\'s so dark you can barely see anything",
      "scheduler": "DDIM",
      "creativity": 0.15,
      "guess_mode": false,
      "resolution": 2048,
      "resemblance": 0.99,
      "guidance_scale": 5,
      "negative_prompt": "Teeth, tooth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

9.3 seconds

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