fofr/controlnet-preprocessors:f6584ef7 | Run with an API on Replicate

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

npx create-replicate --model=fofr/controlnet-preprocessors

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 fofr/controlnet-preprocessors using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/controlnet-preprocessors:f6584ef76cf07a2014ffe1e9bdb1a5cfa714f031883ab43f8d4b05506625988e",
  {
    input: {
      hed: true,
      sam: true,
      mlsd: true,
      pidi: true,
      canny: true,
      leres: true,
      midas: true,
      content: true,
      lineart: true,
      open_pose: true,
      normal_bae: true,
      face_detector: true,
      lineart_anime: true
    }
  }
);

// 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 fofr/controlnet-preprocessors using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/controlnet-preprocessors:f6584ef76cf07a2014ffe1e9bdb1a5cfa714f031883ab43f8d4b05506625988e",
    input={
        "hed": True,
        "sam": True,
        "mlsd": True,
        "pidi": True,
        "canny": True,
        "leres": True,
        "midas": True,
        "content": True,
        "lineart": True,
        "open_pose": True,
        "normal_bae": True,
        "face_detector": True,
        "lineart_anime": True
    }
)

# 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 fofr/controlnet-preprocessors 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": "fofr/controlnet-preprocessors:f6584ef76cf07a2014ffe1e9bdb1a5cfa714f031883ab43f8d4b05506625988e",
    "input": {
      "hed": true,
      "sam": true,
      "mlsd": true,
      "pidi": true,
      "canny": true,
      "leres": true,
      "midas": true,
      "content": true,
      "lineart": true,
      "open_pose": true,
      "normal_bae": true,
      "face_detector": true,
      "lineart_anime": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

fofr /controlnet-preprocessors:f6584ef7

Input

Output