omniedgeio/fabricai:a97d3837 – Run with an API on Replicate

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omniedgeio /fabricai:a97d3837

Playground API

Input

image

*file

input image

fabric_image

*file

image for style

clothes_type

string

Format of the output images

Default: "Dress"

style_strength

number

(minimum: 0, maximum: 3)

How much the style should get applied

Default: 0.4

structure_strength

number

(minimum: 0, maximum: 3)

How much the structure should keep the same

Default: 0.6

prompt

string

Shift + Return to add a new line

Prompt

Default: "masterpiece, best quality, highres"

negative_prompt

string

Shift + Return to add a new line

worst quality, low quality, normal qualityworst quality, low quality, normal quality

Negative Prompt

Default: "worst quality, low quality, normal quality"

num_inference_steps

integer

(minimum: 1, maximum: 100)

Number of denoising steps

Default: 30

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 8

seed

integer

Leave blank to randomize the seed

Default: 1337

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

npx create-replicate --model=omniedgeio/fabricai

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

const output = await replicate.run(
  "omniedgeio/fabricai:a97d3837addca8b45eeaafcd50a34f905e80c78a02e1bdf1c198eb196ff379dd",
  {
    input: {
      seed: 1337,
      prompt: "masterpiece, best quality, highres",
      clothes_type: "Dress",
      guidance_scale: 8,
      style_strength: 0.4,
      negative_prompt: "worst quality, low quality, normal quality",
      structure_strength: 0.6,
      num_inference_steps: 30
    }
  }
);

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

output = replicate.run(
    "omniedgeio/fabricai:a97d3837addca8b45eeaafcd50a34f905e80c78a02e1bdf1c198eb196ff379dd",
    input={
        "seed": 1337,
        "prompt": "masterpiece, best quality, highres",
        "clothes_type": "Dress",
        "guidance_scale": 8,
        "style_strength": 0.4,
        "negative_prompt": "worst quality, low quality, normal quality",
        "structure_strength": 0.6,
        "num_inference_steps": 30
    }
)
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 omniedgeio/fabricai 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": "omniedgeio/fabricai:a97d3837addca8b45eeaafcd50a34f905e80c78a02e1bdf1c198eb196ff379dd",
    "input": {
      "seed": 1337,
      "prompt": "masterpiece, best quality, highres",
      "clothes_type": "Dress",
      "guidance_scale": 8,
      "style_strength": 0.4,
      "negative_prompt": "worst quality, low quality, normal quality",
      "structure_strength": 0.6,
      "num_inference_steps": 30
    }
  }' \
  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.