fofr/illusions:579b32db – Run with an API on Replicate

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fofr /illusions:579b32db

Playground API

Input

prompt

string

Shift + Return to add a new line

Default: "a painting of a 19th century town"

negative_prompt

string

Shift + Return to add a new line

ugly, disfigured, low quality, blurry, nsfwugly, disfigured, low quality, blurry, nsfw

The negative prompt to guide image generation.

Default: "ugly, disfigured, low quality, blurry, nsfw"

num_inference_steps

integer

(minimum: 20, maximum: 100)

Number of diffusion steps

Default: 40

guidance_scale

number

(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 7.5

seed

integer

width

integer

Default: 768

height

integer

Default: 768

sizing_strategy

string

Decide how to resize images – use width/height, resize based on input image or control image

Default: "width/height"

num_outputs

integer

(minimum: 1, maximum: 4)

Number of outputs

Default: 1

control_image

file

Preview

Control image

image

file

Preview

Optional img2img

mask_image

file

Optional mask for inpainting

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image

Default: 0.8

controlnet_conditioning_scale

number

(minimum: 0, maximum: 4)

How strong the controlnet conditioning is

Default: 0.75

controlnet_start

number

(minimum: 0, maximum: 1)

When controlnet conditioning starts

Default: 0

controlnet_end

number

(minimum: 0, maximum: 1)

When controlnet conditioning ends

Default: 1

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

npx create-replicate --model=fofr/illusions

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

const output = await replicate.run(
  "fofr/illusions:579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8",
  {
    input: {
      seed: -1,
      image: "https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png",
      width: 768,
      height: 768,
      prompt: "a painting of a 19th century town",
      num_outputs: 1,
      control_image: "https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg",
      controlnet_end: 1,
      guidance_scale: 7.5,
      negative_prompt: "ugly, disfigured, low quality, blurry, nsfw",
      prompt_strength: 0.75,
      sizing_strategy: "width/height",
      controlnet_start: 0,
      num_inference_steps: 40,
      controlnet_conditioning_scale: 0.75
    }
  }
);
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 fofr/illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/illusions:579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8",
    input={
        "seed": -1,
        "image": "https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png",
        "width": 768,
        "height": 768,
        "prompt": "a painting of a 19th century town",
        "num_outputs": 1,
        "control_image": "https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg",
        "controlnet_end": 1,
        "guidance_scale": 7.5,
        "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
        "prompt_strength": 0.75,
        "sizing_strategy": "width/height",
        "controlnet_start": 0,
        "num_inference_steps": 40,
        "controlnet_conditioning_scale": 0.75
    }
)
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 fofr/illusions 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": "579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8",
    "input": {
      "seed": -1,
      "image": "https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png",
      "width": 768,
      "height": 768,
      "prompt": "a painting of a 19th century town",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg",
      "controlnet_end": 1,
      "guidance_scale": 7.5,
      "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
      "prompt_strength": 0.75,
      "sizing_strategy": "width/height",
      "controlnet_start": 0,
      "num_inference_steps": 40,
      "controlnet_conditioning_scale": 0.75
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

If you don’t have Homebrew, there are other installation options available.

Run this to download the model and run it in your local environment:

cog predict r8.im/fofr/illusions@sha256:579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8 \
  -i 'seed=-1' \
  -i 'image="https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png"' \
  -i 'width=768' \
  -i 'height=768' \
  -i 'prompt="a painting of a 19th century town"' \
  -i 'num_outputs=1' \
  -i 'control_image="https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg"' \
  -i 'controlnet_end=1' \
  -i 'guidance_scale=7.5' \
  -i 'negative_prompt="ugly, disfigured, low quality, blurry, nsfw"' \
  -i 'prompt_strength=0.75' \
  -i 'sizing_strategy="width/height"' \
  -i 'controlnet_start=0' \
  -i 'num_inference_steps=40' \
  -i 'controlnet_conditioning_scale=0.75'

To learn more, take a look at the Cog documentation.

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/fofr/illusions@sha256:579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": -1,
      "image": "https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png",
      "width": 768,
      "height": 768,
      "prompt": "a painting of a 19th century town",
      "num_outputs": 1,
      "control_image": "https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg",
      "controlnet_end": 1,
      "guidance_scale": 7.5,
      "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
      "prompt_strength": 0.75,
      "sizing_strategy": "width/height",
      "controlnet_start": 0,
      "num_inference_steps": 40,
      "controlnet_conditioning_scale": 0.75
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-11-28T11:32:46.230072Z",
  "created_at": "2024-11-28T11:32:43.659000Z",
  "data_removed": false,
  "error": null,
  "id": "tjnxcd3t1drm80ckea5t26p0g4",
  "input": {
    "seed": -1,
    "image": "https://replicate.delivery/pbxt/JouANiZNiW2mwouIgIk1VySvjL9MBmaPD6Ib8HyfW81CJzRR/out-0-44.png",
    "width": 768,
    "height": 768,
    "prompt": "a painting of a 19th century town",
    "num_outputs": 1,
    "control_image": "https://replicate.delivery/pbxt/JouAO2zaHgb66YVChJagSYz0LcGqv3QgG4BS71mioFbBHWTZ/spiral_black_transparent-2513050263.jpg",
    "controlnet_end": 1,
    "guidance_scale": 7.5,
    "negative_prompt": "ugly, disfigured, low quality, blurry, nsfw",
    "prompt_strength": 0.75,
    "sizing_strategy": "width/height",
    "controlnet_start": 0,
    "num_inference_steps": 40,
    "controlnet_conditioning_scale": 0.75
  },
  "logs": "Using seed: 3311311052\nimg2img mode\nUsing given dimensions\n  0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:00<00:03,  8.15it/s]\n 10%|█         | 3/30 [00:00<00:02, 12.79it/s]\n 17%|█▋        | 5/30 [00:00<00:01, 14.25it/s]\n 23%|██▎       | 7/30 [00:00<00:01, 14.90it/s]\n 30%|███       | 9/30 [00:00<00:01, 15.31it/s]\n 37%|███▋      | 11/30 [00:00<00:01, 15.55it/s]\n 43%|████▎     | 13/30 [00:00<00:01, 15.67it/s]\n 50%|█████     | 15/30 [00:00<00:00, 15.76it/s]\n 57%|█████▋    | 17/30 [00:01<00:00, 15.83it/s]\n 63%|██████▎   | 19/30 [00:01<00:00, 15.86it/s]\n 70%|███████   | 21/30 [00:01<00:00, 15.88it/s]\n 77%|███████▋  | 23/30 [00:01<00:00, 15.89it/s]\n 83%|████████▎ | 25/30 [00:01<00:00, 15.90it/s]\n 90%|█████████ | 27/30 [00:01<00:00, 15.90it/s]\n 97%|█████████▋| 29/30 [00:01<00:00, 15.89it/s]\n100%|██████████| 30/30 [00:01<00:00, 15.45it/s]",
  "metrics": {
    "predict_time": 2.561864317,
    "total_time": 2.571072
  },
  "output": [
    "https://replicate.delivery/xezq/iA3MUV1f533LXqi4sHVlAerJhr03uES9OlBHAHrqaeq92ArnA/output-0.png"
  ],
  "started_at": "2024-11-28T11:32:43.668207Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-trpj5ikdlb3ons6twy3fo36eqpz4ciq4hgdk7xnfwv5kyvwjdqua",
    "get": "https://api.replicate.com/v1/predictions/tjnxcd3t1drm80ckea5t26p0g4",
    "cancel": "https://api.replicate.com/v1/predictions/tjnxcd3t1drm80ckea5t26p0g4/cancel"
  },
  "version": "579b32db82b24584c3c6155fe3ae12e8fce50ba28b575c23e8a1f5f3a5e99ed8"
}

Generated in

2.6 seconds

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