qr2ai/outline:aba67d32 – Run with an API on Replicate

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qr2ai /outline:aba67d32

Input

prompt

string

Shift + Return to add a new line

Modern skyscraper, glass facade, urban skyline, clear day.Modern skyscraper, glass facade, urban skyline, clear day.

Input prompt

Default: "Modern skyscraper, glass facade, urban skyline, clear day."

suffix_prompt

string

Shift + Return to add a new line

Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpieceFuturistic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece

Additional prompt

Default: "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece"

negative_prompt

string

Shift + Return to add a new line

deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnaildeformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail

Input Negative Prompt

Default: "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail"

lora_input

string

Shift + Return to add a new line

Comma-separated list of LoRA models from Hugging Face or local paths. Leave empty to skip LoRA.

Default: ""

lora_scale

string

Shift + Return to add a new line

Comma-separated list of scales for each LoRA model. Must match the number of LoRAs. Leave empty if no LoRA is used.

Default: ""

width

integer

Width of output image

Default: 1024

height

integer

Height of output image

Default: 1024

generate_square

boolean

Whether generate square image, assert height == width

Default: false

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 35

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

adapter_conditioning_scale

number

(minimum: 0, maximum: 2)

Scale for adapter module

Default: 0.9

seed

integer

Random seed. Enter 0 to randomize the seed

Default: 0

sampler

string

The sampling method

Default: "Euler a"

use_canny

boolean

Whether to use canny detector for better details

Default: false

dilation_iterations

integer

(minimum: 0, maximum: 5)

Number of dilation iterations to thicken Canny edges

Default: 1

blur_kernel_size

integer

(minimum: 0, maximum: 31)

Kernel size for Gaussian blur to smooth edges before Canny detection. Set to 0 to skip blur.

Default: 11

dilation_kernel_size

integer

(minimum: 1, maximum: 31)

Kernel size for dilation to thicken edges. Adjust to make edges smoother or thicker.

Default: 3

image

file

Input image for img2img or inpaint mode

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

npx create-replicate --model=qr2ai/outline

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 qr2ai/outline using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "qr2ai/outline:aba67d326054b9ba0f813b2d507a58675c005160beba58f930348ba94712ab3d",
  {
    input: {
      seed: 0,
      width: 1024,
      height: 1024,
      prompt: "Modern skyscraper, glass facade, urban skyline, clear day.",
      sampler: "Euler a",
      use_canny: false,
      lora_input: "",
      lora_scale: "",
      num_outputs: 1,
      suffix_prompt: "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece",
      guidance_scale: 7.5,
      generate_square: false,
      negative_prompt: "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail",
      blur_kernel_size: 11,
      dilation_iterations: 1,
      num_inference_steps: 35,
      dilation_kernel_size: 3,
      adapter_conditioning_scale: 0.9
    }
  }
);
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 qr2ai/outline using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "qr2ai/outline:aba67d326054b9ba0f813b2d507a58675c005160beba58f930348ba94712ab3d",
    input={
        "seed": 0,
        "width": 1024,
        "height": 1024,
        "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.",
        "sampler": "Euler a",
        "use_canny": False,
        "lora_input": "",
        "lora_scale": "",
        "num_outputs": 1,
        "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece",
        "guidance_scale": 7.5,
        "generate_square": False,
        "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail",
        "blur_kernel_size": 11,
        "dilation_iterations": 1,
        "num_inference_steps": 35,
        "dilation_kernel_size": 3,
        "adapter_conditioning_scale": 0.9
    }
)
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 qr2ai/outline 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": "aba67d326054b9ba0f813b2d507a58675c005160beba58f930348ba94712ab3d",
    "input": {
      "seed": 0,
      "width": 1024,
      "height": 1024,
      "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.",
      "sampler": "Euler a",
      "use_canny": false,
      "lora_input": "",
      "lora_scale": "",
      "num_outputs": 1,
      "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece",
      "guidance_scale": 7.5,
      "generate_square": false,
      "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail",
      "blur_kernel_size": 11,
      "dilation_iterations": 1,
      "num_inference_steps": 35,
      "dilation_kernel_size": 3,
      "adapter_conditioning_scale": 0.9
    }
  }' \
  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/qr2ai/outline@sha256:aba67d326054b9ba0f813b2d507a58675c005160beba58f930348ba94712ab3d \
  -i 'seed=0' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt="Modern skyscraper, glass facade, urban skyline, clear day."' \
  -i 'sampler="Euler a"' \
  -i 'use_canny=false' \
  -i 'lora_input=""' \
  -i 'lora_scale=""' \
  -i 'num_outputs=1' \
  -i 'suffix_prompt="Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece"' \
  -i 'guidance_scale=7.5' \
  -i 'generate_square=false' \
  -i 'negative_prompt="deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail"' \
  -i 'blur_kernel_size=11' \
  -i 'dilation_iterations=1' \
  -i 'num_inference_steps=35' \
  -i 'dilation_kernel_size=3' \
  -i 'adapter_conditioning_scale=0.9'

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/qr2ai/outline@sha256:aba67d326054b9ba0f813b2d507a58675c005160beba58f930348ba94712ab3d
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 0,
      "width": 1024,
      "height": 1024,
      "prompt": "Modern skyscraper, glass facade, urban skyline, clear day.",
      "sampler": "Euler a",
      "use_canny": false,
      "lora_input": "",
      "lora_scale": "",
      "num_outputs": 1,
      "suffix_prompt": "Futuristic Concept, Cutting-Edge Technology, Historical Landmark, Timeless Aesthetics, sharp focus, 8k, uhd, file grain, masterpiece",
      "guidance_scale": 7.5,
      "generate_square": false,
      "negative_prompt": "deformed, animation, anime, cartoon, comic, cropped, out of frame, low res, draft, cgi, low quality render, thumbnail",
      "blur_kernel_size": 11,
      "dilation_iterations": 1,
      "num_inference_steps": 35,
      "dilation_kernel_size": 3,
      "adapter_conditioning_scale": 0.9
    }
  }' \
  http://localhost:5000/predictions

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

Output

No output yet! Press "Submit" to start a prediction.