arunarupa/instantid-image-size-increase – Run with an API on Replicate

arunarupa / instantid-image-size-increase

Same instant model multricontrolnet that already existed just with the 1024px limit removed when using a reference image

Cold

Public
738 runs
L40S

Run with an API

Playground API Examples README Versions

Input

image

*file

Input face image

pose_image

file

(Optional) reference pose image

prompt

string

Shift + Return to add a new line

Input prompt

Default: "a person"

negative_prompt

string

Shift + Return to add a new line

Input Negative Prompt

Default: ""

sdxl_weights

string

Pick which base weights you want to use

Default: "stable-diffusion-xl-base-1.0"

scheduler

string

Scheduler

Default: "EulerDiscreteScheduler"

max_side_input

integer

Height of the output if reference picture is used

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 30

guidance_scale

number

(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

ip_adapter_scale

number

(minimum: 0, maximum: 1.5)

Scale for image adapter strength (for detail)

Default: 0.8

controlnet_conditioning_scale

number

(minimum: 0, maximum: 1.5)

Scale for IdentityNet strength (for fidelity)

Default: 0.8

enable_pose_controlnet

boolean

Enable Openpose ControlNet, overrides strength if set to false

Default: true

pose_strength

number

(minimum: 0, maximum: 1)

Openpose ControlNet strength, effective only if `enable_pose_controlnet` is true

Default: 0.4

enable_canny_controlnet

boolean

Enable Canny ControlNet, overrides strength if set to false

Default: false

canny_strength

number

(minimum: 0, maximum: 1)

Canny ControlNet strength, effective only if `enable_canny_controlnet` is true

Default: 0.3

enable_depth_controlnet

boolean

Enable Depth ControlNet, overrides strength if set to false

Default: false

depth_strength

number

(minimum: 0, maximum: 1)

Depth ControlNet strength, effective only if `enable_depth_controlnet` is true

Default: 0.5

enable_lcm

boolean

Enable Fast Inference with LCM (Latent Consistency Models) - speeds up inference steps, trade-off is the quality of the generated image. Performs better with close-up portrait face images

Default: false

lcm_num_inference_steps

integer

(minimum: 1, maximum: 10)

Only used when `enable_lcm` is set to True, Number of denoising steps when using LCM

Default: 5

lcm_guidance_scale

number

(minimum: 1, maximum: 20)

Only used when `enable_lcm` is set to True, Scale for classifier-free guidance when using LCM

Default: 1.5

enhance_nonface_region

boolean

Enhance non-face region

Default: true

output_format

string

Format of the output images

Default: "webp"

output_quality

integer

(minimum: 0, maximum: 100)

Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.

Default: 80

seed

integer

Random seed. Leave blank to randomize the seed

num_outputs

integer

(minimum: 1, maximum: 8)

Number of images to output

Default: 1

disable_safety_checker

boolean

Disable safety checker for generated images

Default: false

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

npx create-replicate --model=arunarupa/instantid-image-size-increase

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 arunarupa/instantid-image-size-increase using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "arunarupa/instantid-image-size-increase:8fc16a3542294cb4dad317f2663c2c1ea28df86c35b1dd6b5d6af4cbf2bd70a0",
  {
    input: {
      prompt: "a person",
      scheduler: "EulerDiscreteScheduler",
      enable_lcm: false,
      num_outputs: 1,
      sdxl_weights: "stable-diffusion-xl-base-1.0",
      output_format: "webp",
      pose_strength: 0.4,
      canny_strength: 0.3,
      depth_strength: 0.5,
      guidance_scale: 7.5,
      output_quality: 80,
      negative_prompt: "",
      ip_adapter_scale: 0.8,
      lcm_guidance_scale: 1.5,
      num_inference_steps: 30,
      enable_pose_controlnet: true,
      enhance_nonface_region: true,
      enable_canny_controlnet: false,
      enable_depth_controlnet: false,
      lcm_num_inference_steps: 5,
      controlnet_conditioning_scale: 0.8
    }
  }
);

// 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 arunarupa/instantid-image-size-increase using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "arunarupa/instantid-image-size-increase:8fc16a3542294cb4dad317f2663c2c1ea28df86c35b1dd6b5d6af4cbf2bd70a0",
    input={
        "prompt": "a person",
        "scheduler": "EulerDiscreteScheduler",
        "enable_lcm": False,
        "num_outputs": 1,
        "sdxl_weights": "stable-diffusion-xl-base-1.0",
        "output_format": "webp",
        "pose_strength": 0.4,
        "canny_strength": 0.3,
        "depth_strength": 0.5,
        "guidance_scale": 7.5,
        "output_quality": 80,
        "negative_prompt": "",
        "ip_adapter_scale": 0.8,
        "lcm_guidance_scale": 1.5,
        "num_inference_steps": 30,
        "enable_pose_controlnet": True,
        "enhance_nonface_region": True,
        "enable_canny_controlnet": False,
        "enable_depth_controlnet": False,
        "lcm_num_inference_steps": 5,
        "controlnet_conditioning_scale": 0.8
    }
)
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 arunarupa/instantid-image-size-increase 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": "8fc16a3542294cb4dad317f2663c2c1ea28df86c35b1dd6b5d6af4cbf2bd70a0",
    "input": {
      "prompt": "a person",
      "scheduler": "EulerDiscreteScheduler",
      "enable_lcm": false,
      "num_outputs": 1,
      "sdxl_weights": "stable-diffusion-xl-base-1.0",
      "output_format": "webp",
      "pose_strength": 0.4,
      "canny_strength": 0.3,
      "depth_strength": 0.5,
      "guidance_scale": 7.5,
      "output_quality": 80,
      "negative_prompt": "",
      "ip_adapter_scale": 0.8,
      "lcm_guidance_scale": 1.5,
      "num_inference_steps": 30,
      "enable_pose_controlnet": true,
      "enhance_nonface_region": true,
      "enable_canny_controlnet": false,
      "enable_depth_controlnet": false,
      "lcm_num_inference_steps": 5,
      "controlnet_conditioning_scale": 0.8
    }
  }' \
  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.

Run time and cost

This model costs approximately $0.18 to run on Replicate, or 5 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 4 minutes. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.