usamaehsan/instant-id-x-juggernaut:926e65e2 – Run with an API on Replicate

Version

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usamaehsan /instant-id-x-juggernaut:926e65e2

Input

prompt

string

Shift + Return to add a new line

analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best qualityanalog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality

Input prompt

Default: "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality"

image

file

Input image

image2

file

face image2

pose_image

file

pose image

negative_prompt

string

Shift + Return to add a new line

Input Negative Prompt

Default: ""

width

integer

(minimum: 0, maximum: 2048)

Width for face detection

Default: 640

height

integer

(minimum: 0, maximum: 2048)

Height for face detection

Default: 640

scheduler

string

Choose a scheduler.

Default: "UniPCMultistep"

min_side

integer

(minimum: 0, maximum: 2048)

min resolution // if resize image is on

Default: 1024

max_side

integer

(minimum: 0, maximum: 2048)

min resolution // if resize image is on

Default: 1280

resize_image

boolean

Default: true

enhance_face_region

boolean

Default: true

use_controlnet_pose

boolean

Default: true

use_gfpgan

boolean

Default: true

ip_adapter_scale

number

(minimum: 0, maximum: 5)

Scale for IP adapter

Default: 0.8

controlnet_conditioning_scale

number

(minimum: 0, maximum: 5)

Scale for ControlNet conditioning

Default: 0.8

pose_controlnet_conditioning_scale

number

(minimum: 0, maximum: 5)

Scale for ControlNet conditioning

Default: 0.8

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: 5

micro_detail_lora_weight

number

disabled on 0

Default: 0

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

npx create-replicate --model=usamaehsan/instant-id-x-juggernaut

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 usamaehsan/instant-id-x-juggernaut using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "usamaehsan/instant-id-x-juggernaut:926e65e2dd874dc93a9f403fe20495917fff5ad8277e780c73971238b8a1d21c",
  {
    input: {
      width: 640,
      height: 640,
      prompt: "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
      max_side: 1280,
      min_side: 1024,
      scheduler: "UniPCMultistep",
      use_gfpgan: true,
      resize_image: true,
      guidance_scale: 5,
      negative_prompt: "",
      ip_adapter_scale: 0.8,
      enhance_face_region: true,
      num_inference_steps: 30,
      use_controlnet_pose: true,
      micro_detail_lora_weight: 0,
      controlnet_conditioning_scale: 0.8,
      pose_controlnet_conditioning_scale: 0.8
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", 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 usamaehsan/instant-id-x-juggernaut using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "usamaehsan/instant-id-x-juggernaut:926e65e2dd874dc93a9f403fe20495917fff5ad8277e780c73971238b8a1d21c",
    input={
        "width": 640,
        "height": 640,
        "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
        "max_side": 1280,
        "min_side": 1024,
        "scheduler": "UniPCMultistep",
        "use_gfpgan": True,
        "resize_image": True,
        "guidance_scale": 5,
        "negative_prompt": "",
        "ip_adapter_scale": 0.8,
        "enhance_face_region": True,
        "num_inference_steps": 30,
        "use_controlnet_pose": True,
        "micro_detail_lora_weight": 0,
        "controlnet_conditioning_scale": 0.8,
        "pose_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 usamaehsan/instant-id-x-juggernaut 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": "usamaehsan/instant-id-x-juggernaut:926e65e2dd874dc93a9f403fe20495917fff5ad8277e780c73971238b8a1d21c",
    "input": {
      "width": 640,
      "height": 640,
      "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality",
      "max_side": 1280,
      "min_side": 1024,
      "scheduler": "UniPCMultistep",
      "use_gfpgan": true,
      "resize_image": true,
      "guidance_scale": 5,
      "negative_prompt": "",
      "ip_adapter_scale": 0.8,
      "enhance_face_region": true,
      "num_inference_steps": 30,
      "use_controlnet_pose": true,
      "micro_detail_lora_weight": 0,
      "controlnet_conditioning_scale": 0.8,
      "pose_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.