InstantID

fal-ai/instantid/lcm
Inference
Research only

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/serverless-client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import * as fal from "@fal-ai/serverless-client";

const result = await fal.subscribe("fal-ai/instantid/lcm", {
  input: {
    face_image_url: "https://storage.googleapis.com/falserverless/model_tests/instantid/post_malone.jpg",
    prompt: "man"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import * as fal from "@fal-ai/serverless-client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

3. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import * as fal from "@fal-ai/serverless-client";

// Upload a file (you can get a file reference from an input element or a drag-and-drop event)
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

// Use the URL in your request
const result = await fal.subscribe("fal-ai/instantid/lcm", { image_url: url });

Read more about file handling in our file upload guide.

4. Schema#

Input#

face_image_url*string

The image of the person you want to generate.

prompt*string

The prompt to use for generating the image. Be as descriptive as possible for best results.

styleStyleEnum

Default value: "Headshot"

Possible values: "(No style)", "Headshot", "Spring Festival", "Watercolor", "Film Noir", "Neon", "Jungle", "Mars", "Vibrant Color", "Snow", "Line art"

negative_promptstring

The negative prompt to use.Use it to address details that you don't want in the image. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). Default value: ""

num_inference_stepsinteger

Increasing the amount of steps tells Stable Diffusion that it should take more steps to generate your final result which can increase the amount of detail in your image. If using LCM scheduler, use a value in the range of 1 to 12 for best results. Default value: 5

guidance_scalefloat

The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. If using LCM scheduler, use a value in the range of 0.1 to 2.0 for best results. Default value: 1.5

controlnet_selectionControlnetSelectionEnum

Type of the ControlNet. If not provided, ControlNets will not be used. Default value: "canny"

Possible values: "pose", "canny", "depth"

controlnet_conditioning_scalefloat

The scale of the controlnet conditioning. Default value: 0.4

ip_adapter_scalefloat

The scale of the IP adapter (increase to improve details). Default value: 0.7

identity_controlnet_conditioning_scalefloat

The scale of the controlnet conditioning (increase to preserve identity). This only affects the identity controlnet. Default value: 0.7

enhance_face_regionboolean

Whether to enhance the face region or not. Default value: true

seedinteger

The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.

model_namestring

The link of the model to use for generating the image. If not provided, the default model will be used.

{
  "face_image_url": "https://storage.googleapis.com/falserverless/model_tests/instantid/post_malone.jpg",
  "prompt": "man",
  "style": "Headshot",
  "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
  "num_inference_steps": 5,
  "guidance_scale": 1.5,
  "controlnet_selection": "canny",
  "controlnet_conditioning_scale": 0.4,
  "ip_adapter_scale": 0.7,
  "identity_controlnet_conditioning_scale": 0.7,
  "enhance_face_region": true,
  "seed": 42
}

Output#

image*Image

The generated image

seed*integer

The seed used to generate the image

{
  "image": {
    "height": 1280,
    "content_type": "image/png",
    "url": "https://storage.googleapis.com/falserverless/model_tests/instantid/post_malone_after_canny.png",
    "width": 960
  }
}