Live Portrait | Image to Image

fal-ai/live-portrait/image

Transfer expression from a video to a portrait.

Inference

Commercial use

Schema

LLMs

Playground API

About

Predict Pose Image

1. Calling the API#

Install the client#

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

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Please check the migration guide for more information.

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 { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/live-portrait/image", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/live-portrait/XKEmk3mAzGHUjK3qqH-UL.jpeg"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

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 { fal } from "@fal-ai/client";

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

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/live-portrait/image", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/live-portrait/XKEmk3mAzGHUjK3qqH-UL.jpeg"
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/live-portrait/image", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/live-portrait/image", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. 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 { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

image_url string* required

URL of the image to be animated

blink float

Amount to blink the eyes

eyebrow float

Amount to raise or lower eyebrows

wink float

Amount to wink

pupil_x float

Amount to move pupils horizontally

pupil_y float

Amount to move pupils vertically

aaa float

Amount to open mouth in 'aaa' shape

eee float

Amount to shape mouth in 'eee' position

woo float

Amount to shape mouth in 'woo' position

smile float

Amount to smile

rotate_pitch float

Amount to rotate the face in pitch

rotate_yaw float

Amount to rotate the face in yaw

rotate_roll float

Amount to rotate the face in roll

flag_pasteback boolean

Whether to paste-back/stitch the animated face cropping from the face-cropping space to the original image space. Default value: true

flag_do_crop boolean

Whether to crop the source portrait to the face-cropping space. Default value: true

flag_do_rot boolean

Whether to conduct the rotation when flag_do_crop is True. Default value: true

flag_lip_zero boolean

Whether to set the lip to closed state before animation. Only takes effect when flag_eye_retargeting and flag_lip_retargeting are False. Default value: true

dsize integer

Size of the output image. Default value: 512

scale float

Scaling factor for the face crop. Default value: 2.3

vx_ratio float

Horizontal offset ratio for face crop.

vy_ratio float

Vertical offset ratio for face crop. Positive values move up, negative values move down. Default value: -0.125

enable_safety_checker boolean

Whether to enable the safety checker. If enabled, the model will check if the input image contains a face before processing it. The safety checker will process the input image

output_format OutputFormatEnum

Output format Default value: "jpeg"

Possible enum values: jpeg, png

{
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/live-portrait/XKEmk3mAzGHUjK3qqH-UL.jpeg",
  "flag_pasteback": true,
  "flag_do_crop": true,
  "flag_do_rot": true,
  "flag_lip_zero": true,
  "dsize": 512,
  "scale": 2.3,
  "vy_ratio": -0.125,
  "output_format": "jpeg"
}

Output#

image Image* required

The generated image file.

{
  "image": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019,
    "width": 1024,
    "height": 1024
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

Image#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

Image#

Related Models

Live Portrait Image to Image

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

File#

Image#

Related Models