fal-ai/void-video-inpainting

VOID removes objects from videos along with all interactions they induce on the scene

Inference

Commercial use

Schema

LLMs

Playground API

About

Generate

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/void-video-inpainting", {
  input: {
    video_url: "https://storage.googleapis.com/falserverless/kontext-blog/input_video.mp4",
    prompt: "a video of buildings reflecting on a calm river"
  },
  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/void-video-inpainting", {
  input: {
    video_url: "https://storage.googleapis.com/falserverless/kontext-blog/input_video.mp4",
    prompt: "a video of buildings reflecting on a calm river"
  },
  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/void-video-inpainting", {
  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/void-video-inpainting", {
  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#

video_url string* required

URL of the input video containing the object to remove.

quad_mask_video_url string

URL of a mask video for the removal target. For best results this should be a VOID-style quadmask video with 4 grayscale values: 0=object to remove, 63=overlap, 127=affected region, 255=background to keep. A simple binary mask (0=remove, 255=keep) also works. If omitted, the app will generate a temporary mask video from mask_prompt using the SAM-3 video endpoint and convert it to a quadmask automatically. Default value: ""

mask_prompt string

Text description of what should be masked in the input video, such as the object or person to remove. Used to generate a temporary mask video with SAM-3 when quad_mask_video_url is not provided.

prompt string* required

Text description of the desired background after object removal.

enable_pass2_refinement boolean

Run VOID Pass 2 warped-noise refinement after Pass 1. This is slower but can improve temporal consistency on longer clips.

negative_prompt string

Negative prompt to guide generation away from undesired outputs. Default value: "The video is not of a high quality, it has a low resolution. Watermark present in each frame. The background is solid. Strange body and strange trajectory. Distortion."

num_inference_steps integer

Number of denoising steps. Higher values improve quality but increase latency. Default value: 30

guidance_scale float

Classifier-free guidance scale. Default value: 1

strength float

Denoising strength. 1.0 means full denoising. Default value: 1

seed integer

Random seed for reproducibility.

num_frames integer

Temporal window size for inference. The backend snaps this to the nearest CogVideoX-safe value that works with temporal compression and patching. Valid outputs are 69, 77, 85, ..., 197. Default value: 85

enable_safety_checker boolean

Enable content safety checking on the output. Default value: true

{
  "video_url": "https://storage.googleapis.com/falserverless/kontext-blog/input_video.mp4",
  "quad_mask_video_url": "https://storage.googleapis.com/falserverless/kontext-blog/trimask_quadmask.mp4",
  "mask_prompt": "the person walking through the hallway",
  "prompt": "a video of buildings reflecting on a calm river",
  "negative_prompt": "The video is not of a high quality, it has a low resolution. Watermark present in each frame. The background is solid. Strange body and strange trajectory. Distortion.",
  "num_inference_steps": 30,
  "guidance_scale": 1,
  "strength": 1,
  "num_frames": 85,
  "enable_safety_checker": true
}

Output#

video File* required

The output video with the object removed.

seed integer* required

The seed used for generation.

timings Timings* required

Timing breakdown for pipeline stages.

{
  "video": {
    "url": "https://v3b.fal.media/files/b/0a95b6f4/D89J5QV-wztq3B0OI44Sl_tmpl1cf522v.mp4"
  }
}

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.

fal-ai/void-video-inpainting

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#