ControlNeXt SVD | Video to Video | API Documentation

fal-ai/controlnext

Animate a reference image with a driving video using ControlNeXt.

Inference

Commercial use

Schema

About

Run

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/controlnext", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/musepose/ref.png",
    video_url: "https://storage.googleapis.com/falserverless/model_tests/musepose/dance.mp4"
  },
  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/controlnext", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/musepose/ref.png",
    video_url: "https://storage.googleapis.com/falserverless/model_tests/musepose/dance.mp4"
  },
  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/controlnext", {
  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/controlnext", {
  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 reference image.

video_url string* required

URL of the input video.

height integer

Height of the output video. Default value: 1024

width integer

Width of the output video. Default value: 576

guidance_scale float

Guidance scale for the diffusion process. Default value: 3

num_inference_steps integer

Number of inference steps. Default value: 25

max_frame_num integer

Maximum number of frames to process. Default value: 240

batch_frames integer

Number of frames to process in each batch. Default value: 24

overlap integer

Number of overlapping frames between batches. Default value: 6

sample_stride integer

Stride for sampling frames from the input video. Default value: 2

decode_chunk_size integer

Chunk size for decoding frames. Default value: 2

motion_bucket_id float

Motion bucket ID for the pipeline. Default value: 127

fps integer

Frames per second for the output video. Default value: 7

controlnext_cond_scale float

Condition scale for ControlNeXt. Default value: 1

{
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/musepose/ref.png",
  "video_url": "https://storage.googleapis.com/falserverless/model_tests/musepose/dance.mp4",
  "height": 1024,
  "width": 576,
  "guidance_scale": 3,
  "num_inference_steps": 25,
  "max_frame_num": 240,
  "batch_frames": 24,
  "overlap": 6,
  "sample_stride": 2,
  "decode_chunk_size": 2,
  "motion_bucket_id": 127,
  "fps": 7,
  "controlnext_cond_scale": 1
}

Output#

video File* required

The generated video.

{
  "video": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string | null

The mime type of the file.

file_name string | null

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

file_size integer | null

The size of the file in bytes.

Related Models

fal-ai/auto-caption

video-to-video

Automatically generates text captions for your videos from the audio as per text colour/font specifications

MMAudio generates synchronized audio given video and/or text inputs. It can be combined with video models to get videos with audio.

This endpoint delivers seamlessly localized videos by generating lip-synced dubs in multiple languages, ensuring natural and immersive multilingual experiences

ControlNeXt SVD Video to Video

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#

Related Models