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fal-ai/sam-3-1/video

SAM 3.1 builds comes with Object Multiplex, a shared-memory approach for joint multi-object tracking that delivers faster speeds with larger number of objects tracked.
Inference
Commercial use
Schema
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Table of contents

About

Segment Video Simple

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

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/sam-3-1/video", {
  input: {
    video_url: "https://storage.googleapis.com/falserverless/example_inputs/birefnet-video-input.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);

Real-time via WebSockets#

This model has a real-time mode via websockets, this is supported via the fal.realtime client.

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

const connection = fal.realtime.connect("fal-ai/sam-3-1/video", {
  onResult: (result) => {
    console.log(result);
  },
  onError: (error) => {
    console.error(error);
  },
  // Fetch short-lived JWT token from your backend
  tokenProvider: async (app) => {
    const response = await fetch("/api/fal/realtime-token", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({ app }),
    });
    return response.text();
  },
  tokenExpirationSeconds: 10,
});

connection.send({
  video_url: "https://storage.googleapis.com/falserverless/example_inputs/birefnet-video-input.mp4"
});

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"
});

3. Queue#

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/sam-3-1/video", {
  input: {
    video_url: "https://storage.googleapis.com/falserverless/example_inputs/birefnet-video-input.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/sam-3-1/video", {
  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/sam-3-1/video", {
  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);

Read more about file handling in our file upload guide.

5. Schema#

Input#

video_url string* required

The URL of the video to be segmented.

prompt string

Text prompt for segmentation. Use commas to track multiple objects (e.g., 'person, cloth'). Default value: ""

point_prompts list<PointPromptBase>

List of point prompts

box_prompts list<BoxPromptBase>

List of box prompt coordinates (x_min, y_min, x_max, y_max).

apply_mask boolean

Apply the mask on the video. Default value: true

video_output_type VideoOutputTypeEnum

The output type of the generated video. Default value: "X264 (.mp4)"

Possible enum values: X264 (.mp4), VP9 (.webm)

detection_threshold float

Detection confidence threshold (0.0-1.0). Lower = more detections but less precise. Default value: 0.5

max_num_objects integer

Maximum number of objects to track in the video. Default value: 16

{
  "video_url": "https://storage.googleapis.com/falserverless/example_inputs/birefnet-video-input.mp4",
  "prompt": "person",
  "point_prompts": [],
  "box_prompts": [],
  "apply_mask": true,
  "video_output_type": "X264 (.mp4)",
  "detection_threshold": 0.5,
  "max_num_objects": 16
}

Output#

video File* required

The segmented video.

boundingbox_frames_zip File

Zip file containing per-frame bounding box overlays.

{
  "video": "https://fal.media/files/lion/gr-RSvy2e7_AWbjxAq4mJ_output.mp4"
}

Other types#

PointPrompt#

x integer

X Coordinate of the prompt

y integer

Y Coordinate of the prompt

label Enum

1 for foreground, 0 for background

Possible enum values: 0, 1

object_id integer

Optional object identifier. Prompts sharing an object id refine the same object.

frame_index integer

The frame index to interact with.

PointPromptBase#

x integer

X Coordinate of the prompt

y integer

Y Coordinate of the prompt

label Enum

1 for foreground, 0 for background

Possible enum values: 0, 1

object_id integer

Optional object identifier. Prompts sharing an object id refine the same object.

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.

MaskMetadata#

index integer* required

Index of the mask inside the model output.

score float

Score for this mask.

box list<float>

Bounding box for the mask in normalized cxcywh coordinates.

BoxPrompt#

x_min integer

X Min Coordinate of the box

y_min integer

Y Min Coordinate of the box

x_max integer

X Max Coordinate of the box

y_max integer

Y Max Coordinate of the box

object_id integer

Optional object identifier. Boxes sharing an object id refine the same object.

frame_index integer

The frame index to interact with.

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.

BoxPromptBase#

x_min integer

X Min Coordinate of the box

y_min integer

Y Min Coordinate of the box

x_max integer

X Max Coordinate of the box

y_max integer

Y Max Coordinate of the box

object_id integer

Optional object identifier. Boxes sharing an object id refine the same object.

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