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Segment Image
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"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/sam2/image", {
input: {
image_url: "https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/notebooks/images/truck.jpg"
},
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);This model has a real-time mode via WebSockets, supported by fal.realtime.connect.
import { fal } from "@fal-ai/client";
const connection = fal.realtime.connect("fal-ai/sam2/image", {
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({
image_url: "https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/notebooks/images/truck.jpg"
});The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_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.
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/sam2/image", {
input: {
image_url: "https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/notebooks/images/truck.jpg"
},
webhookUrl: "https://optional.webhook.url/for/results",
});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/sam2/image", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});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/sam2/image", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);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.
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.
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.
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);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.
image_url string* requiredURL of the image to be segmented
List of prompts to segment the image
Coordinates for boxes
apply_mask booleanApply the mask on the image.
sync_mode booleanIf True, the media will be returned as a data URI and the output data won't be available in the request history.
output_format OutputFormatEnumThe format of the generated image. Default value: "png"
Possible enum values: jpeg, png, webp
{
"image_url": "https://raw.githubusercontent.com/facebookresearch/segment-anything-2/main/notebooks/images/truck.jpg",
"prompts": [
{
"y": 375,
"label": 1,
"x": 500
}
],
"box_prompts": [
{
"x_max": 700,
"y_max": 875,
"x_min": 425,
"y_min": 600
}
],
"output_format": "png"
}Segmented image.
{
"image": {
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019,
"width": 1024,
"height": 1024
}
}url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
width integerThe width of the image in pixels.
height integerThe height of the image in pixels.
x integerX Coordinate of the prompt Default value: 305
y integerY Coordinate of the prompt Default value: 350
label LabelEnumLabel of the prompt. 1 for foreground, 0 for background Default value: "1"
Possible enum values: 0, 1
frame_index integerThe frame index to interact with.
x_min integerX Min Coordinate of the box
y_min integerY Min Coordinate of the box
x_max integerX Max Coordinate of the prompt
y_max integerY Max Coordinate of the prompt
frame_index integerThe frame index to interact with.