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Sam 3 Image to 3D

fal-ai/sam-3/3d-objects
SAM 3D enables precise 3D reconstruction of objects from real images, while accurately reconstructing their geometry and texture.
Inference
Commercial use

About

Reconstruct one or more 3D objects from image and masks.

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-3/3d-objects", {
  input: {
    image_url: "https://v3b.fal.media/files/b/0a8439e5/TyAmfW5w_sqRXRzWVBGsW_car.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"
});

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-3/3d-objects", {
  input: {
    image_url: "https://v3b.fal.media/files/b/0a8439e5/TyAmfW5w_sqRXRzWVBGsW_car.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/sam-3/3d-objects", {
  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-3/3d-objects", {
  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#

image_url string* required

URL of the image to reconstruct in 3D

mask_urls list<string>

Optional list of mask URLs (one per object). If not provided, use prompt/point_prompts/box_prompts to auto-segment, or entire image will be used.

prompt string

Text prompt for auto-segmentation when no masks provided (e.g., 'chair', 'lamp') Default value: "car"

point_prompts list<PointPromptBase>

Point prompts for auto-segmentation when no masks provided

box_prompts list<BoxPromptBase>

Box prompts for auto-segmentation when no masks provided

seed integer

Random seed for reproducibility

pointmap_url string

Optional URL to external pointmap/depth data (NPY or NPZ format) for improved 3D reconstruction depth estimation

{
  "image_url": "https://v3b.fal.media/files/b/0a8439e5/TyAmfW5w_sqRXRzWVBGsW_car.jpeg",
  "prompt": "car",
  "point_prompts": [],
  "box_prompts": []
}

Output#

gaussian_splat File* required

Gaussian splat file (.ply) - combined scene splat for multi-object, single splat otherwise

model_glb File

3D mesh in GLB format - combined scene for multi-object, single mesh otherwise

metadata list<SAM3DObjectMetadata>* required

Per-object metadata (rotation/translation/scale)

individual_splats list<File>

Individual Gaussian splat files per object (only for multi-object scenes)

individual_glbs list<File>

Individual GLB mesh files per object (only for multi-object scenes)

artifacts_zip File

Zip bundle containing all artifacts and metadata

{
  "gaussian_splat": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "metadata": [
    {}
  ],
  "individual_splats": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019
    }
  ],
  "individual_glbs": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019
    }
  ]
}

Other types#

SAM3DObjectMetadata#

object_index integer* required

Index of the object in the scene

scale list<list<float>>

Scale factors [sx, sy, sz]

rotation list<list<float>>

Rotation quaternion [x, y, z, w]

translation list<list<float>>

Translation [tx, ty, tz]

camera_pose list<list<float>>

Camera pose matrix

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.

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.

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.

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.

SAM3DBodyMetadata#

num_people integer* required

Number of people detected

people list<SAM3DBodyPersonMetadata>* required

Per-person metadata

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.

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.

SAM3DBodyPersonMetadata#

person_id integer* required

Index of the person in the scene

bbox list<float>* required

Bounding box [x_min, y_min, x_max, y_max]

focal_length float* required

Estimated focal length

pred_cam_t list<float>* required

Predicted camera translation [tx, ty, tz]

keypoints_2d list<list<float>>* required

2D keypoints [[x, y], ...] - 70 body keypoints

keypoints_3d list<list<float>>

3D keypoints [[x, y, z], ...] - 70 body keypoints in camera space

SAM3DBodyAlignmentInfo#

person_id integer* required

Index of the person

scale_factor float* required

Scale factor applied for alignment

translation list<float>* required

Translation [tx, ty, tz]

focal_length float* required

Focal length used

target_points_count integer* required

Number of target points for alignment

cropped_vertices_count integer* required

Number of cropped vertices

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