Hyper3d | Image to 3D

fal-ai/hyper3d/rodin/v2

Rodin by Hyper3D generates realistic and production ready 3D models from text or images.

Inference

Commercial use

Schema

LLMs

Playground API

About

Image-to-3D generation using Rodin Gen-2

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/hyper3d/rodin/v2", {
  input: {},
  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/hyper3d/rodin/v2", {
  input: {},
  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/hyper3d/rodin/v2", {
  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/hyper3d/rodin/v2", {
  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#

prompt string

A textual prompt to guide model generation. Optional for Image-to-3D mode - if empty, AI will generate a prompt based on your images. Default value: ""

input_image_urls list<string>

URL of images to use while generating the 3D model. Required for Image-to-3D mode. Up to 5 images allowed.

use_original_alpha boolean

When enabled, preserves the transparency channel from input images during 3D generation.

seed integer

Seed value for randomization, ranging from 0 to 65535. Optional.

geometry_file_format GeometryFileFormatEnum

Format of the geometry file. Possible values: glb, usdz, fbx, obj, stl. Default is glb. Default value: "glb"

Possible enum values: glb, usdz, fbx, obj, stl

material MaterialEnum

Material type. PBR: Physically-based materials with realistic lighting. Shaded: Simple materials with baked lighting. All: Both types included. Default value: "All"

Possible enum values: PBR, Shaded, All

quality_mesh_option QualityMeshOptionEnum

Combined quality and mesh type selection. Quad = smooth surfaces, Triangle = detailed geometry. Default value: "500K Triangle"

Possible enum values: 4K Quad, 8K Quad, 18K Quad, 50K Quad, 2K Triangle, 20K Triangle, 150K Triangle, 500K Triangle

TAPose boolean

Generate characters in T-pose or A-pose format, making them easier to rig and animate in 3D software.

bbox_condition list<integer>

An array that specifies the bounding box dimensions [width, height, length].

preview_render boolean

Generate a preview render image of the 3D model along with the model files.

{
  "prompt": "A futuristic robot with sleek metallic design.",
  "input_image_urls": [
    "https://v3.fal.media/files/panda/l7mQrG8plbB42lBNqVjm0_image.png",
    "https://v3b.fal.media/files/b/kangaroo/scq50Bf1PB2NZOW8szphV_image.png",
    "https://v3.fal.media/files/penguin/X21qtlVMazAtljzRCJD2__image.png"
  ],
  "geometry_file_format": "glb",
  "material": "All",
  "quality_mesh_option": "500K Triangle"
}

Output#

model_mesh File* required

Generated 3D object file.

seed integer* required

Seed value used for generation.

textures list<Image>* required

Generated textures for the 3D object.

{
  "model_mesh": {
    "url": "https://storage.googleapis.com/falserverless/model_tests/video_models/base_basic_shaded.glb"
  },
  "textures": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019,
      "width": 1024,
      "height": 1024
    }
  ]
}

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.

file_data string

File data

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.

file_data string

File data

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

Hyper3d Image to 3D

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#

Image#