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fal-ai/reconviagen-0.5

Generate 3D models from one or more images using ReconViaGen 0.5
Inference
Commercial use
Schema
LLMs
PlaygroundAPI

Table of contents

About

Generate a 3D model from one or more images.

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/reconviagen-0.5", {
  input: {
    image_urls: ["https://storage.googleapis.com/falserverless/model_tests/video_models/front.png", "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png", "https://storage.googleapis.com/falserverless/model_tests/video_models/left.png"]
  },
  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/reconviagen-0.5", {
  input: {
    image_urls: ["https://storage.googleapis.com/falserverless/model_tests/video_models/front.png", "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png", "https://storage.googleapis.com/falserverless/model_tests/video_models/left.png"]
  },
  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/reconviagen-0.5", {
  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/reconviagen-0.5", {
  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#

seed integer

Random seed for reproducibility

resolution ResolutionEnum

Output resolution; higher is slower but more detailed Default value: "1024"

Possible enum values: 512, 1024, 1536

ss_source SparseStructureSourceEnum

Sparse structure source. 'mesh' gives best quality, 'direct' is fastest, 'mvtrellis2' uses multi-view TRELLIS.2. Default value: "mesh"

Possible enum values: direct, mesh, mvtrellis2

ss_guidance_strength float

How closely the initial 3D structure follows the input. Higher values produce more faithful but potentially noisier results. Default value: 7.5

ss_guidance_rescale float

Dampens artifacts from high guidance in stage 1. Default value: 0.7

ss_sampling_steps integer

Number of denoising steps for the initial structure. Default value: 12

ss_rescale_t float

Controls noise schedule sharpness for structure generation. Default value: 5

slat_guidance_strength float

Guidance strength for SLat stage (only used when ss_source='mesh'). Default value: 7.5

slat_guidance_rescale float

Guidance rescale for SLat stage (only used when ss_source='mesh'). Default value: 0.5

slat_sampling_steps integer

Sampling steps for SLat stage (only used when ss_source='mesh'). Default value: 12

slat_rescale_t float

Rescale T for SLat stage (only used when ss_source='mesh'). Default value: 3

shape_slat_guidance_strength float

How closely the detailed geometry follows the input. Default value: 7.5

shape_slat_guidance_rescale float

Dampens artifacts from high guidance in the shape stage. Default value: 0.5

shape_slat_sampling_steps integer

Number of denoising steps for shape refinement. Default value: 12

shape_slat_rescale_t float

Controls noise schedule sharpness for shape refinement. Default value: 3

tex_slat_guidance_strength float

How closely the texture follows the input colors. Default value: 1

tex_slat_guidance_rescale float

Dampens artifacts from high guidance in the texture stage.

tex_slat_sampling_steps integer

Number of denoising steps for texture generation. Default value: 12

tex_slat_rescale_t float

Controls noise schedule sharpness for texture generation. Default value: 3

decimation_target integer

Target number of vertices in the final mesh. Default value: 500000

texture_size TextureSizeEnum

Resolution of the texture image baked onto the mesh. Default value: "2048"

Possible enum values: 1024, 2048, 4096

image_urls list<string>* required

One or more views of the same object. Multiple views yield higher-quality 3D reconstruction.

multi_image_strategy MultiImageStrategyEnum

Strategy for combining multi-view conditioning. 'adaptive_guidance_weight' works best in most cases. Only used when more than one image is provided. Default value: "adaptive_guidance_weight"

Possible enum values: average_right, weighted_average, sequential, average, adaptive_guidance_weight, fixed_guidance_rescale

{
  "resolution": 1024,
  "ss_source": "mesh",
  "ss_guidance_strength": 7.5,
  "ss_guidance_rescale": 0.7,
  "ss_sampling_steps": 12,
  "ss_rescale_t": 5,
  "slat_guidance_strength": 7.5,
  "slat_guidance_rescale": 0.5,
  "slat_sampling_steps": 12,
  "slat_rescale_t": 3,
  "shape_slat_guidance_strength": 7.5,
  "shape_slat_guidance_rescale": 0.5,
  "shape_slat_sampling_steps": 12,
  "shape_slat_rescale_t": 3,
  "tex_slat_guidance_strength": 1,
  "tex_slat_sampling_steps": 12,
  "tex_slat_rescale_t": 3,
  "decimation_target": 500000,
  "texture_size": 2048,
  "image_urls": [
    "https://storage.googleapis.com/falserverless/model_tests/video_models/front.png",
    "https://storage.googleapis.com/falserverless/model_tests/video_models/back.png",
    "https://storage.googleapis.com/falserverless/model_tests/video_models/left.png"
  ],
  "multi_image_strategy": "adaptive_guidance_weight"
}

Output#

model_glb File* required

Generated 3D GLB file with PBR materials

seed integer* required

Seed used for generation.

{
  "model_glb": {
    "url": "https://v3b.fal.media/files/b/0a951b66/qp0eJhESNtvkFHVd8q9M2_reconviagen_6a9848519c2d43a69dcce8c00a8803b2.glb"
  }
}

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.

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