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Hunyuan Part 3D to 3D

fal-ai/hunyuan-part
Use the capabilities of hunyuan part to generate point clouds from your 3D files.
Inference
Commercial use
PlaygroundAPI

About

Run

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/hunyuan-part", {
  input: {
    model_file_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/base_basic_shaded.glb"
  },
  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/hunyuan-part", {
  input: {
    model_file_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/base_basic_shaded.glb"
  },
  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/hunyuan-part", {
  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/hunyuan-part", {
  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#

model_file_url string* required

URL of the 3D model file (.glb or .obj) to process for segmentation.

point_prompt_x float

X coordinate of the point prompt for segmentation (normalized space -1 to 1).

point_prompt_y float

Y coordinate of the point prompt for segmentation (normalized space -1 to 1).

point_prompt_z float

Z coordinate of the point prompt for segmentation (normalized space -1 to 1).

point_num integer

Number of points to sample from the mesh. Default value: 100000

use_normal boolean

Whether to use normal information for segmentation. Default value: true

noise_std float

Standard deviation of noise to add to sampled points.

seed integer

The same seed and input will produce the same segmentation results.

{
  "model_file_url": "https://storage.googleapis.com/falserverless/model_tests/video_models/base_basic_shaded.glb",
  "point_num": 100000,
  "use_normal": true
}

Output#

segmented_mesh File* required

Segmented 3D mesh with mask applied.

mask_1_mesh File* required

Mesh showing segmentation mask 1.

mask_2_mesh File* required

Mesh showing segmentation mask 2.

mask_3_mesh File* required

Mesh showing segmentation mask 3.

best_mask_index integer* required

Index of the best mask (1, 2, or 3) based on IoU score.

iou_scores list<float>* required

IoU scores for each of the three masks.

seed integer* required

Seed value used for generation.

{
  "segmented_mesh": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "mask_1_mesh": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "mask_2_mesh": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "mask_3_mesh": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  }
}

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