Loading API documentation
Estimate monocular geometry (affine-invariant point map, depth, optional surface normals, camera intrinsics/FoV) from a single image using MoGe-2, and optionally export a textured mesh (.glb) and colored point cloud (.ply).
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientSet 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("microsoft/moge-2", {
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);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"
});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("microsoft/moge-2", {
input: {},
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("microsoft/moge-2", {
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("microsoft/moge-2", {
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);Read more about file handling in our file upload guide.
image_url stringInput RGB image to estimate geometry (point map, depth, normals) for. Default value: "https://storage.googleapis.com/falserverless/example_inputs/dog.png"
model ModelEnumMoGe-2 checkpoint variant. '-normal' variants additionally predict surface normals. 'vitl' is the metric model without normals; the smaller 'vitb-normal'/'vits-normal' variants trade accuracy for speed. Default value: "vitl-normal"
Possible enum values: vitl-normal, vitl, vitb-normal, vits-normal
resolution_level integerProcessing resolution level (0-9). Higher values use more tokens for finer detail but slower inference. Output size always matches the input. Default value: 9
fov_x floatOptional known horizontal field of view in degrees. If provided, MoGe uses it instead of estimating the camera FoV.
apply_mask booleanIf true, mask out invalid (sky/background/uncertain) regions in the predicted point map and depth map. Default value: true
edge_threshold floatRelative threshold for removing mesh edges across depth discontinuities. Smaller values remove more edges. Default value: 0.04
export_glb booleanIf true, export a textured .glb mesh of the reconstructed geometry. Default value: true
export_ply booleanIf true, export a colored .ply point cloud of the reconstructed geometry. Default value: true
enable_safety_checker booleanEnable safety checking of the input image. Default value: true
{
"image_url": "https://storage.googleapis.com/falserverless/example_inputs/dog.png",
"model": "vitl-normal",
"resolution_level": 9,
"apply_mask": true,
"edge_threshold": 0.04,
"export_glb": true,
"export_ply": true,
"enable_safety_checker": true
}Textured .glb mesh of the reconstructed geometry (when export_glb=true).
Colored .ply point cloud of the reconstructed geometry (when export_ply=true).
Colorized depth visualization (PNG).
Colorized surface-normal visualization (PNG). Null for non-normal model variants.
Binary validity mask (PNG); white where geometry is valid.
fov_x float* requiredHorizontal field of view in degrees.
fov_y float* requiredVertical field of view in degrees.
Normalized 3x3 camera intrinsics matrix [[fx,0,cx],[0,fy,cy],[0,0,1]].
{
"depth_map": {
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019,
"width": 1024,
"height": 1024
},
"mask": {
"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.
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.