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fal-ai/depth-anything-video

Generates depth maps from video using Video Depth Anything (CVPR 2025). Produces per-frame depth estimation with temporal consistency across frames. Supports 3 model sizes (Small, Base, Large), 5 colormaps including grayscale, side-by-side comparison with the original video, and raw depth export as .npz. Useful for 3D reconstruction, video effects, compositing, and scene understanding.
Inference
Commercial use
Schema
LLMs
PlaygroundAPI

Table of contents

About

Estimate depth from video and return visualization.

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/depth-anything-video", {
  input: {
    video_url: "https://v3b.fal.media/files/b/0a8fb1c1/xNTrr7wtczzLBkJdyE5_f_7JTYCmQe.mp4"
  },
  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/depth-anything-video", {
  input: {
    video_url: "https://v3b.fal.media/files/b/0a8fb1c1/xNTrr7wtczzLBkJdyE5_f_7JTYCmQe.mp4"
  },
  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/depth-anything-video", {
  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/depth-anything-video", {
  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#

video_url string* required

URL of the input video to estimate depth for.

model ModelEnum

Depth estimation model size. VDA-Large = best quality, VDA-Small = fastest. Default value: "VDA-Large"

Possible enum values: VDA-Small, VDA-Base, VDA-Large

colormap ColormapEnum

Colormap for depth visualization. 'turbo' (recommended) shows near=warm, far=cool. 'grayscale' for raw normalized depth. 'inferno'/'magma' for perceptually uniform. 'viridis' for colorblind-friendly. Default value: "grayscale"

Possible enum values: grayscale, turbo, inferno, magma, viridis

resolution ResolutionEnum

Output resolution. 'auto' preserves input (max 1080p). Options: 'auto', '360p', '480p', '720p', '1080p'. Default value: "auto"

Possible enum values: auto, 360p, 480p, 720p, 1080p

max_frames integer

Max frames to process. None = all frames.

output_fps float

Output video FPS. None = same as input.

side_by_side boolean

Output original | depth comparison video.

include_raw_depths boolean

Export raw float32 depths as .npz file with: 'depths' [N,H,W], 'min_depth', 'max_depth', 'fps', 'model', 'shape'.

{
  "video_url": "https://v3b.fal.media/files/b/0a8fb1c1/xNTrr7wtczzLBkJdyE5_f_7JTYCmQe.mp4",
  "model": "VDA-Large",
  "colormap": "grayscale",
  "resolution": "auto"
}

Output#

video File* required

Depth visualization video (MP4, H.264).

raw_depths File

Raw depth values as .npz (if include_raw_depths=True).

{
  "video": {
    "url": "https://v3b.fal.media/files/b/0a909a72/bC4JmEhmaBIaMC4vRhhTq_depth_output.mp4"
  }
}

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.