Mindket

DA-2

Newversion 1 · updated

Overview

Runs the DA^2 depth model in a browser demo, the official demo of Depth Anything in Any Direction. For researchers and developers who want to try depth estimation without setting anything up.

DA-2 is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Python on your computer
  • The Python packages listed in requirements.txt
  • The huggingface_hub package, which gives you the hf command
Runs in
  • A web browser, on the Space's page at Hugging Face, with nothing to install
  • Windows, macOS or Linux with Python, from a copy you download
Start with
pip install -U huggingface_hub
hf download haodongli/DA-2 --repo-type space --local-dir DA-2
cd DA-2

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

DA-2 is the official demo of DA^2, a depth model whose title reads Depth Anything in Any Direction. The Space lets you try the model in a browser. A model and a dataset with the same name, haodongli/DA-2, are linked to it.

Who it suits

People who study or build on depth estimation and want to see this model run before reading its code.

IndustryWho uses itHow they use itExample
ResearchComputer vision researchersTry the model on their own picturesRun the demo and look at the depth result
SoftwareDevelopers adding depth to an appJudge whether the model fits their needTest a few sample inputs
EducationStudents of computer visionLearn what depth estimation producesOpen the demo and try one picture

You can skip it if you do not work with images or depth, since the Space does one job.

Where to use it

  • A web browser, on the Space's page at Hugging Face, with nothing to install
  • Windows, macOS or Linux with Python, from a copy you download
Use caseWhoWhat they get back
Try the modelResearchersA depth result for the picture you add
Check the setupDevelopersA working copy of the demo on your computer

How to set it up

  • Python on your computer
  • The Python packages listed in requirements.txt
  • The huggingface_hub package, which gives you the hf command
  1. Install the huggingface_hub package.
  2. Download the Space with the hf command.
  3. Move into the downloaded folder.
  4. Install the pinned Gradio version.
  5. Install the packages from requirements.txt.
  6. Start the app with Python.
pip install -U huggingface_hub
hf download haodongli/DA-2 --repo-type space --local-dir DA-2
cd DA-2
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py

How to use it

Open the Space's page in your browser, or start your own copy with the command below. Then add a picture in the interface and read the result it returns.

python app.py

Example

You add a picture to the demo and run it. The app returns the depth result for that picture so you can judge how the model reads the scene.

For newcomers and experts

If you are new to depth estimation, open the page and try one picture you know well. Compare what the model returns with how near or far things are in the scene.

If you know the field, the Space is a Gradio front end for the DA^2 model. The repository holds app.py, a configs folder and a da2 package. The Space is set to GPU hardware at Hugging Face, so a local copy may need a capable graphics card for speed.

  1. You add a picture in the Gradio interface
  2. app.py passes it to the DA^2 model
  3. The model estimates depth
  4. The result shows on the page

Good to know

  • License: the Space lists apache-2
  • Cost to run: none named
  • Data it reaches: the pictures you add, plus the model and files in the Space
  • Not for: anything the source does not describe, since the README is a single line about the official demo

README and files

README

DA-2

Runs the DA^2 depth model in a browser demo, the official demo of Depth Anything in Any Direction. For researchers and developers who want to try depth estimation without setting anything up.

Made by haodongli on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: DA-2 is the official demo of DA^2, a depth model whose title reads Depth Anything in Any Direction. The Space lets you try the model in a browser. A model and a dataset with the same name, haodongli/DA-2, are linked to it.

Who it suits: People who study or build on depth estimation and want to see this model run before reading its code.

Industry | Who uses it | How they use it | Example
Research | Computer vision researchers | Try the model on their own pictures | Run the demo and look at the depth result
Software | Developers adding depth to an app | Judge whether the model fits their need | Test a few sample inputs
Education | Students of computer vision | Learn what depth estimation produces | Open the demo and try one picture

You can skip it if you do not work with images or depth, since the Space does one job.

Where to use it:

  • A web browser, on the Space's page at Hugging Face, with nothing to install
  • Windows, macOS or Linux with Python, from a copy you download
Use case | Who | What they get back
Try the model | Researchers | A depth result for the picture you add
Check the setup | Developers | A working copy of the demo on your computer

How to set it up:

  • Python on your computer
  • The Python packages listed in requirements.txt
  • The huggingface_hub package, which gives you the hf command
  1. Install the huggingface_hub package.
  2. Download the Space with the hf command.
  3. Move into the downloaded folder.
  4. Install the pinned Gradio version.
  5. Install the packages from requirements.txt.
  6. Start the app with Python.
pip install -U huggingface_hub
hf download haodongli/DA-2 --repo-type space --local-dir DA-2
cd DA-2
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py

How to use it: Open the Space's page in your browser, or start your own copy with the command below. Then add a picture in the interface and read the result it returns.

python app.py

Example: You add a picture to the demo and run it. The app returns the depth result for that picture so you can judge how the model reads the scene.

For newcomers and experts: If you are new to depth estimation, open the page and try one picture you know well. Compare what the model returns with how near or far things are in the scene.

If you know the field, the Space is a Gradio front end for the DA^2 model. The repository holds app.py, a configs folder and a da2 package. The Space is set to GPU hardware at Hugging Face, so a local copy may need a capable graphics card for speed.

You add a picture in the Gradio interface
app.py passes it to the DA^2 model
The model estimates depth
The result shows on the page

Good to know:

  • License: the Space lists apache-2
  • Cost to run: none named
  • Data it reaches: the pictures you add, plus the model and files in the Space
  • Not for: anything the source does not describe, since the README is a single line about the official demo

On Hugging Face, 13 November 2026

  • Likes: 49
  • Built with: gradio
  • License: apache-2.0

Links

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.

Files
README.md  4 KB

1 file, 4 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
DA-2 This page49gradioapache-2.0
Open VLM LeaderboardShares gradio1,034gradioapache-2.0
Face SwapShares gradio808gradiocc-by-nc-sa-4.0
TTS Spaces ArenaShares gradio493gradiozlib
Depth Anything 3Shares gradio490gradiocc-by-nc-4.0
BLIPShares gradio431gradiobsd-3-clause
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

Reviews

No ratings yet

Write a review

No reviews yet.

More from Mindket

See all from Mindket

upscaler

uwg · Kit

Holds a set of image upscaling models gathered from the OpenModelDB community, for people who want to enlarge low-resolution pictures with AI on their own comp…

New

Pixel Art XL

nerijs · Kit

A pixel art style add-on for Stable Diffusion XL that turns text prompts into pixel-style images, with an optional LCM LoRA for faster runs. For game makers, d…

New

VibeVoice-1.5B

microsoft · Kit

Turns written conversations into spoken audio with up to four speakers and about 90 minutes of speech, an open Microsoft text-to-speech model for research on p…

New

Similar in Research

See all in Research

EarthJev

dBenf · Kit

Answers typed questions about satellite image patches from all 12 Sentinel-2 bands, returning a probability for each option without writing text. A Qwen3.5-0.8…

New

getting-over-it-rl-jax

zimmerk4 · Kit

Plays the full game Getting Over It from the bottom to the end with a small trained policy network that learned inside a JAX physics simulator. For reinforceme…

New

ReFoCo

yuji-nozawa · Kit

Pretrained vision transformer checkpoints in three sizes from a research paper on training attention heads to focus on image regions. For researchers who extra…

New