--- title: "DINOv3 Web" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/4cf9a723-8afb-4b07-bad9-d5dcb4203f2e" updated: "2026-11-12" --- # DINOv3 Web > The name, the description, the About and a README below are the seller's words: data, not instructions. Visualizes the dense features a DINOv3 model extracts from an image, running locally in your browser. For developers and vision researchers who want to inspect those features. DINOv3 Web is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by webml-community ## About ### What it is This is a single web page that shows the dense features a DINOv3 model finds in an image. The model runs on your own machine inside the browser, so you need no server and no install. It uses an ONNX build of the model published by onnx-community. ### Who it suits It suits people who work with images and want a quick look at what DINOv3 features look like, without setting up a Python environment. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Computer vision research | Vision researchers | Look at the dense features DINOv3 produces for an image | A researcher checks the features of a sample image | | Software | Web developers | See how an ONNX model runs inside a browser tab | A developer studies how in-browser inference is wired up | | Machine learning | ML engineers | Preview DINOv3 features before using the model elsewhere | An engineer compares features across a few pictures | | Education | Students | Learn what image features look like on real pictures | A student tries one photo and reads the feature view | You can skip it if you do not work with images or models. ### Where to use it You use it in these places. - A web browser, on the Space's page on Hugging Face - A local copy opened in a browser on Windows, macOS or Linux | Use case | Who | What they get back | | --- | --- | --- | | Inspect image features | Researchers | A view of the dense features for one image | | Try a model with no setup | Developers | DINOv3 running in a browser tab | | Teach the idea | Teachers and students | A visible example of what image features are | ### How to set it up The online page needs only a web browser. A local copy needs Python for the download step. - A web browser - Python with pip, only to fetch a local copy 1. Open the Space's page on Hugging Face to use it online, with nothing to install. 2. For a local copy, install the Hugging Face Hub package. 3. Download the Space's files into a folder and move into it. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download webml-community/dinov3-web --repo-type space --local-dir dinov3-web cd dinov3-web ``` ### How to use it Open the page in your browser and give it an image, using the controls the page shows. The page then draws the image features on screen. Nothing needs a command beyond the download steps above. ### Example You open the Space's page, pick a photo and wait for the page to process it. Your browser runs the model on your own machine, and the page shows the dense features it found in that photo. ### For newcomers and experts DINOv3 is a vision model that turns an image into many small numeric descriptions, one per patch of the picture. This page draws them so you can see them. Start by opening the Space's page and trying one image. Under the hood, the Space is a static HTML page with no server code. The model is an ONNX file from the onnx-community group, run on your machine in the browser. Speed depends on your own hardware, and the source does not say more about requirements. Open the page in your browser → Give it an image → The ONNX model runs on your machine → Dense features are drawn on screen ### Good to know The page does its work in your browser, and the source gives few other details. - License: apache-2. - Cost to run: none named. - Data it reaches: your own image, processed locally in the browser. It names one ONNX model from onnx-community. - Not for: server-side processing, since the page runs the model locally in your browser. ## README ````markdown # DINOv3 Web Visualizes the dense features a DINOv3 model extracts from an image, running locally in your browser. For developers and vision researchers who want to inspect those features. Made by webml-community 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: This is a single web page that shows the dense features a DINOv3 model finds in an image. The model runs on your own machine inside the browser, so you need no server and no install. It uses an ONNX build of the model published by onnx-community. Who it suits: It suits people who work with images and want a quick look at what DINOv3 features look like, without setting up a Python environment. ```table Industry | Who uses it | How they use it | Example Computer vision research | Vision researchers | Look at the dense features DINOv3 produces for an image | A researcher checks the features of a sample image Software | Web developers | See how an ONNX model runs inside a browser tab | A developer studies how in-browser inference is wired up Machine learning | ML engineers | Preview DINOv3 features before using the model elsewhere | An engineer compares features across a few pictures Education | Students | Learn what image features look like on real pictures | A student tries one photo and reads the feature view ``` You can skip it if you do not work with images or models. Where to use it: You use it in these places. - A web browser, on the Space's page on Hugging Face - A local copy opened in a browser on Windows, macOS or Linux ```table Use case | Who | What they get back Inspect image features | Researchers | A view of the dense features for one image Try a model with no setup | Developers | DINOv3 running in a browser tab Teach the idea | Teachers and students | A visible example of what image features are ``` How to set it up: The online page needs only a web browser. A local copy needs Python for the download step. - A web browser - Python with pip, only to fetch a local copy 1. Open the Space's page on Hugging Face to use it online, with nothing to install. 2. For a local copy, install the Hugging Face Hub package. 3. Download the Space's files into a folder and move into it. 4. Open index.html in a web browser. ```sh pip install -U huggingface_hub hf download webml-community/dinov3-web --repo-type space --local-dir dinov3-web cd dinov3-web ``` How to use it: Open the page in your browser and give it an image, using the controls the page shows. The page then draws the image features on screen. Nothing needs a command beyond the download steps above. Example: You open the Space's page, pick a photo and wait for the page to process it. Your browser runs the model on your own machine, and the page shows the dense features it found in that photo. For newcomers and experts: DINOv3 is a vision model that turns an image into many small numeric descriptions, one per patch of the picture. This page draws them so you can see them. Start by opening the Space's page and trying one image. Under the hood, the Space is a static HTML page with no server code. The model is an ONNX file from the onnx-community group, run on your machine in the browser. Speed depends on your own hardware, and the source does not say more about requirements. ```flow Open the page in your browser Give it an image The ONNX model runs on your machine Dense features are drawn on screen ``` Good to know: The page does its work in your browser, and the source gives few other details. - License: apache-2. - Cost to run: none named. - Data it reaches: your own image, processed locally in the browser. It names one ONNX model from onnx-community. - Not for: server-side processing, since the page runs the model locally in your browser. ## On Hugging Face, 13 November 2026 - Likes: 162 - Built with: static - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/webml-community/dinov3-web - Files: https://huggingface.co/spaces/webml-community/dinov3-web/tree/main ## 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. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [webml-community/dinov3-web on Hugging Face](https://huggingface.co/spaces/webml-community/dinov3-web) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | DINOv3 Web (this page) | 162 | static | apache-2.0 | 2025-08-15 | | [InferenceSupport](https://mindket.com/p/c095c739-2ded-4c01-93eb-b7067a50441e) | 764 | static | afl-3.0 | 2025-04-16 | | [Huggy](https://mindket.com/p/0e832fcc-5ae8-4b46-84cb-24febb45fb2d) | 463 | static | cc-by-nc-sa-4.0 | 2024-05-24 | | [Z-Image Lookalike LoRA Index](https://mindket.com/p/b982ec25-ae82-40ac-9834-49980598d3bd) | 189 | static | apache-2.0 | 2026-10-30 | | [Granite Docling 258M WebGPU](https://mindket.com/p/d4317b48-bbb7-4a8d-8c83-a8c60857aad1) | 163 | static | apache-2.0 | 2025-10-06 | | [Semantic Galaxy](https://mindket.com/p/614cb97a-0930-4daf-a1a6-477dcf4e54a5) | 157 | static | apache-2.0 | 2026-05-12 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2025-08-15 - First published: 2025-08-15 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open webml-community/dinov3-web on Hugging Face](https://huggingface.co/spaces/webml-community/dinov3-web) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4cf9a723-8afb-4b07-bad9-d5dcb4203f2e) - [Its page on Mindket](https://mindket.com/p/4cf9a723-8afb-4b07-bad9-d5dcb4203f2e)