--- title: "YOLOv10 Document Layout Analysis" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/3d46fd92-760f-4582-83a5-1cb57e4cb6b1" updated: "2026-11-12" --- # YOLOv10 Document Layout Analysis > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app that analyzes the layout of a document with a YOLOv10 model, for people who want to see page layout detection run in a browser or on their own computer. YOLOv10 Document Layout Analysis is a kit in the Productivity 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 omoured ## About ### What it is YOLOv10 Document Layout Analysis is a small Gradio app that, going by its title, studies the layout of a document with a YOLOv10 model. Layout analysis means finding where the parts of a page sit. The repository holds the app code and a models folder. ### Who it suits It suits people who handle documents and want to see layout detection working before they build anything around it. Who might use this app | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Document processing | Developers | Try a layout model before building a pipeline around it | Run one sample page through the app | | Computer vision | Students | See a YOLOv10 model applied to documents | Open the Space and test a page of your choice | | Digitization | Records and archive teams | Check how a layout model reads their pages | Try a page from a scanned file | If you need an API for batch jobs, you can skip it, since the notes describe none. ### Where to use it You can use it online or on your own machine. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: a local copy that runs with Python - Hugging Face Spaces: where the hosted app runs, on the cpu-basic hardware tier What the app is good for | Use case | Who | What they get back | | --- | --- | --- | | Try layout detection online | Anyone curious | The app's analysis of a page you supply | | Run it locally | Developers | A copy of the app running on their own machine | | Test YOLOv10 on documents | Students | A look at what the model makes of a page | ### How to set it up The hosted app needs nothing. A local copy needs Python and pip. - Python, with pip - The Python packages that requirements.txt lists 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 4.32.2. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub pip install gradio==4.32.2 pip install -r requirements.txt python app.py ``` Put your own value in its key setting first. ### How to use it Open the Space online, or start your copy with the command below. Then use the controls on the page to supply a document and read what the app returns. ```sh python app.py ``` The files you will meet | Tool | What it does | | --- | --- | | app.py | Starts the Gradio page when you run it with Python | | requirements.txt | Lists the Python packages the app needs | | models | A folder in the repository that sits beside the app code | ### Example You open the Space, give it one page of a document and let the YOLOv10 model analyze it. The page then shows what the model found about that page's layout. ### For newcomers and experts If you are new to this, open the Space and try one page first. Then try a page with a more complicated layout and compare what comes back. If you know the field, the title names YOLOv10 as the detector, and the front end is Gradio 4.32.2. The hosted copy runs on cpu-basic hardware, so inference there happens on a CPU. The notes give no training details or class list. Open the Space or run app.py → Supply a page from a document → The YOLOv10 model analyzes its layout → You read the result on the page ### Good to know The Space's notes say little about the app, so open it to see exactly what it returns. - Hosting: the hosted copy runs on cpu-basic hardware - Notes: the README only points to Hugging Face's configuration reference - License: cc-by-4 - Cost to run: none named - Data it reaches: the document you supply, plus the Python packages pip installs from requirements.txt ## README ````markdown # YOLOv10 Document Layout Analysis A Gradio app that analyzes the layout of a document with a YOLOv10 model, for people who want to see page layout detection run in a browser or on their own computer. Made by omoured 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: YOLOv10 Document Layout Analysis is a small Gradio app that, going by its title, studies the layout of a document with a YOLOv10 model. Layout analysis means finding where the parts of a page sit. The repository holds the app code and a models folder. Who it suits: It suits people who handle documents and want to see layout detection working before they build anything around it. ```table Title: Who might use this app Industry | Who uses it | How they use it | Example Document processing | Developers | Try a layout model before building a pipeline around it | Run one sample page through the app Computer vision | Students | See a YOLOv10 model applied to documents | Open the Space and test a page of your choice Digitization | Records and archive teams | Check how a layout model reads their pages | Try a page from a scanned file ``` If you need an API for batch jobs, you can skip it, since the notes describe none. Where to use it: You can use it online or on your own machine. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: a local copy that runs with Python - Hugging Face Spaces: where the hosted app runs, on the cpu-basic hardware tier ```table Title: What the app is good for Use case | Who | What they get back Try layout detection online | Anyone curious | The app's analysis of a page you supply Run it locally | Developers | A copy of the app running on their own machine Test YOLOv10 on documents | Students | A look at what the model makes of a page ``` How to set it up: The hosted app needs nothing. A local copy needs Python and pip. - Python, with pip - The Python packages that requirements.txt lists 1. Install the huggingface_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 4.32.2. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub pip install gradio==4.32.2 pip install -r requirements.txt python app.py ``` Put your own value in its key setting first. How to use it: Open the Space online, or start your copy with the command below. Then use the controls on the page to supply a document and read what the app returns. ```sh python app.py ``` ```table Title: The files you will meet Tool | What it does app.py | Starts the Gradio page when you run it with Python requirements.txt | Lists the Python packages the app needs models | A folder in the repository that sits beside the app code ``` Example: You open the Space, give it one page of a document and let the YOLOv10 model analyze it. The page then shows what the model found about that page's layout. For newcomers and experts: If you are new to this, open the Space and try one page first. Then try a page with a more complicated layout and compare what comes back. If you know the field, the title names YOLOv10 as the detector, and the front end is Gradio 4.32.2. The hosted copy runs on cpu-basic hardware, so inference there happens on a CPU. The notes give no training details or class list. ```flow Open the Space or run app.py Supply a page from a document The YOLOv10 model analyzes its layout You read the result on the page ``` Good to know: The Space's notes say little about the app, so open it to see exactly what it returns. - Hosting: the hosted copy runs on cpu-basic hardware - Notes: the README only points to Hugging Face's configuration reference - License: cc-by-4 - Cost to run: none named - Data it reaches: the document you supply, plus the Python packages pip installs from requirements.txt ## On Hugging Face, 13 November 2026 - Likes: 45 - Built with: gradio - License: cc-by-4.0 ## Links - Space: https://huggingface.co/spaces/omoured/YOLOv10-Document-Layout-Analysis - Files: https://huggingface.co/spaces/omoured/YOLOv10-Document-Layout-Analysis/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 [omoured/YOLOv10-Document-Layout-Analysis on Hugging Face](https://huggingface.co/spaces/omoured/YOLOv10-Document-Layout-Analysis) ## 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 | | --- | --- | --- | --- | --- | | YOLOv10 Document Layout Analysis (this page) | 45 | gradio | cc-by-4.0 | 2024-06-02 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | 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: 2024-06-02 - First published: 2024-06-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open omoured/YOLOv10-Document-Layout-Analysis on Hugging Face](https://huggingface.co/spaces/omoured/YOLOv10-Document-Layout-Analysis) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3d46fd92-760f-4582-83a5-1cb57e4cb6b1) - [Its page on Mindket](https://mindket.com/p/3d46fd92-760f-4582-83a5-1cb57e4cb6b1)