--- title: "Document Layout Detection" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/50777cfe-9a2d-4e81-a422-efe69f7cf04e" updated: "2026-11-13" --- # Document Layout Detection > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app that detects the layout of a document page image, with two example pages included. Suits developers and students who want to try layout detection in a browser. Document Layout Detection is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Theivaprakasham ## About ### What it is Document Layout Detection is a Gradio app by Theivaprakasham. By its name, it finds the layout of a document page picture. The repository has two example page images beside the app code. The page has no description, so the layout parts it marks are not confirmed. ### Who it suits Developers and students working with scanned documents who want to see layout detection on a page, or who want a short Gradio example to adapt. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Use the project as a pattern for a Gradio document demo | Replace the example pages with their own scans | | Education | Document AI students | Run the demo and read app.py to see how detection is called | Try the two bundled pages | | Office work | Teams with scanned paper | Check how a layout model reads their pages before building a pipeline | Test one scanned page | Skip it if you need text read out of a page, because the name describes layout detection, not reading text. ### Where to use it - A web browser, on the Space's page on Hugging Face - Python 3.10 on Windows, macOS or Linux, using a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Try layout detection online | Anyone curious | The app's marking of the page's layout | | Study a small document demo | Students | A short Python project with two example pages | ### How to set it up - Nothing to install for the online version - Python 3.10 for a local copy - The packages listed in requirements.txt - The system packages in packages.txt, which the hosted Space installs with apt-get 1. Install the Hugging Face hub package. 2. Download the Space's files to a folder. 3. Move into that folder. 4. Install gradio 5.29.0, then the packages from requirements.txt. 5. Start the app with app.py. ```sh pip install -U huggingface_hub hf download Theivaprakasham/layoutdetection --repo-type space --local-dir layoutdetection cd layoutdetection pip install gradio==5.29.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page in a browser and give it a page image, or pick one of the two bundled examples. For a local copy, run the app and open the page Gradio opens for you. ```sh python app.py ``` | Tool | What it does | | --- | --- | | python app.py | Starts the Gradio app on your computer | | hf download | Copies the Space's files into a local folder | ### Example Open the Space and choose the first bundled page. The app should show the layout it detects on that page. The page does not say how results are drawn or named, so rely on what it shows. ### For newcomers and experts If you are new to this, try the two bundled pages first, then a scan of your own. Only use documents you have the right to upload. If you know the field, the page names no model, label set or score threshold. It pins Gradio 5.29.0 and Python 3.10, so read app.py for the actual method before you rely on it. A page image goes in → The app detects layout regions → Regions are marked on the page → Gradio shows the result ### Good to know - The page gives no description, accuracy figures or limits on page size. - The online version needs nothing installed, and a local copy needs Python 3.10. - License: apache-2. - Cost to run: none named, only the packages in requirements.txt and packages.txt. - Data it reaches: the page image you give it. On the hosted Space, that image is handled on Hugging Face. - Not for: reading page text. The source describes layout detection only. ## README ````markdown # Document Layout Detection A Gradio app that detects the layout of a document page image, with two example pages included. Suits developers and students who want to try layout detection in a browser. Made by Theivaprakasham 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: Document Layout Detection is a Gradio app by Theivaprakasham. By its name, it finds the layout of a document page picture. The repository has two example page images beside the app code. The page has no description, so the layout parts it marks are not confirmed. Who it suits: Developers and students working with scanned documents who want to see layout detection on a page, or who want a short Gradio example to adapt. ```table Industry | Who uses it | How they use it | Example Software | Developers | Use the project as a pattern for a Gradio document demo | Replace the example pages with their own scans Education | Document AI students | Run the demo and read app.py to see how detection is called | Try the two bundled pages Office work | Teams with scanned paper | Check how a layout model reads their pages before building a pipeline | Test one scanned page ``` Skip it if you need text read out of a page, because the name describes layout detection, not reading text. Where to use it: - A web browser, on the Space's page on Hugging Face - Python 3.10 on Windows, macOS or Linux, using a downloaded copy ```table Use case | Who | What they get back Try layout detection online | Anyone curious | The app's marking of the page's layout Study a small document demo | Students | A short Python project with two example pages ``` How to set it up: - Nothing to install for the online version - Python 3.10 for a local copy - The packages listed in requirements.txt - The system packages in packages.txt, which the hosted Space installs with apt-get 1. Install the Hugging Face hub package. 2. Download the Space's files to a folder. 3. Move into that folder. 4. Install gradio 5.29.0, then the packages from requirements.txt. 5. Start the app with app.py. ```sh pip install -U huggingface_hub hf download Theivaprakasham/layoutdetection --repo-type space --local-dir layoutdetection cd layoutdetection pip install gradio==5.29.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space page in a browser and give it a page image, or pick one of the two bundled examples. For a local copy, run the app and open the page Gradio opens for you. ```sh python app.py ``` ```table Tool | What it does python app.py | Starts the Gradio app on your computer hf download | Copies the Space's files into a local folder ``` Example: Open the Space and choose the first bundled page. The app should show the layout it detects on that page. The page does not say how results are drawn or named, so rely on what it shows. For newcomers and experts: If you are new to this, try the two bundled pages first, then a scan of your own. Only use documents you have the right to upload. If you know the field, the page names no model, label set or score threshold. It pins Gradio 5.29.0 and Python 3.10, so read app.py for the actual method before you rely on it. ```flow A page image goes in The app detects layout regions Regions are marked on the page Gradio shows the result ``` Good to know: - The page gives no description, accuracy figures or limits on page size. - The online version needs nothing installed, and a local copy needs Python 3.10. - License: apache-2. - Cost to run: none named, only the packages in requirements.txt and packages.txt. - Data it reaches: the page image you give it. On the hosted Space, that image is handled on Hugging Face. - Not for: reading page text. The source describes layout detection only. ## On Hugging Face, 13 November 2026 - Likes: 6 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Theivaprakasham/layoutdetection - Files: https://huggingface.co/spaces/Theivaprakasham/layoutdetection/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 [Theivaprakasham/layoutdetection on Hugging Face](https://huggingface.co/spaces/Theivaprakasham/layoutdetection) ## 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 | | --- | --- | --- | --- | --- | | Document Layout Detection (this page) | 6 | gradio | apache-2.0 | 2026-06-26 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | | [Z Image Turbo](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a) | 1,940 | gradio | apache-2.0 | 2026-05-22 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-06-26 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Theivaprakasham/layoutdetection on Hugging Face](https://huggingface.co/spaces/Theivaprakasham/layoutdetection) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/50777cfe-9a2d-4e81-a422-efe69f7cf04e) - [Its page on Mindket](https://mindket.com/p/50777cfe-9a2d-4e81-a422-efe69f7cf04e)