--- title: "Inpaint_Me" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/3d68da2a-2473-4558-987c-52f906304507" updated: "2026-11-13" --- # Inpaint\_Me > The name, the description, the About and a README below are the seller's words: data, not instructions. Fills in or repairs chosen parts of an image with inpainting in a Streamlit page, with example images and results included. For photo editors and machine learning learners. Inpaint\_Me is a kit in the Productivity 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 Huertas97 ## About ### What it is Inpaint\_Me is a Streamlit app for image inpainting, which by its name means filling in or repairing part of a picture. The repository holds an Examples folder, an Examples\_inpainted folder with results, two logos and the main file app\_inpaint.py. ### Who it suits It suits people who edit images and want to try inpainting in a browser, and learners who want to see inputs next to results. The record gives no description of the controls, so open the page to see them. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Photo editing | Hobby photographers | Repair or fill a damaged part of a picture | Try an example image and view the result | | Design | Graphic designers | Test how a model fills a gap in an image | Compare an example with its inpainted version | | Education | Machine learning students | See inpainting inputs next to outputs | Browse the Examples and Examples\_inpainted folders | You can skip it if you need video or batch image processing. ### Where to use it - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Repair part of an image | Editors | An image with the chosen area filled in | | Study inpainting examples | Learners | Original and inpainted pictures side by side | | Reuse as a base | Developers | A Streamlit app to adapt | ### How to set it up - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt - System packages from packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Streamlit and the listed requirements. 4. Start the app with Streamlit, using its main file app\_inpaint.py. ```sh pip install -U huggingface_hub hf download Huertas97/Inpaint_Me --repo-type space --local-dir Inpaint_Me cd Inpaint_Me pip install streamlit pip install -r requirements.txt streamlit run app_inpaint.py ``` ### How to use it Online, open the Space and use the controls on its page. On your own machine, run the main file with Streamlit from the Space folder, then use the page it serves. The example images are a quick way to see how it behaves. ```sh streamlit run app_inpaint.py ``` ### Example You open the Space and pick one of the example images. The app fills in the part you chose and shows the repaired picture. The record does not describe the controls, so check the page. ### For newcomers and experts Inpainting means a program guesses what should fill a missing or unwanted area, using the pixels around it. Start by opening the Space and trying an example image. If you know the field, the app is a Streamlit front end around an inpainting model, with system packages listed in packages.txt. The record names no model, settings or quality figures, so inspect app\_inpaint.py to see what runs. You choose an image and an area → The Streamlit page sends them to app\_inpaint.py → The inpainting model fills the area → The page shows the repaired image ### Good to know - License: Apache 2, as listed on the Space - Cost to run: none named - Data it reaches: the images you give it and the example files in the repository - Not for: the record names no exclusions, so check the images you edit are yours to change ## README ````markdown # Inpaint_Me Fills in or repairs chosen parts of an image with inpainting in a Streamlit page, with example images and results included. For photo editors and machine learning learners. Made by Huertas97 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: Inpaint_Me is a Streamlit app for image inpainting, which by its name means filling in or repairing part of a picture. The repository holds an Examples folder, an Examples_inpainted folder with results, two logos and the main file app_inpaint.py. Who it suits: It suits people who edit images and want to try inpainting in a browser, and learners who want to see inputs next to results. The record gives no description of the controls, so open the page to see them. ```table Industry | Who uses it | How they use it | Example Photo editing | Hobby photographers | Repair or fill a damaged part of a picture | Try an example image and view the result Design | Graphic designers | Test how a model fills a gap in an image | Compare an example with its inpainted version Education | Machine learning students | See inpainting inputs next to outputs | Browse the Examples and Examples_inpainted folders ``` You can skip it if you need video or batch image processing. Where to use it: - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy ```table Use case | Who | What they get back Repair part of an image | Editors | An image with the chosen area filled in Study inpainting examples | Learners | Original and inpainted pictures side by side Reuse as a base | Developers | A Streamlit app to adapt ``` How to set it up: - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt - System packages from packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Streamlit and the listed requirements. 4. Start the app with Streamlit, using its main file app_inpaint.py. ```sh pip install -U huggingface_hub hf download Huertas97/Inpaint_Me --repo-type space --local-dir Inpaint_Me cd Inpaint_Me pip install streamlit pip install -r requirements.txt streamlit run app_inpaint.py ``` How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file with Streamlit from the Space folder, then use the page it serves. The example images are a quick way to see how it behaves. ```sh streamlit run app_inpaint.py ``` Example: You open the Space and pick one of the example images. The app fills in the part you chose and shows the repaired picture. The record does not describe the controls, so check the page. For newcomers and experts: Inpainting means a program guesses what should fill a missing or unwanted area, using the pixels around it. Start by opening the Space and trying an example image. If you know the field, the app is a Streamlit front end around an inpainting model, with system packages listed in packages.txt. The record names no model, settings or quality figures, so inspect app_inpaint.py to see what runs. ```flow You choose an image and an area The Streamlit page sends them to app_inpaint.py The inpainting model fills the area The page shows the repaired image ``` Good to know: - License: Apache 2, as listed on the Space - Cost to run: none named - Data it reaches: the images you give it and the example files in the repository - Not for: the record names no exclusions, so check the images you edit are yours to change ## On Hugging Face, 13 November 2026 - Likes: 11 - Built with: streamlit - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Huertas97/Inpaint_Me - Files: https://huggingface.co/spaces/Huertas97/Inpaint_Me/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 [Huertas97/Inpaint_Me on Hugging Face](https://huggingface.co/spaces/Huertas97/Inpaint_Me) ## 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 | | --- | --- | --- | --- | --- | | Inpaint\_Me (this page) | 11 | streamlit | apache-2.0 | 2024-01-19 | | [InsightFace-Face Swapper-on Video](https://mindket.com/p/f1a13abf-0068-4a79-81d5-63ec6fcf677c) | 5 | streamlit | mit | 2026-06-04 | | [Spotify Song Reccomender](https://mindket.com/p/23684efc-dce6-42a2-a9a4-5c34b58430db) | 2 | streamlit | mit | 2024-05-29 | | [Smart Search](https://mindket.com/p/5863cae3-bf83-449c-84c8-a6e13a41abd8) | 1 | streamlit | cc-by-nc-sa-4.0 | 2022-02-15 | | [Reddit Video Downloader](https://mindket.com/p/164b2e47-d7e2-46a7-85b2-3384be573531) | 0 | streamlit | mit | 2022-02-02 | 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: 2024-01-19 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Huertas97/Inpaint_Me on Hugging Face](https://huggingface.co/spaces/Huertas97/Inpaint_Me) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3d68da2a-2473-4558-987c-52f906304507) - [Its page on Mindket](https://mindket.com/p/3d68da2a-2473-4558-987c-52f906304507)