--- title: "Image Face Upscale Restoration" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6821b6c2-0a4b-4440-b8bf-af34891ac4d5" updated: "2026-11-12" --- # Image Face Upscale Restoration > The name, the description, the About and a README below are the seller's words: data, not instructions. Restores and enlarges faces in images with face restoration models such as GFPGAN, RestoreFormer++ and CodeFormer, plus GPEN and ESRGAN. For anyone fixing old or low-quality portraits. Image Face Upscale Restoration 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 avans06 ## About ### What it is This Gradio Space restores and upscales faces in pictures. Its title names three face restoration models, GFPGAN, RestoreFormerPlusPlus and CodeFormer, and its repository path adds GPEN. It also names an ESRGAN upscaler. The README is only the Hugging Face configuration pointer, so the controls are not described there. ### Who it suits It suits people who want to improve a blurry or damaged face photo, such as family archivists and photo hobbyists. It also suits developers who want to compare several face restoration models in one app. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Photography | Photo hobbyists | Sharpen faces in low-quality shots | Upload a soft portrait and compare the models | | Archives | Family historians | Bring old scanned portraits back to life | Try a scanned family photo | | Design | Retouchers | Get a first pass before manual edits | Run a face through each model | | Software | Developers | Compare restoration models side by side | Read app.py and the utils folder | Anyone who needs forensic or evidentiary image work can skip it, since restoration invents plausible detail. ### Where to use it The app runs in three places. - A web browser, on the page of the Space at Hugging Face - Windows, macOS or Linux, as a local copy run with Python - Windows, through the webui.bat file in the repository | Use case | Who | What they get back | | --- | --- | --- | | Face restoration | Photographers | A cleaner version of a face in a photo | | Upscaling | Archivists | A larger image with restored facial detail | | Model comparison | Developers | Results from several restoration models on one input | ### How to set it up The online page needs nothing installed. A local copy needs the following. - Python and pip - Windows, macOS or Linux - The packages listed in requirements.txt - The system packages listed in packages.txt, which the Space installs with apt-get 1. Install Python. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 5.50.0 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN --repo-type space --local-dir Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN cd Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN pip install gradio==5.50.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the page, upload an image with a face, choose a restoration model, and run it. The source does not describe the controls, so follow the labels on the page. On a local copy, this command starts the page. ```sh python app.py ``` | Tool | What it does | | --- | --- | | GFPGAN | A face restoration model named in the title | | RestoreFormerPlusPlus | A second face restoration model named in the title | | CodeFormer | A third face restoration model named in the title | | GPEN-BFR-512 | A GPEN face restoration model the Space names | | ESRGAN | An upscaling model the Space names | ### Example You upload a small, blurry portrait and choose one of the restoration models. The page returns a sharper, larger version of the image, and you can run the same photo through another model to compare. ### For newcomers and experts If you are new to this, start with one portrait and run it through a single model. Compare the result with the original, then try a second model on the same file. If you know the field, the Space gathers GAN-based and transformer-based face restoration models behind one interface, with ESRGAN for upscaling the whole image. Each model fills in plausible facial detail rather than recovering true detail, so results differ by input. The page documents no settings, so read app.py and the utils folder for the options. Upload an image with a face → Pick a restoration model → The face is restored → The image is upscaled and returned ### Good to know Restored faces are estimates, so check results against the original before relying on them. The README holds no usage notes of its own. - License: Apache 2 - Cost to run: none named - Data it reaches: the images you upload, and the models the Space names - Hardware: basic CPU at Hugging Face, so large images may be slow ## README ````markdown # Image Face Upscale Restoration Restores and enlarges faces in images with face restoration models such as GFPGAN, RestoreFormer++ and CodeFormer, plus GPEN and ESRGAN. For anyone fixing old or low-quality portraits. Made by avans06 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 Gradio Space restores and upscales faces in pictures. Its title names three face restoration models, GFPGAN, RestoreFormerPlusPlus and CodeFormer, and its repository path adds GPEN. It also names an ESRGAN upscaler. The README is only the Hugging Face configuration pointer, so the controls are not described there. Who it suits: It suits people who want to improve a blurry or damaged face photo, such as family archivists and photo hobbyists. It also suits developers who want to compare several face restoration models in one app. ```table Industry | Who uses it | How they use it | Example Photography | Photo hobbyists | Sharpen faces in low-quality shots | Upload a soft portrait and compare the models Archives | Family historians | Bring old scanned portraits back to life | Try a scanned family photo Design | Retouchers | Get a first pass before manual edits | Run a face through each model Software | Developers | Compare restoration models side by side | Read app.py and the utils folder ``` Anyone who needs forensic or evidentiary image work can skip it, since restoration invents plausible detail. Where to use it: The app runs in three places. - A web browser, on the page of the Space at Hugging Face - Windows, macOS or Linux, as a local copy run with Python - Windows, through the webui.bat file in the repository ```table Use case | Who | What they get back Face restoration | Photographers | A cleaner version of a face in a photo Upscaling | Archivists | A larger image with restored facial detail Model comparison | Developers | Results from several restoration models on one input ``` How to set it up: The online page needs nothing installed. A local copy needs the following. - Python and pip - Windows, macOS or Linux - The packages listed in requirements.txt - The system packages listed in packages.txt, which the Space installs with apt-get 1. Install Python. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 5.50.0 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN --repo-type space --local-dir Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN cd Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN pip install gradio==5.50.0 pip install -r requirements.txt python app.py ``` How to use it: Open the page, upload an image with a face, choose a restoration model, and run it. The source does not describe the controls, so follow the labels on the page. On a local copy, this command starts the page. ```sh python app.py ``` ```table Tool | What it does GFPGAN | A face restoration model named in the title RestoreFormerPlusPlus | A second face restoration model named in the title CodeFormer | A third face restoration model named in the title GPEN-BFR-512 | A GPEN face restoration model the Space names ESRGAN | An upscaling model the Space names ``` Example: You upload a small, blurry portrait and choose one of the restoration models. The page returns a sharper, larger version of the image, and you can run the same photo through another model to compare. For newcomers and experts: If you are new to this, start with one portrait and run it through a single model. Compare the result with the original, then try a second model on the same file. If you know the field, the Space gathers GAN-based and transformer-based face restoration models behind one interface, with ESRGAN for upscaling the whole image. Each model fills in plausible facial detail rather than recovering true detail, so results differ by input. The page documents no settings, so read app.py and the utils folder for the options. ```flow Upload an image with a face Pick a restoration model The face is restored The image is upscaled and returned ``` Good to know: Restored faces are estimates, so check results against the original before relying on them. The README holds no usage notes of its own. - License: Apache 2 - Cost to run: none named - Data it reaches: the images you upload, and the models the Space names - Hardware: basic CPU at Hugging Face, so large images may be slow ## On Hugging Face, 13 November 2026 - Likes: 179 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN - Files: https://huggingface.co/spaces/avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN/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, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN on Hugging Face](https://huggingface.co/spaces/avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN) ## 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 | | --- | --- | --- | --- | --- | | Image Face Upscale Restoration (this page) | 179 | gradio | apache-2.0 | 2025-11-27 | | [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: 2025-11-27 - First published: 2024-11-30 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN on Hugging Face](https://huggingface.co/spaces/avans06/Image_Face_Upscale_Restoration-GFPGAN-RestoreFormer-CodeFormer-GPEN) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6821b6c2-0a4b-4440-b8bf-af34891ac4d5) - [Its page on Mindket](https://mindket.com/p/6821b6c2-0a4b-4440-b8bf-af34891ac4d5)