Mindket

Photo Enhancer

Newversion 1 · updated

Overview

Restores detail in noisy, soft or heavily compressed photos at the same size or 2x larger, using the MegaPotato model on a static page. Free demo for logged-in Hugging Face users.

Photo Enhancer is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • A web browser
  • A Hugging Face login, to enhance your own photos
  • Python and pip, only to fetch a local copy
Runs in
  • A web browser, on the Space's page at Hugging Face
  • A local copy of the page files, which still sends uploads to the maker's service
  • Your own code, through the maker's REST API
Start with
pip install -U huggingface_hub
hf download MegaPotatoAI/Photo-Enhancer --repo-type space --local-dir Photo-Enhancer
cd Photo-Enhancer

Platform

PhoneRuns on it

About

What it is

Photo Enhancer is a static web page that cleans up grainy, soft or compressed photos with the MegaPotato model. It can keep the original size or double it. It aims to work from what is already in the photo and not to draw new faces or text. The model runs on the maker's own service.

Who it suits

It suits anyone with old, noisy or over-compressed photos who wants to see a cleaner version beside the original.

IndustryWho uses itHow they use itExample
PhotographyPhotographersClean up grainy or soft shotsEnhance a noisy low-light photo
ArchivesArchivistsImprove scanned historical picturesOpen one of the examples taken from public archives
Real estateAgentsRefresh compressed listing photosRun a heavily compressed picture at the original size
SoftwareDevelopersCall the same model from code through the maker's REST APIRead the API notes in the README

Skip it if you need to run the model offline, since the weights are not published.

Where to use it

  • A web browser, on the Space's page at Hugging Face
  • A local copy of the page files, which still sends uploads to the maker's service
  • Your own code, through the maker's REST API
Use caseWhoWhat they get back
Clean up one photoPhotographersA restored version at the same size or 2x larger
Compare before and afterEveryoneTwo views side by side with zoom
Try it without logging inNewcomersReal example results that anyone can open

How to set it up

The online page needs a browser and, for your own photos, a Hugging Face login. A local copy needs Python only to fetch the files.

  • A web browser
  • A Hugging Face login, to enhance your own photos
  • Python and pip, only to fetch a local copy
  1. Install the Hugging Face hub library.
  2. Download the Space's files into a folder named Photo-Enhancer.
  3. Move into that folder.
  4. Load index.html in a web browser.
pip install -U huggingface_hub
hf download MegaPotatoAI/Photo-Enhancer --repo-type space --local-dir Photo-Enhancer
cd Photo-Enhancer

How to use it

Work through the page in order.

  1. Pick a photo by choosing a file or dropping it on the page. PNG, JPEG and WebP all work.
  2. Choose Original size or 2x, then press Enhance.
  3. View the before and after images beside each other, then zoom to 100% or 200%.
  4. On a phone, the Inspect button does the zooming.
  5. To keep the full-size file, make a free account on the maker's own site and upload the photo there.

Example

You open one of the real examples, a grainy old photograph. You compare the before and after views side by side and zoom in to check the fine detail.

For newcomers and experts

Open an example first. Examples need no login and show what the enhancer does before you spend a daily run on your own photo.

The page is static HTML. Uploads go to a Cloudflare service that holds the API key, enforces the demo limits and forwards the image to the maker's API. The proprietary model runs on the maker's GPUs. The README reports the maker's own blind test of 18 upscalers, in which none of 67 faces turned into a different person. It notes that this is its own evaluation and that its product is one of those compared.

  1. You choose a photo
  2. A Cloudflare service checks the demo limits
  3. The maker's model restores it on its GPUs
  4. You compare before and after

Good to know

  • Limits: The free demo gives you 2 runs a day. The count follows your network address across a rolling 24 hours. Size limits match those of the full product.
  • License: The demo code is MIT. Access to the model and API follows the maker's service terms.
  • Cost to run: The demo is free with a Hugging Face login. Downloads need an account on the maker's site, and new accounts get free chips.
  • Data it reaches: Your uploads go to the maker's service. Each image is checked automatically before processing, and some may be refused. The original is removed when the run ends, and the result about an hour later.
  • Not for: Running the model on your own machine, since the weights are not published.

README and files

README

Photo Enhancer

Restores detail in noisy, soft or heavily compressed photos at the same size or 2x larger, using the MegaPotato model on a static page. Free demo for logged-in Hugging Face users.

Made by MegaPotatoAI 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: Photo Enhancer is a static web page that cleans up grainy, soft or compressed photos with the MegaPotato model. It can keep the original size or double it. It aims to work from what is already in the photo and not to draw new faces or text. The model runs on the maker's own service.

Who it suits: It suits anyone with old, noisy or over-compressed photos who wants to see a cleaner version beside the original.

Industry | Who uses it | How they use it | Example
Photography | Photographers | Clean up grainy or soft shots | Enhance a noisy low-light photo
Archives | Archivists | Improve scanned historical pictures | Open one of the examples taken from public archives
Real estate | Agents | Refresh compressed listing photos | Run a heavily compressed picture at the original size
Software | Developers | Call the same model from code through the maker's REST API | Read the API notes in the README

Skip it if you need to run the model offline, since the weights are not published.

Where to use it:

  • A web browser, on the Space's page at Hugging Face
  • A local copy of the page files, which still sends uploads to the maker's service
  • Your own code, through the maker's REST API
Use case | Who | What they get back
Clean up one photo | Photographers | A restored version at the same size or 2x larger
Compare before and after | Everyone | Two views side by side with zoom
Try it without logging in | Newcomers | Real example results that anyone can open

How to set it up: The online page needs a browser and, for your own photos, a Hugging Face login. A local copy needs Python only to fetch the files.

  • A web browser
  • A Hugging Face login, to enhance your own photos
  • Python and pip, only to fetch a local copy
  1. Install the Hugging Face hub library.
  2. Download the Space's files into a folder named Photo-Enhancer.
  3. Move into that folder.
  4. Load index.html in a web browser.
pip install -U huggingface_hub
hf download MegaPotatoAI/Photo-Enhancer --repo-type space --local-dir Photo-Enhancer
cd Photo-Enhancer

How to use it: Work through the page in order.

  1. Pick a photo by choosing a file or dropping it on the page. PNG, JPEG and WebP all work.
  2. Choose Original size or 2x, then press Enhance.
  3. View the before and after images beside each other, then zoom to 100% or 200%.
  4. On a phone, the Inspect button does the zooming.
  5. To keep the full-size file, make a free account on the maker's own site and upload the photo there.

Example: You open one of the real examples, a grainy old photograph. You compare the before and after views side by side and zoom in to check the fine detail.

For newcomers and experts: Open an example first. Examples need no login and show what the enhancer does before you spend a daily run on your own photo.

The page is static HTML. Uploads go to a Cloudflare service that holds the API key, enforces the demo limits and forwards the image to the maker's API. The proprietary model runs on the maker's GPUs. The README reports the maker's own blind test of 18 upscalers, in which none of 67 faces turned into a different person. It notes that this is its own evaluation and that its product is one of those compared.

You choose a photo
A Cloudflare service checks the demo limits
The maker's model restores it on its GPUs
You compare before and after

Good to know:

  • Limits: The free demo gives you 2 runs a day. The count follows your network address across a rolling 24 hours. Size limits match those of the full product.
  • License: The demo code is MIT. Access to the model and API follows the maker's service terms.
  • Cost to run: The demo is free with a Hugging Face login. Downloads need an account on the maker's site, and new accounts get free chips.
  • Data it reaches: Your uploads go to the maker's service. Each image is checked automatically before processing, and some may be refused. The original is removed when the run ends, and the result about an hour later.
  • Not for: Running the model on your own machine, since the weights are not published.

On Hugging Face, 13 November 2026

  • Likes: 11
  • Built with: static
  • License: mit

Links

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.

Files
README.md  5 KB

1 file, 5 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
Photo Enhancer This page11staticmit
AI Image UpscalerShares image-enhancement · super-resolution · image-to-image21staticmit
AI Face RestorationShares image-restoration · super-resolution · image-to-image4staticmit
4K UpscalerShares super-resolution · image-to-image · static11staticmit
Seedream 5.0 Pro EditShares image-to-image2dockermit
DALL·E miniShares static5,750staticapache-2.0
Numbers as Mindket last read them, on 2026-11-12.

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