Zero DCE Low Light Image Enhancement

Zero DCE Low Light Image Enhancement

Brightens dark photos with the Zero-DCE low-light enhancement model from the Keras team in a Gradio page, with sample images included. For photographers and learners.

Made by keras-io 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 app brightens photos taken in low light, using the Zero-DCE method. The record names one Keras model, low-light-image-enhancement. Several sample pictures sit in the repository, including a file named got_final.png.

Who it suits: It suits photographers and hobbyists with dark pictures, and machine learning learners who want to see a low-light method run. Developers can read it as a small Gradio demo around a Keras model.

Industry | Who uses it | How they use it | Example
Photography | Hobby photographers | Lift detail out of a dim photo | Upload a night shot and compare it with the result
Education | Machine learning students | See what a low-light enhancement model does | Run the bundled sample pictures
Software | Python developers | Read a small Gradio demo around a Keras model | Open app.py and requirements.txt

You can skip it if your pictures are already well lit.

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
Brighten a dark photo | Photographers | A lighter version of the picture
Try the bundled samples | Anyone | A quick before and after look
Reuse as a base | Developers | A small Gradio app around a Keras model

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

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 Gradio and the listed requirements.
4. Start the app with Python.

pip install -U huggingface_hub
hf download keras-io/low-light-image-enhancement --repo-type space --local-dir low-light-image-enhancement
cd low-light-image-enhancement
pip install gradio
pip install -r requirements.txt
python app.py

How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The sample pictures are the quickest way to try it.

python app.py

Example: You open the Space and give it a dark photo, such as one of the samples. The app returns a brighter version that you can set beside the original. The record shows no sample output, so the exact display depends on the page.

For newcomers and experts: Photos shot in dim light look dark and muddy. A low-light model brightens them and tries to keep details visible. Start by opening the Space and running one of the sample pictures.

If you know the field, Zero-DCE learns a set of brightness curves for an image without needing paired dark and bright photos. The record gives no figures on quality or speed, so judge the results by eye on your own photos.

You give the page a dark photo
The Gradio page sends it to app.py
The Zero-DCE model estimates brightness curves
The page shows the brighter picture

Good to know:

• License: Apache 2, as listed on the Space
• Cost to run: none named
• Data it reaches: the pictures you give it and the model it names
• Not for: the record names no exclusions, and it gives no quality figures

On Hugging Face, 13 November 2026

• Likes: 15
• Built with: gradio
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/keras-io/low-light-image-enhancement
• Files: https://huggingface.co/spaces/keras-io/low-light-image-enhancement/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.