Huashu Design
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A Gradio app from jasperai for fast image relighting with Latent Bridge Matching, which runs online in the browser or on your computer with Python 3.12.
LBM Relighting is a kit in the Developer 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.
pip install -U huggingface_hub hf download jasperai/LBM_relighting --repo-type space --local-dir LBM_relighting cd LBM_relighting
LBM Relighting is a Gradio app that jasperai published as a Hugging Face Space. It relights images quickly using Latent Bridge Matching. It names the jasperai/LBM_relighting model along with IC-Light, Stable Diffusion XL base and BiRefNet, and it runs on zero-a10g hardware at Hugging Face.
People who want to change the lighting of an image in a browser, and developers who want the app's files to read or run themselves.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Photography | Photo editors | Open the Space and relight an image | Trying a different light on a portrait |
| E-commerce | Product teams | Relight product photos | Matching the light across a set of images |
| Machine learning | Researchers | Download the files and read app.py and utils.py | Studying how the model and helpers are put together |
Skip it if you want a hosted service with an API, since this is an app you open or run yourself.
LBM Relighting runs in these places.
| Use case | Who | What they get back |
|---|---|---|
| Try it online | Anyone with a browser | The Gradio app running from the Space |
| Relight an image | Photo editors | The image with new lighting |
| Run it locally | Developers with Python | A copy of the app started from app.py |
Online use needs only a browser. A local copy needs a few things first.
pip install -U huggingface_hub hf download jasperai/LBM_relighting --repo-type space --local-dir LBM_relighting cd LBM_relighting pip install gradio==5.49.1 pip install -r requirements.txt python app.py
Online, open the Space's page and give the app an image to relight. The repository ships an examples folder to start from. On your own computer, start the app from the folder with the command below.
python app.py
| Tool | What it does |
|---|---|
| python app.py | Starts the Gradio app from the main file |
| pip install -r requirements.txt | Installs the packages the app needs |
| hf download | Fetches the Space's files into a local folder |
You open the Space and give it one of the example images. The app relights it and returns the image with the new lighting.
If you are new, open the Space's page and start from an example image. Running it online needs no setup, so start there before you try a local copy.
If you know the field, the Space names four models, the LBM relighting model, IC-Light, Stable Diffusion XL base and BiRefNet. A local copy pins Gradio 5.49.1. The Space itself uses zero-a10g hardware at Hugging Face, so a local run depends on your own machine.
It is a single Gradio app, so what you can do is limited to what its page offers.
A Gradio app from jasperai for fast image relighting with Latent Bridge Matching, which runs online in the browser or on your computer with Python 3.12.
Made by jasperai 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.
What it is: LBM Relighting is a Gradio app that jasperai published as a Hugging Face Space. It relights images quickly using Latent Bridge Matching. It names the jasperai/LBM_relighting model along with IC-Light, Stable Diffusion XL base and BiRefNet, and it runs on zero-a10g hardware at Hugging Face.
Who it suits: People who want to change the lighting of an image in a browser, and developers who want the app's files to read or run themselves.
Industry | Who uses it | How they use it | Example
Photography | Photo editors | Open the Space and relight an image | Trying a different light on a portrait
E-commerce | Product teams | Relight product photos | Matching the light across a set of images
Machine learning | Researchers | Download the files and read app.py and utils.py | Studying how the model and helpers are put together
Skip it if you want a hosted service with an API, since this is an app you open or run yourself.
Where to use it: LBM Relighting runs in these places.
Use case | Who | What they get back
Try it online | Anyone with a browser | The Gradio app running from the Space
Relight an image | Photo editors | The image with new lighting
Run it locally | Developers with Python | A copy of the app started from app.py
How to set it up: Online use needs only a browser. A local copy needs a few things first.
pip install -U huggingface_hub
hf download jasperai/LBM_relighting --repo-type space --local-dir LBM_relighting
cd LBM_relighting
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py
How to use it: Online, open the Space's page and give the app an image to relight. The repository ships an examples folder to start from. On your own computer, start the app from the folder with the command below.
python app.py
Tool | What it does
python app.py | Starts the Gradio app from the main file
pip install -r requirements.txt | Installs the packages the app needs
hf download | Fetches the Space's files into a local folder
Example: You open the Space and give it one of the example images. The app relights it and returns the image with the new lighting.
For newcomers and experts: If you are new, open the Space's page and start from an example image. Running it online needs no setup, so start there before you try a local copy.
If you know the field, the Space names four models, the LBM relighting model, IC-Light, Stable Diffusion XL base and BiRefNet. A local copy pins Gradio 5.49.1. The Space itself uses zero-a10g hardware at Hugging Face, so a local run depends on your own machine.
Open the Space or run app.py
You give it an image
The model relights it
You get the relit image back
Good to know: It is a single Gradio app, so what you can do is limited to what its page offers.
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.
README.md 4 KB
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