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A Gradio app from frapochetti that, going by its name, repaints a picture in the look of another style with a fast neural network. For people who want to try image style transfer in a browser.
Fast Neural Style Transfer 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.
pip install -U huggingface_hub hf download frapochetti/fast-neural-style-transfer --repo-type space --local-dir fast-neural-style-transfer cd fast-neural-style-transfer
Fast Neural Style Transfer is a Gradio app from frapochetti. Going by its name, it redraws a picture in the look of a chosen style using a fast neural network. The repository holds a model definition, a models folder and one sample photo of a dog. The README is empty, so the controls are not described.
It suits people who like playing with image styles, and students who want to see a small style transfer model served in a web app.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Design | Designers and hobbyists | Try a stylized look on a photo | Upload a picture and view the stylized copy |
| Education | Students | Study style transfer in practice | Read model.py next to the weights folder |
| Social media | Content makers | Make playful picture variants | Stylize a casual snapshot |
You can skip it if you need exact control over the style, since the source lists no style options.
| Use case | Who | What they get back |
|---|---|---|
| Stylize a photo | Hobbyists | The picture redrawn in a new style, if the app works as named |
| Try the sample | Newcomers | A quick look using the included dog photo |
| Study the model | Students | A small PyTorch-style model file and weights folder |
pip install -U huggingface_hub hf download frapochetti/fast-neural-style-transfer --repo-type space --local-dir fast-neural-style-transfer cd fast-neural-style-transfer pip install gradio pip install -r requirements.txt python app.py
Open the Space and give it a picture. If the page offers a choice of style, pick one. The README gives no steps, so follow the page's own controls. On your own copy, start the app with this command and open the local page Gradio prints.
python app.py
Open the Space online and use the sample dog photo from the repository, if the page offers it. You should get the same picture back in a new style, though the source does not describe the options.
If you are new, start with the sample dog photo, then try your own picture. Photos with clear shapes and good light tend to show style changes well.
If you know the field, the repository holds model.py and a models folder, so the app loads trained style networks and runs a single forward pass per image. That is what makes the approach fast, but the README does not say which styles or architecture it uses.
A Gradio app from frapochetti that, going by its name, repaints a picture in the look of another style with a fast neural network. For people who want to try image style transfer in a browser.
Made by frapochetti 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: Fast Neural Style Transfer is a Gradio app from frapochetti. Going by its name, it redraws a picture in the look of a chosen style using a fast neural network. The repository holds a model definition, a models folder and one sample photo of a dog. The README is empty, so the controls are not described.
Who it suits: It suits people who like playing with image styles, and students who want to see a small style transfer model served in a web app.
Industry | Who uses it | How they use it | Example
Design | Designers and hobbyists | Try a stylized look on a photo | Upload a picture and view the stylized copy
Education | Students | Study style transfer in practice | Read model.py next to the weights folder
Social media | Content makers | Make playful picture variants | Stylize a casual snapshot
You can skip it if you need exact control over the style, since the source lists no style options.
Where to use it:
Use case | Who | What they get back
Stylize a photo | Hobbyists | The picture redrawn in a new style, if the app works as named
Try the sample | Newcomers | A quick look using the included dog photo
Study the model | Students | A small PyTorch-style model file and weights folder
How to set it up:
pip install -U huggingface_hub
hf download frapochetti/fast-neural-style-transfer --repo-type space --local-dir fast-neural-style-transfer
cd fast-neural-style-transfer
pip install gradio
pip install -r requirements.txt
python app.py
How to use it: Open the Space and give it a picture. If the page offers a choice of style, pick one. The README gives no steps, so follow the page's own controls. On your own copy, start the app with this command and open the local page Gradio prints.
python app.py
Example: Open the Space online and use the sample dog photo from the repository, if the page offers it. You should get the same picture back in a new style, though the source does not describe the options.
For newcomers and experts: If you are new, start with the sample dog photo, then try your own picture. Photos with clear shapes and good light tend to show style changes well.
If you know the field, the repository holds model.py and a models folder, so the app loads trained style networks and runs a single forward pass per image. That is what makes the approach fast, but the README does not say which styles or architecture it uses.
You give the app a picture
The app loads a trained style network
One pass redraws the picture
The page shows the stylized result
Good to know:
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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| Product | Likes | Built with | License | Last change |
|---|---|---|---|---|
| Fast Neural Style Transfer This page | 6 | gradio | apache-2.0 | |
| MusicGenShares gradio | 5,116 | gradio | cc-by-nc-4.0 | |
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| Omni Image EditorShares gradio | 2,922 | gradio | mit | |
| Diffusers Image OutpaintShares gradio | 2,565 | gradio | apache-2.0 |
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