--- title: "Fast Neural Style Transfer" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/0713effe-8b89-4d17-8228-5e64f14c62b2" updated: "2026-11-12" --- # Fast Neural Style Transfer > The name, the description, the About and a README below are the seller's words: data, not instructions. 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 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by frapochetti ## About ### 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 - A web browser, on the Space's page at Hugging Face - Your own computer, on Windows, macOS or Linux | 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 - Nothing to install if you use the Space online - Python, if you run a copy on your own computer - The Python packages in requirements.txt 1. Open the Space's page on Hugging Face to use it online. 2. To run a copy, install huggingface\_hub and download the Space into a folder. 3. Move into that folder and install Gradio, then the listed packages. 4. Start the app with Python. ```sh 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. ```sh 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 - License: apache-2 - Cost to run: none named. The online Space runs on Hugging Face. - Data it reaches: the pictures you give it, and the model files in its repository. - Limits: no style list, resolution limit or speed figures are given. ## README ````markdown # Fast Neural Style Transfer 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. ## About 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. ```table 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: - A web browser, on the Space's page at Hugging Face - Your own computer, on Windows, macOS or Linux ```table 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: - Nothing to install if you use the Space online - Python, if you run a copy on your own computer - The Python packages in requirements.txt 1. Open the Space's page on Hugging Face to use it online. 2. To run a copy, install huggingface_hub and download the Space into a folder. 3. Move into that folder and install Gradio, then the listed packages. 4. Start the app with Python. ```sh 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. ```sh 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. ```flow 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: - License: apache-2 - Cost to run: none named. The online Space runs on Hugging Face. - Data it reaches: the pictures you give it, and the model files in its repository. - Limits: no style list, resolution limit or speed figures are given. ## On Hugging Face, 13 November 2026 - Likes: 6 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/frapochetti/fast-neural-style-transfer - Files: https://huggingface.co/spaces/frapochetti/fast-neural-style-transfer/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, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [frapochetti/fast-neural-style-transfer on Hugging Face](https://huggingface.co/spaces/frapochetti/fast-neural-style-transfer) ## 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 | | --- | --- | --- | --- | --- | | Fast Neural Style Transfer (this page) | 6 | gradio | apache-2.0 | 2022-02-05 | | [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: 2022-02-05 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open frapochetti/fast-neural-style-transfer on Hugging Face](https://huggingface.co/spaces/frapochetti/fast-neural-style-transfer) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/0713effe-8b89-4d17-8228-5e64f14c62b2) - [Its page on Mindket](https://mindket.com/p/0713effe-8b89-4d17-8228-5e64f14c62b2)