Projected GAN

Projected GAN

A Gradio app that wraps a GAN image generator from the autonomousvision group, built to try in a browser. Its README gives no description, so the page shows what it takes and returns.

Made by autonomousvision 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: Projected GAN is a Gradio app on Hugging Face Spaces from the autonomousvision group. It wraps a GAN, a kind of image generating network, and its settings name a model whose title ends in Pokemon. The code is app.py with a requirements.txt, and it is built with Gradio 6.14.0 on Python 3.10.

Who it suits: It suits people who want to try an image generating model in a browser, and learners who want a short example of wrapping a GAN in a Gradio page.

Industry | Who uses it | How they use it | Example
Machine learning | Students | Read app.py to see how a GAN is called from a page | Download the Space and open app.py
Digital art | Hobbyists | Try the generator and look at what it makes | Open the Space and follow what the page asks for
Education | Instructors | Show a generative model running in a web page | Run the Space in a lesson

Anyone who needs training code, documented settings or output quality can skip it, since the README gives none.

Where to use it:

• A web browser, straight from the Space page on Hugging Face
• A local copy on Windows, macOS or Linux, using Python 3.10

Use case | Who | What they get back
Try the generator online | Anyone curious | Generated images shown in the browser
Study a GAN demo | Learners | A short app file that calls the named model

How to set it up: Using it online needs nothing. A local copy needs these first.

• Python 3.10 and pip
• The huggingface_hub package, to fetch the files
• Gradio 6.14.0, and the packages in requirements.txt

1. Install the Hugging Face Hub package.
2. Download the Space into a folder called projected_gan.
3. Move into that folder.
4. Install Gradio 6.14.0, then the packages from requirements.txt.
5. Start the app.

pip install -U huggingface_hub
hf download autonomousvision/projected_gan --repo-type space --local-dir projected_gan
cd projected_gan
pip install gradio==6.14.0
pip install -r requirements.txt
python app.py

How to use it: Open the Space page on Hugging Face and use the page that loads. For a local copy, run python app.py in the folder and open the page it starts.

Example: You run python app.py inside the projected_gan folder. The Gradio page comes up in your browser, and you try it there the same way as on the Space page.

For newcomers and experts: If you are new, open the Space page first and see what it offers. Nothing needs installing, so you can try it straight away.

If you know the field, the repository is only an app file and a requirements list, and the model itself is named in the settings. Training data, architecture and sample quality are not described in the source.

Open the Space or run python app.py
app.py loads the named GAN model
Gradio shows the page in your browser

Good to know:

• The README gives no description, so inputs and outputs are clear only on the page
• It is built for Python 3.10 and Gradio 6.14.0
• License: mit
• Cost to run: none named
• Data it reaches: the model it names

On Hugging Face, 13 November 2026

• Likes: 15
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/autonomousvision/projected_gan
• Files: https://huggingface.co/spaces/autonomousvision/projected_gan/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.