Surfrider

Surfrider

A Gradio app from the Surfrider account with data, models and tracking folders, which points to a model plus tracking pipeline. Suits developers and students who want to read a tracking demo or try it in a browser.

Made by Surfrider 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: Surfrider is a Gradio app published by the Surfrider account under the address surfnet. Its repository has data, models and tracking folders next to app.py, which points to a trained model followed by a tracking step. The page has no description, so what it tracks is not confirmed.

Who it suits: Developers and students who want to read a small tracking pipeline or try it in a browser, and people who already know the Surfrider project.

Industry | Who uses it | How they use it | Example
Software | Developers | Read the tracking and models folders to see how the pipeline is organised | Open the tracking folder next to app.py
Education | Computer vision students | Run the demo and study how detection and tracking connect | Try the Space with a sample input
Research | Environmental and vision teams | Check the demo against their own material | Compare its output with their own notes

Skip it if you need documented behaviour, because the page does not explain the inputs or outputs.

Where to use it:

• A web browser, on the Space's page on Hugging Face
• Python 3.9.14 on Windows, macOS or Linux, using a downloaded copy

Use case | Who | What they get back
Try the demo online | Anyone curious | Whatever the app returns for your input
Study a tracking project | Students and developers | A Python project with data, models and tracking code to read

How to set it up:

• Nothing to install for the online version
• Python 3.9.14 for a local copy
• The packages listed in requirements.txt
• The system packages in packages.txt, which the hosted Space installs with apt-get

1. Install the Hugging Face hub package.
2. Download the Space's files to a folder.
3. Move into that folder.
4. Install gradio 3.0.12, then the packages from requirements.txt.
5. Start the app with app.py.

pip install -U huggingface_hub
hf download Surfrider/surfnet --repo-type space --local-dir surfnet
cd surfnet
pip install gradio==3.0.12
pip install -r requirements.txt
python app.py

How to use it: Open the Space page in a browser and follow the controls it shows. For a local copy, run the app and open the page Gradio opens for you.

python app.py

Tool | What it does
python app.py | Starts the Gradio app on your computer
hf download | Copies the Space's files into a local folder

Example: Open the Space and give it one of the inputs it asks for. The app should return the result of its model and tracking steps. The page does not say what the input or the result looks like, so rely on what the page shows.

For newcomers and experts: If you are new to this, open the Space and try the simplest input it offers before reading any code. Expect a demo, not a finished product.

If you know the field, the layout suggests a detection model kept in a models folder and a tracker kept in a tracking folder. The page names no model, dataset or metric. It pins an old Gradio, 3.0.12, and Python 3.9.14.

An input goes in
The model in the models folder runs
The tracking code follows results
Gradio shows the output

Good to know:

• The page gives no description, so inputs, outputs and accuracy are not stated.
• It pins Gradio 3.0.12 and Python 3.9.14, so a local copy needs that older setup.
• License: mit.
• Cost to run: none named, only the packages in requirements.txt and packages.txt.
• Data it reaches: the input you give it. On the hosted Space, that input is handled on Hugging Face.
• Not for: the source names none.

On Hugging Face, 13 November 2026

• Likes: 7
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/Surfrider/surfnet
• Files: https://huggingface.co/spaces/Surfrider/surfnet/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.