Landmark Detection

Landmark Detection

A Gradio app whose name points to landmark detection, built to try in a browser. Its README gives no description, so the page shows what it takes and returns.

Made by coolzude 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: Landmark Detection is a Gradio app on Hugging Face Spaces. Its name points to finding landmarks, but the README is only the settings template and does not say which kind or what the app takes in. The code is app.py, and requirements.txt lists the Python packages.

Who it suits: It suits people who want to try a landmark detection demo in a browser, and learners who want a short Gradio example to read.

Industry | Who uses it | How they use it | Example
Computer vision | Students | Read app.py to see how the detection step is built | Download the Space and open app.py
Machine learning | Hobbyists | Run a copy locally to try the app | Start python app.py after installing the packages
Education | Instructors | Use the small repository as a classroom example | Show the three files and how they fit

Anyone who needs documented inputs, outputs or accuracy can skip it, since the README gives none.

Where to use it:

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

Use case | Who | What they get back
Try the app online | Anyone curious | The Gradio page running in the browser with nothing to install
Study a detection demo | Learners | A short repository with one app file and one requirements file

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

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

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

pip install -U huggingface_hub
hf download coolzude/Landmark-Detection --repo-type space --local-dir Landmark-Detection
cd Landmark-Detection
pip install gradio
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 Landmark-Detection 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. It shows what the app asks for and what it gives back, with nothing to install.

If you know the field, the settings name no model, so the detection logic sits in app.py and its requirements. The kind of landmark, the method and the accuracy are not stated.

Open the Space or run python app.py
app.py runs the detection step
Gradio shows the result in your browser

Good to know:

• The README gives no description, so the exact input and output are clear only on the page
• It needs Gradio and the packages in requirements.txt
• License: mit
• Cost to run: none named
• Data it reaches: none named

On Hugging Face, 13 November 2026

• Likes: 1
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/coolzude/Landmark-Detection
• Files: https://huggingface.co/spaces/coolzude/Landmark-Detection/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.