Practica1 by Jacampo

Practica1 by Jacampo

Runs a saved image model in a Gradio page, with two example pictures to try. The model file is named for blindness, but the record does not say what it predicts. A course-style demo.

Made by Jacampo 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: Practica1 is a Gradio app built around a saved model file named export_blindness.pkl and two example pictures. The file name hints at an eye-related image task, but the record does not say what the model predicts. The repository is small, with a README, the app file and a package list.

Who it suits: It suits students and developers who want a tiny example of a saved image model served with Gradio. The name reads like a course exercise. It is a demo and does not replace any medical advice or test.

Industry | Who uses it | How they use it | Example
Education | Machine learning students | Study a simple saved model inside a web page | Read app.py next to export_blindness.pkl
Software | Python developers | Copy the folder layout for their own image demo | Swap the example pictures and the model file
Hobby projects | Curious makers | Try the two example pictures | Click an example and read the output

You can skip it if you want a documented tool, because the record says nothing about its purpose or accuracy.

Where to use it:

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

Use case | Who | What they get back
Try the demo | Anyone | The model's output for an example picture
Study the structure | Learners | A small app with a model file and examples
Reuse as a base | Developers | A starting folder for their own classifier

How to set it up:

• Nothing at all if you use the online Space
• Python on your computer, only if you run a copy
• The packages listed in requirements.txt

1. Open the Space's page in a browser to use it with nothing to install.
2. To run a copy, install the Hugging Face Hub package and download the Space.
3. Move into the new folder, then install Gradio and the listed requirements.
4. Start the app with Python.

pip install -U huggingface_hub
hf download Jacampo/Practica1 --repo-type space --local-dir Practica1
cd Practica1
pip install gradio
pip install -r requirements.txt
python app.py

How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file from the Space folder, then use the page it serves. The two example pictures are the quickest way to see what it does.

python app.py

Example: You open the Space and pick one of the example pictures. The app runs its saved model on it and shows the output on the page. The record does not describe the output, so look at it yourself.

For newcomers and experts: A saved model is a file holding what a program learned, so the app can use it without training again. Start by opening the Space and clicking an example picture.

If you know the field, the folder shows a common course-style pattern: Gradio for the page, one exported model and a few sample inputs. No metrics, training data or class names are given, so inspect the files before trusting any output.

You pick or upload a picture
The Gradio page sends it to app.py
The saved model in export_blindness.pkl runs on it
The page shows the result

Good to know:

• License: afl-3, as listed on the Space
• Cost to run: none named
• Data it reaches: the images you give it and the saved model file
• Not for: medical decisions, since the record gives no purpose, accuracy or validation figures

On Hugging Face, 13 November 2026

• Likes: 0
• Built with: gradio
• License: afl-3.0

Links

• Space: https://huggingface.co/spaces/Jacampo/Practica1
• Files: https://huggingface.co/spaces/Jacampo/Practica1/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.