Rice Disease Classifier

Rice Disease Classifier

A Gradio app from dnth that, going by its name, classifies rice plant diseases from pictures, with a saved learner file and sample images. For students and growers curious about plant disease classifiers.

Made by dnth 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: Rice Disease Classifier is a Gradio app from dnth. As its name says, it is meant to sort pictures of rice plants by disease. The repository holds a saved learner file and a folder of sample images. The README carries only the standard Space settings text.

Who it suits: It suits students, growers and agriculture hobbyists who want to see a small plant disease classifier at work.

Industry | Who uses it | How they use it | Example
Agriculture | Growers and advisers | Try a picture-based disease check | Upload a photo of a rice leaf and read the label
Education | Students | See an image classifier in a finished app | Run one of the sample images
Machine learning | Practitioners | Study a small classifier deployment | Read app.py next to the learner file

You can skip it if you need a field-ready diagnosis, since this is a demo with no stated accuracy.

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
Check a rice picture | Growers and students | A predicted disease label for the image
Try the samples | Newcomers | Quick results from the sample images 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.

pip install -U huggingface_hub
hf download dnth/rice-disease-classifier --repo-type space --local-dir rice-disease-classifier
cd rice-disease-classifier
pip install gradio
pip install -r requirements.txt
python app.py

How to use it: Open the Space and give it a picture of a rice plant. The repository has a sample images folder you can try first. 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.

python app.py

Example: Open the Space online and run one of the sample images. You get back a predicted label for that picture, though the README does not list which diseases the model knows.

For newcomers and experts: If you are new, start with a sample image, then try a clear close-up of a single leaf. Treat the result as a hint and not a diagnosis.

If you know the field, the repository pairs app.py with a saved learner file, which means the app loads a trained model and runs it on a picture. The README gives no classes, dataset, accuracy or training details, so validate it on your own images.

You give the app a rice picture
The app loads the saved learner
The model predicts a label
The page shows the prediction

Good to know:

• License: afl-3
• Cost to run: none named. The online Space runs on Hugging Face.
• Data it reaches: the pictures you give it, and the saved learner file in its repository.
• Not for: farm decisions made on its output alone. The README states no accuracy.

On Hugging Face, 13 November 2026

• Likes: 1
• Built with: gradio
• License: afl-3.0

Links

• Space: https://huggingface.co/spaces/dnth/rice-disease-classifier
• Files: https://huggingface.co/spaces/dnth/rice-disease-classifier/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.