Rice Disease Detector

Rice Disease Detector

A Gradio app from dnth that, going by its name, detects rice plant diseases in pictures, with a saved checkpoint and eight sample images. For students and growers curious about plant disease detection.

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 Detector is a Gradio app from dnth. As its name says, it is meant to detect rice plant diseases in pictures. The repository holds a saved model checkpoint and eight 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 detector 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 look at the result
Education | Students | See a vision model in a finished app | Run one of the eight sample images
Machine learning | Practitioners | Study how a checkpoint is wrapped in an app | Read app.py next to the checkpoint 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 | The model's output for the image
Try the samples | Newcomers | Quick results from the eight sample images

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
• The system packages in packages.txt, which Hugging Face installs with apt-get

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-detector --repo-type space --local-dir rice-disease-detector
cd rice-disease-detector
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 includes eight sample pictures 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 eight sample pictures. You get back the model's result for that picture, though the README does not say what form it takes.

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

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

You give the app a rice picture
The app loads the saved checkpoint
The model processes the image
The page shows the result

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

Links

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