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title: Plant Disease Detector
emoji: π
colorFrom: green
colorTo: green
sdk: gradio
sdk_version: 5.34.2
app_file: app.py
pinned: false
---
# π Plant Disease Detector
This is a Gradio-based web app for detecting fruit and leaf diseases using an EfficientNetB0-based CNN model.
π§ **Model Overview**
- **Architecture:** EfficientNetB0 (transfer learning)
- **Input Size:** 160Γ160 RGB
- **Classes:** 21 fruit/leaf disease types (mango, guava, lime, pomegranate)
- **Framework:** TensorFlow / Keras
- **Performance:** ~99.5% train accuracy, ~98.5% validation accuracy
πΌοΈ **How to Use**
- Upload a fruit/leaf image via the interface
- The model will return the predicted disease name and confidence %
- You can also try it using the provided example images
π **Example Images**
Sample images are available in the `examples/` folder:
- `Phytopthora.jpg`
- `RedRust.jpg`
- `HealthyMangoLeaf.jpg`
- `LimeLeafSpotted.jpg`
π οΈ **Dependencies**
All dependencies are listed in `requirements.txt`:
- `tensorflow`
- `gradio`
- `numpy`
- `pillow`
πββοΈ **Author**
Aarzoo Singh
Research Intern, Machine Learning
B.Tech CSE, NIT Patna
π [Hugging Face Profile](https://huggingface.co/Aarzoo-Singh2206)
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π **Live App:** [Click here to run this app](https://huggingface.co/spaces/Aarzoo-Singh2206/codeblock) |