README.md

---
title: 'CropGuard: Leaf Disease Detector'
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 5.27.1
app_file: app.py
pinned: false
---

# CropGuard: Leaf Disease Detector

**CropGuard** is a lightweight, deployable machine learning app that detects **leaf diseases** in **Potato**, **Tomato**, and **Grape** plants from user-uploaded or captured images.

Built using **PyTorch**, **Gradio**, **Docker**, and **Hugging Face Spaces**, it provides the following capabilities:

- Upload or capture a leaf image
- Predict plant health status
- Identify likely disease (if any)
- Visualize model attention using **GradCAM++** heatmaps
- Provide quick disease information and treatment suggestions

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## Project Structure

```
CropGuard/
├── app.py                # Gradio app
├── Dockerfile            # Docker container definition
├── requirements.txt      # Python dependencies
├── src/                  # Source code (organized into modules)
│   ├── app/
│   ├── data/
│   ├── model/
│   └── utils/
├── sample_images/        # Few test images (optional for demo)
├── disease_info.json     # Disease descriptions
└── README.md             # (this file)
```

## License

MIT License.

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## Acknowledgments

- **Dataset:** [PlantVillage Dataset](https://www.kaggle.com/datasets/mohitsingh1804/plantvillage)
- **Base Model:** [MobileNetV2 (pretrained on ImageNet)](https://arxiv.org/abs/1801.04381)
- **Visualization:** GradCAM++

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## Author

Made by **[Arka Mitra](https://github.com/mitraarka27)** © 2025.

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