---
title: CDIApp
emoji: 🏆
colorFrom: red
colorTo: black
sdk: gradio
sdk_version: 5.4.0
app_file: app.py
pinned: false
license: apache-2.0
---

# Plant Disease Classification
## Generated by Claude v3

This is a deep learning project for classifying plant diseases from images. It uses a convolutional neural network trained on a dataset of plant disease images.

## Features

- Train a disease classification model on your own dataset
- Evaluate model performance on a test set
- Run inference on new images through a web interface

## Installation

1. Clone the repository:

```
git clone https://github.com/username/plant-disease-classifier.git
```

2. Install dependencies:

```
cd plant-disease-classifier
pip install -r requirements.txt
```

## Usage

### Data Preparation

Organize your image data into folders for each disease class, for example:

```
data/
  healthy/
    image1.jpg
    image2.jpg
    ...
  disease_a/
    image1.jpg
    image2.jpg
    ...
  disease_b/
    ...
```

### Training

To train the model, run:

```
python train_classifier.py --data_dir data/
```

This will save the trained model to the `models/` directory.

### Evaluation

Evaluate the model on a test set:

```
python evaluate.py --data_dir data/test/ --model models/classifier.pth
```

This will print the classification metrics.

### Inference

To launch the web interface for running inference on new images:

```
python app.py
```

Then open `http://localhost:5000` in your web browser. You can upload images and see the predicted disease class.

## Contributing

Contributions are welcome! Please open an issue or submit a pull request.

## License

This project is licensed under the [MIT License](LICENSE).